INTERNATIONAL COURT OF JUSTICE
DISPUTE OVER THE STATUS AND USE OF THE
WATERS OF THE SILALA
(CHILE v. BOLIVIA)
REPLY OF THE
REPUBLIC OF CHILE
ANNEXES XI - XIV TO THE EXPERT REPORTS
VOLUME 3 OF 3
15 FEBRUARY 2019
i
LIST OF ANNEXES TO THE
EXPERT REPORTS
VOLUME 3
ANNEXES XI - XIV
ANNEX Nº TITLE PAGE Nº
Annex XI Herrera, C. and Aravena, R., 2019. Chemical and
Isotopic Characterization of Surface Water and
Groundwater of the Silala River Transboundary
Basin, Second Region, Chile
1
Annex XII Herrera, C. and Aravena, R., 2019. Chemical
Characterization of Surface Water and Groundwater
of the Quebrada Negra, Second Region, Chile
69
Annex XIII Muñoz, J.F. and Suárez, F., 2019. Quebrada Negra
Wetland Study
83
Annex XIV SERNAGEOMIN (National Geology and Mining
Service), 2019. Geology of the Silala River: An
Updated Interpretation
187
Data CD CD-ROM containing supporting data to Annexes
XI – XIV
273
Appendix C to
Annex XIV
Blanco, N. and Polanco, E., 2018. Geology of the
Silala River Basin, Northern Chile
273
ii
Annex XI
Herrera, C. and Aravena, R., 2019. Chemical and
Isotopic Characterization of Surface Water and
Groundwater of the Silala River Transboundary Basin,
Second Region, Chile
1
2
Annex XI
3
CHEMICAL AND ISOTOPIC CHARACTERIZATION OF SURFACE
WATER AND GROUNDWATER OF THE SILALA RIVER
TRANSBOUNDARY BASIN, SECOND REGION, CHILE
Christian Herrera (PhD)
Associate Professor, Universidad Católica del Norte
Ramón Aravena (PhD)
Emeritus and Adjunct Professor, University of Waterloo
January 2019
4
Annex XI
GLOSSARY
Alkalinity: The name given to the quantitative capacity of an aqueous solution to
neutralize an acid.
Anion: An ionic species, with a net negative charge.
Aquifer: A permeable region of rock or soil capable of storing, transmitting and
yielding exploitable quantities of water.
Cation: An ionic species with a net positive charge.
Deuterium excess: The concept of deuterium excess (d) is defined as d = δ2H - 8δ18O.
The deuterium excess can be used to identify vapor source regions for air masses
producing precipitation that contribute to groundwater recharge.
Global meteoric line: An equation defined by the geochemist Harmon Craig that states
the average relationship between hydrogen and oxygen isotope ratios in natural
terrestrial waters, expressed as a worldwide average: δ2H = 8δ18O + 10‰.
Headwater: A tributary stream of a river, close to or forming part of its source.
Hydrochemical: Dealing with the chemical characteristics of bodies of water.
Ion: An atom or molecule with a net electrical charge due to the gain or loss of one or
more electrons.
Ion chromatography: A chromatography process that separates ions and polar
molecules based on their affinity to an ion exchanger.
Isotope: One or two or more species of the same chemical element, having the same
numbers of protons in the nucleus but differing from one another by having a different
numbers of neutrons. The isotopes of an element have slightly different physical
properties, owing to their mass differences, by which they can be separated.
Isotopic characterization: The identification of isotopic signature, the distribution of
certain stable isotopes and radioactive isotopes within chemical compounds.
Meteoric water line: A linear equation that defines the average relationship between
hydrogen and oxygen isotope ratios in rain waters in a defined area.
Mineralization: Process by which groundwater through interaction with minerals in the
aquifer incorporated chemical elements in the water.
Percent Modern Carbon (pMC): Unit to report radiocarbon dates. The reference is the
radiocarbon content of the atmospheric CO2 before 1950 defined as 100 percent modern
carbon.
Perched aquifer: Groundwater body, generally of moderate dimensions, supported by a
relatively impermeable stratum and which is located between a deeper water table and
the ground surface.
Annex XI
5
Plasma emission spectrometry: An analytical technique used for the detection of trace
elements. It is a type of emission spectroscopy that uses the inductively coupled plasma
to produce excited atoms and ions that emit electromagnetic radiation at wavelengths
characteristic of a particular element.
Radioactive isotope: A radioactive form of an element, consisting of atoms with
unstable nuclei, which undergo radioactive decay to stable forms, emitting characteristic
alpha, beta, or gamma radiation. These may occur naturally, as in the cases of tritium
and radiocarbon, or may be created artificially.
Recharge: Groundwater recharge (or deep drainage or deep percolation) is a hydrologic
process whereby water that has infiltrated the surface moves downward from the
unsaturated zone to groundwater. Recharge is the primary method through which water
enters an aquifer. Its source can be precipitation or surface water.
Redox process: A chemical reaction in which the oxidation states of atoms are
changed. Any such reaction involves both a reduction process and a complementary
oxidation process, two key concepts involved with electron transfer processes.
Salinity: The concentration of dissolved salts in water.
Silicate: A compound whose crystal structure contains SiO4
2-, either isolated or joined
through one or more of the oxygen atoms, to form groups, chains, sheets, or three
dimensional structures with metallic elements.
Silicate minerals: Silicate minerals are rock-forming minerals made up of silicate
groups. They are the largest and most important class of rock-forming minerals and
make up approximately 90 percent of the Earth's crust.
Stable isotope: One that does not transmute into another element with emission of
corpuscular or electromagnetic radiations.
Tritium: A radioactive isotope of hydrogen. The nucleus of tritium contains one proton
and two neutrons. Naturally occurring tritium is rare on Earth, where trace amounts are
formed by the interaction of the atmosphere with cosmic rays.
Volumetric method: A quantitative chemical analysis that involves the measurement of
volume of a solution of known concentration that is used to determine the concentration
of the analyte.
Weathering: The destructive process by which earth materials on exposure to
atmospheric agents (water, wind, temperature, etc.) at or near the Earth's surface are
changed in color, texture, composition, firmness or form, with little or no transport of
the loosened or altered material.
6
Annex XI
Annex XI
7
TABLE OF CONTENTS
1. INTRODUCTION.......................................................................................................... 1
1.1 Presentation................................................................................................................ 1
1.2 Location of the investigated area ............................................................................... 1
1.3 Objective of the report ............................................................................................... 2
1.4 Methodology.............................................................................................................. 3
1.5 Hydrogeochemical and isotopic data collected in the Bolivian sector (DHI, 2018) . 7
1.6 Structure of the report ................................................................................................ 8
2. RESULTS AND DISCUSSION..................................................................................... 8
2.1 Geochemistry data ..................................................................................................... 8
2.2 Environmental isotope data...................................................................................... 16
2.2.1 δ18O and δ2H data ........................................................................................... 17
2.2.2 Tritium data .................................................................................................... 22
2.2.3 Carbon-14 and Carbon-13 data ...................................................................... 24
3. CONCLUSIONS .......................................................................................................... 30
4. REFERENCES ............................................................................................................. 33
APPENDIX A ................................................................................................................... 35
APPENDIX B.................................................................................................................... 37
APPENDIX C.................................................................................................................... 41
APPENDIX D ................................................................................................................... 43
APPENDIX E.................................................................................................................... 55
APPENDIX F.................................................................................................................... 58
APPENDIX G ................................................................................................................... 60
8
Annex XI
Annex XI
9
1
1. INTRODUCTION
1.1 Presentation
The National Director of the Dirección Nacional de Fronteras y Límites del Estado
(DIFROL) of the Ministry of Foreign Affairs of Chile, Mrs. Ximena Fuentes, requested
a study on the hydrochemical and isotopic characterization of the transboundary basin
of the Silala River in the northern region of Chile as part of a study aimed at deepening
the hydrogeological knowledge of this basin. This report updates a 2017 report of
Herrera and Aravena (Chile’s Memorial (CM), Vol. 4, Annex III) and includes
hydrogeochemical and isotopic data collected in the Bolivian sector of the Silala River
presented in DHI (2018) as part of the Bolivian Counter-Memorial (BCM).
The study of the chemical and isotopic evolution of surface and groundwater in the
Silala River basin can contribute to the understanding of the complex interactions
between the river and the groundwater and mechanisms of local and regional recharge
to the river flow. In this context, the hydrogeochemical study of groundwater has been
an important approach to understand the flow of groundwater and to validate or discard
hypotheses about the conceptual understanding of the hydrogeology. This report was
elaborated under the supervision and instruction of Professors Howard Wheater and
Denis Peach.
1.2 Location of the investigated area
The headwaters of the Silala River are located above 4300 m.a.s.l. in Bolivian territory
where the perennial river flow originates from two wetland areas, the Cajones ravine
and the Orientales area, which are fed by groundwater from many springs. The recharge
area for these springs has been estimated to be much larger than the topographic
catchment and is included in Figure 1. After the river enters a ravine it crosses into
Chilean territory. In Chile, the basin is located between S -21.98° and S -22.06° latitude
and W -68.08° and W -68.02° longitude, in the second region of Chile. The Silala River
has carved a ravine at the border between Chile and Bolivia, into the existing bedrock,
that in some places is more than 10 m deep (Latorre and Frugone, 2017). Part of the
flow of the river is abstracted at a small impoundment just south west of the
international border in Chilean territory. A major ephemeral tributary, called the
Quebrada Negra (Figure 1), reaches the Silala River from the southeast, some 1700 m
downstream from the border. The upper course of the Silala River in Chile in this report
refers to the area between the international border and the junction with the Quebrada
Negra, whereas the lower course term refers to the area between the Quebrada Negra
10
Annex XI
2
and the CODELCO intake (Figure 1), which is a surface water abstraction intake
structure located downstream in the Silala River.
Figure 1. Location map of the study area. It depicts key features of the area, for example the
CODELCO intake and the upper and lower part of the Silala River in Chile, as defined in this
report.
1.3 Objective of the report
The main objective of this study is to characterize the chemistry and isotopic
composition of the surface and groundwater of the Silala River basin. Chemical and
isotopic tracers can potentially provide information to evaluate the mechanisms of rivergroundwater
interaction and the origins of waters in the Silala River basin. This report
also includes hydrogeochemical and isotopic data collected in the Bolivian sector of the
Silala River basin presented in DHI (2018) as part of the BCM. This information will be
used to complement the analysis of the data collected in the study carried out in the
Chilean part of the Silala River basin.
4
Kilometers
Mercator Projection, WGS 84
COjones
. \ MIiitary
.Post
o,.ienrales
""'SILALA RIVER BASIN
GROUNDWATER
CATCHMENT
~ · '!:;SI/ala
---SILALA RIVER
TOPOGRAPHIC
N CATCHMENT
Annex XI
11
3
1.4 Methodology
Four periods of field work were conducted in Chile during the study. The first was
carried out on 28 August 2016 by a multidisciplinary team. The main activities
performed during this field trip focused on evaluating the hydrogeological context of the
study area, and an evaluation of spring systems. The second and third field campaigns
were carried out between 19 and 21 December 2016 and during the period 31 January
2017 to 3 February 2017, respectively, and focused on water sample collection. These
campaigns were carried out in the rainy season. The fourth campaign was carried out
from 11 to 15 October 2017 corresponding to the dry season. During the second field
campaign, samples from springs, river and groundwater were collected for chemical and
isotopic analysis, the groundwater being sampled from boreholes drilled as part of the
hydrogeological investigation in the study area (Arcadis, 2017). A sampling location
map is presented in Figure 2. During the third campaign, samples of river water and a
larger number of springs were collected for chemical and isotope analysis. A sampling
location map for the third campaign is presented in Figure 3. During the third campaign
a survey of all the springs found on the northern flank of the ravine in the upper course
of the river in Chile was performed and in situ parameters including pH, electrical
conductivity and temperature were also measured. A location map showing the spring
sites is presented in Figure 4. During the fourth campaign, samples from river, springs
and groundwater from wells were collected for chemical and isotopic analysis. The
sampling locations are presented in Figure 5. The sampling protocol including materials
used is described in Appendix A; pictures of some of the sampling locations are
presented in Appendix B; and the analytical methods are detailed in Appendix C. Note
that samples are identified by sample location XXX-YYY-ZZ followed by a sample
date descriptor (-16, -17 and O17 for December 2016, January-February 2017, and
October 2017, respectively).
The chemical analysis included major cations and anions. The anions were determined
by ion chromatography (chloride, sulfate, nitrate) (Cl-, SO4
2-, NO3-) and volumetric
titration (bicarbonate) (HCO3
-), and cations (sodium, potassium, calcium, magnesium)
(Na+, K+, Ca2+, Mg2+) by plasma emission spectrometry (ICP-OES). The chemical
analyses were performed at the ALS Laboratory in Chile and the results are presented in
Tables 1 and 2 of this report.
The isotope analysis included oxygen-18 (18O) and deuterium (2H), tritium (3H) in water
samples and carbon 13 (13C) and carbon 14 (14C) in dissolved inorganic carbon. The
isotope analyses were carried out at IT2 Isotope Tracer Technologies Inc. in Canada as
presented in Appendix D, and the isotope data are reported in Tables 3 to 8 of this
report.
12
Annex XI
4
Figure 2. Sampling location map, second campaign, December 2016.
Hito
SIN-LXXIII
R-S12·
FCAB
SP-511-16 , CW-BO
CW-BO
.sP-s1-s-16 / r,,wL-u
CODELCO Inta"ke ' ~• PW-DQN-A-16 PPWW--UUQQNN--BA--1166
;:.,;;: PW-DQN-B-16 ;y . ,acallrl :'\,. -9.· \ R·R101-16
ollca Stall on '
0
S z ~ , ala ~.;,-?SPW·DQN·Sl-16
MW-DQN-A-16
Merc<1llJfPr..ijection, WG.$34
.;,; 1
c:-"'~ ./ \.,, -~ r .o~"~r ,3 r:}'"r'/
Annex XI
13
5
Figure 3. Sampling location map, third campaign, January-February 2017.
S/LALA RIVER BASIN
GROUNDWATER
CATCHMENT
/
Hito
S/N-LXXIII
FCAB In
SP-Sl-16-17 1, ...
SP·S1·28· 1 ~ P-Sl-lS-17
SP-S1-17-17•,I /
SP-Sl-19-17 ._ P-Sl-18-17
'SP-S1-9·17•
. SP-Sl-5-17 SP-Sl-27-17 ' r
CODELCOlntake •• .-, ~ ~ '-
~ ~ : Sf431:17 a<· 'F / R·S1-7-17
lnacallrf
,·. c lic•Station
,,R-S1-4-17
:'\,. . sP-51-29-17 "' R-Sl-3·l7
'9,.; -~ 0 St/aJo ~.:--::C
f
oi:: =====i6oc::o:::(==::::::11:co=o ====1aoo
Meter1
.;,;)1
14
Annex XI
6
Figure 4. Location map of the spring survey in the upper course of the river in Chile.
0
SILA lA RIVER BASIN
GROUNDWATER
CATCHMENT
/
d --.o-.<f.
o,,., o,,,_
~'Q
/ ,.i. "'"~ti 'f'-0
SP-FCAB-2 /
SP-FCAB-4 \ / FCAB'House
SP-FCAB-s,\ • ..rsP-FGAB-6
SP-NNl., ; ~ P-FCAB-3
SP-FCAB-7-• .t,__SP-FCAB-1
SP-NN2- t~ SP-FCAB·8
SP-FCAB-10 • SP·FCAB-9
SP-FCAB-n-....... • •♦sP-FCAB-12
SP-FCAB-14
SP·FCAB-15/
~
,J
• SP-FCAB-13
200
Meter,
Me«ator Projection, WGS 84 \
Annex XI
15
7
Figure 5. Sampling location map, fourth campaign, October 2017. This map also shows the
location of the samples collected in the Bolivian sector (DHI, 2018).
1.5 Hydrogeochemical and isotopic data collected in the Bolivian sector (DHI,
2018)
Hydrogeochemical and isotopic data collected in the Bolivian sector of the Silala River
basin and reported in DHI (2018) (BCM, Vol. 4, pp. 89-94), are used in this report as
part of the evaluation of the data collected in the Chilean sector.
The information provided in the Bolivian studies corresponds to:
− 14 chemical analyses of water samples from the Silala River basin in Bolivia,
which included springs and groundwater (piezometers). No data were reported
for the Silala River. The data were collected during different sampling
campaigns carried out for different studies between the years 2000-2001 and
2016-2017 (BCM, Vol. 4, pp. 539-542).
− 3 tritium and 14C analyses of springs obtained in 2004 (BCM, Vol. 4, p. 92)
(see Appendix G of this report).
Sample sites
• Springs
• Wells
" River
2400 Hito'o--_.,;,H;ctt;.o;,S::.l:N.:._
S/IHXXV
r
16
Annex XI
8
Only samples that have less than 10% ionic balance error in the chemical analyses were
used to construct the Stiff diagrams. These included samples from the Cajones ravine
(referred to in DHI (2018) as the North Wetland or Bofedal) and the Orientales area
(referred to in DHI (2018) as the South Wetland or Bofedal).
1.6 Structure of the report
Chapter 2 provides a description and discussion of the river, spring and groundwater
hydrochemistry from the three sampling campaigns in Chile. The discussions focus on
salinity patterns and the chemical composition of the different water types analyzed in
the study. It also contains a brief discussion of the Bolivian data. Subsequently the
stable isotopic composition of these waters is presented for each campaign. Here the
discussion focuses on the differences between the isotopic signatures of the river,
springs and groundwater in wells and their possible relationship to local and regional
recharge. The tritium and Carbon 14 data are also presented and discussed in Chapter 2,
within the context of the conceptual model of river-groundwater interaction in the Silala
River basin system. Chapter 3 details the conclusions drawn from the study where all
the data and information are integrated and a conceptual model for the rivergroundwater
interaction is proposed. Details of the sampling methods are reported in
Appendix A, whereas photographs recording some sampling activities are part of
Appendix B. Detailed information about analytical methods is described in Appendix C
and finally the official isotope data reported by the laboratory are presented in Appendix
D. Appendix E contains the Piper and Stiff diagrams for the rainy season. Appendix F
presents the chemical data from Bolivian lake, spring and well samples contained in
DHI (2018) and cited in this report, and Appendix G reproduces the Tritium and Carbon
14 data presented by DHI (2018), also cited in this report.
2. RESULTS AND DISCUSSION
2.1 Geochemistry data
The chemical data collected in the upper course of the Silala River basin in the territory
of Bolivia will be used to complement the chemical data collected in the Chilean sector.
These Bolivian waters included one group of springs and groundwater from wells
collected in the North Bofedal in Bolivia (Cajones ravine). The springs, which are close
to the border with Chile, are located in the foothills of the Cerro Inacaliri. The second
group corresponds to water samples from springs and piezometers located east of the
Annex XI
17
9
first group of springs, in the South Bofedal in Bolivia (Orientales), where the springs are
characterized by more diffuse discharges.
In order to facilitate the discussion of the data, the study area in Chile was divided into
the upper and lower course of the river, which correspond to the zones above and below
the Quebrada Negra (Figure 1).
The first results of the chemical characterization of the surface and groundwater of the
Silala River area in Chile were presented in Herrera and Aravena (2017). All samples
were obtained in the months of December 2016 and January-February 2017 and
correspond to the rainy season of the Altiplano. Table 1 presents all the chemical
analyses of river samples, springs and boreholes obtained in the rainy season. Table 2
shows the more recent analytical results from the Silala River, springs and boreholes in
Chile that were sampled in the dry season (October 2017).
The water in the study area is characterized by low salinity. No appreciable differences
in conductivity values were observed during the rainy and dry season (Tables 1 and 2).
The conductivity values for the Silala River range between 150 and 330 μS/cm in the
rainy season and 178 and 264 μS/cm in the dry season. The springs are characterized by
conductivity values ranging between 84 and 290 μS/cm in the rainy season and between
69 and 379 μS/cm in the dry season. The higher conductivity values of 290 and
379 μS/cm in the spring waters are observed in the Quebrada Negra spring SP-SI-10.
The waters of springs located in the upper part of the Silala River course in Chile with
EC values ranging between 149 and 220 μS/cm tend to have a relatively higher
mineralization, compared to the springs located in the northern part of the lower course
of the Silala River in Chile, which are characterized by EC values between 69 and
160 μS/cm. Furthermore, the springs in the upper part of the Silala River course in Chile
tend to have conductivity values in the range of the Silala River. These patterns were
observed in both the dry season (base flow condition) and rainy season campaigns
(Tables 1 and 2).
The groundwater collected in the wells tends to have higher salinity than the Silala
River and the springs. The conductivity values range between 309 and 440 μS/cm and
226 and 342 μS/cm, in the rainy and dry season respectively (Tables 1 and 2).
18
Annex XI
10
Table 1. Location, field parameters and chemical data for the rainy season campaign.
Sample ID
Coordinates
Date
Sampling
depth
(m.b.s.)
Water type T°C pH lab
EC field Alkalinity Cl SO4 HCO3 Ca Mg K Si Na NO3
x y (μS/cm) (mg/l of CaCO3) mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L
R-SI2-16 600242 7565357 20-12-2016 River 17.5 8.89 150 91 2,34 5,92 91,622 9,9 4,099 2,5 18,8 19,74 0,19
R-Río 1-16 599410 7564117 21-12-2016 River 14.5 8.57 163 104 4,55 7,4 93,818 9,8 4,014 2,78 21,9 18,07 0,25
R-SI-2-17 600227 7565333 31-01-2017 River 17.1 9.03 100 66 2,36 6,27 95.6 8,37 3,633 2,01 22,1 17,44 0,22
R-SI-3-17 599184 7563959 01-02-2017 River 18.3 7.33 220 22 2,31 6,48 91.6 9,29 3,664 2,44 19,8 16,56 0,23
R-SI-4-17 597908 7564081 01-02-2017 River 20.8 7.64 330 96 1,99 7,89 133 16,04 7,164 3,74 25,9 18,39 0,24
R-SI-7-17 596611 7563887 01-02-2017 River 18.4 9.02 215 119 1,92 9,33 115 14,42 6,407 3,55 25,3 17,16 0,19
SP-SI1-16 599943 7564936 20-12-2016 Spring 15.2 8.07 160 77 2,13 6,11 92,72 10,34 4,293 2,96 22 16,75 0,33
SP-SI-1-17 599956 7564952 31-01-2017 Spring 15.2 7.92 160 63 2,12 6,64 100 9,96 4,106 2,71 21,7 15,97 0,35
SP-SI-5-16 597518 7564344 21-12-2016 Spring 20.3 8.06 177 25 1,28 8,26 30,378 3,93 0,646 2,91 21,4 10,37 0,27
SP-SI-5-17 597517 7564342 01-02-2017 Spring 20.2 8.05 160 48 1,24 8,19 34 3,79 0,563 2,57 21,9 9,41 0,29
SP-SI-8-17 596886 7564854 01-02-2017 Spring 19.2 7.61 88 25 1,18 11,5 31 3,95 0,489 2,25 20,4 10,66 0,24
SP-SI-9-17 597091 7564257 01-02-2017 Spring 18.5 7.5 90.7 64 1,09 9,72 32 4,24 0,525 2,58 21,1 9,77 0,21
SP-SI-10-17 600098 7563292 01-02-2017 Spring 13.6 7.05 290 74 2,16 14,88 99 14,63 6,294 6,68 30,6 11,86 0,22
SP-SI-15-17 599926 7564847 31-01-2017 Spring 15.6 8.11 131 43 2,09 6,24 76 8,45 3,09 2,36 19,7 14,88 0,35
SP-SI-16-17 599927 7564885 31-01-2017 Spring 15.5 8.18 84 48 2,09 5,94 73 7,06 2,55 2,04 23 13,52 0,36
SP-SI-17-17 599871 7564761 31-01-2017 Spring 15.1 7.25 170 28 2,06 5,81 68 6,54 2,119 2,12 18,6 13,66 0,34
SP-SI-18-17 599765 7564582 31-01-2017 Spring 15.6 7.13 220 19 2,06 6,08 62 6,12 2,175 1,96 22,9 12,91 0,34
SP-SI-19-17 599609 7564354 31-01-2017 Spring 16.1 7 190 28 2,04 5,94 66 6,6 2,463 2,06 19,6 13,35 0,34
SP-SI-27-17 599611 7564360 31-01-2017 Spring 16.6 6.87 220 83 2,03 6,52 74 7,66 3,107 2,18 23,8 14,02 0,33
SP-SI-28-17 599825 7564812 31-01-2017 Spring 11.5 7.13 230 17 2,13 7,1 87 9,6 3,908 2,63 22 15,45 0,34
SP-SI-29-17 598290 7563892 01-02-2017 Spring 21.5 7.22 220 44 2,01 6,28 78 8,59 2,762 2,81 19,6 14,81 0,31
SP-SI-31-17 596773 7563900 02-02-2017 Spring 19.1 7 210 75 2,32 6,55 82 8,73 2,907 3,71 26,6 16,17 0,44
SPW-DQN-SI-16 599090 7563871 21-12-2016 Well 20.7 7.6 309 150 1,86 9,8 170,31 21,89 10,3 5,07 30,7 21,09 0,32
PW-BO-A-16 600185 7565278 21-12-2016 50 Well 18.9 8.15 430 5,86 9,8 206,91 24,99 13,9 5,11 29,3 26,7 0,35
PW-BO-B-16 600185 7565278 21-12-2016 75 Well 17.7 7.94 430 152 5,36 11,03 201,18 24,9 12,7 4,99 28 24,79 0,3
CW-BO-A-16 600175 7565267 21-12-2016 55 Well 16.9 8.48 - 148 7,29 13,69 181,78 21,57 11,89 4,9 29,6 26,12 0,58
CW-BO-B-16 600175 7565267 21-12-2016 110 Well 16.0 8.56 440 147 6,48 17,13 179,22 22,09 11,66 4,81 29,1 26,51 0,56
PW-UQN-A-16 599346 7564063 21-12-2016 40 Well 19.4 7.94 390 147 2,19 10,35 183,85 23,11 10,47 5,61 32,8 21,97 0,28
PW-UQN-B-16 599346 7564063 22-12-2016 75 Well 20.1 7.29 390 168 4,65 11,33 187,51 22,99 10,44 5,55 32,2 21,73 0,31
MWL-UQN-A-16 600175 7565267 22-12-2016 50 Well 20.3 7.28 390 110 5,35 11,57 181,78 22,69 10,02 5,39 32,1 21,31 0,31
PW-DQN-A-16 598839 7563780 22-12-2016 45 Well 17.40 7.40 370 3,5 17,75 128,34 16,32 7,567 4,16 25,8 21,12 0,31
PW-DQN-B-16 598839 7563780 22-12-2016 35 Well 17.70 7.65 320 102 3,39 19 129,93 16,45 7,302 4,23 27,2 20,5 0,29
MW-DQN-A-16 598841 7563769 22-12-2016 35 Well 19.5 7.52 360 137 2,58 11,73 167,14 20,93 9,243 5,22 28,5 22,06 0,29
Annex XI
19
11
Sample ID
Coordinates
Date
Sampling
depth
(m.b.s.)
Water type T°C pH lab
EC lab Alkalinity Cl SO4 HCO3 Ca Mg K Si Na NO3
x y (μS/cm) (mg/l of CaCO3) mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L
R-SI2-O17 600242 7565357 13-10-2017 - River 15,8 8,86 178 105 2,25 4,42 85,5 10,16 5.031 2.206 21,01 19,82 0,25
R-Río 1-O17 599411 7564113 12-10-2017 - River 13,1 8,4 178 169 2,05 5,14 82,3 10,80 5.110 3.074 23,31 19,43 0,26
R-SI-8- O17 599109 7563893 13-10-2017 - River 14,9 8,49 178 2,03 4,41 81,2 10,26 4.992 2.667 22,37 19,30 0,23
R-SI-9-O17 599005 7563829 13-10-2017 - River 17,8 8,02 264 1,87 7,56 128,3 18,78 9.081 3.917 29,41 20,81 0,30
SPW-DQN-SI-O17 599093 7563881 11-10-2017 63 Well 21,4 7,71 292 158 1,72 8,27 157,1 24,63 11.890 5.729 34,09 22,71 0,33
PW-BO-A-O17 600185 7565278 12-10-2017 45 Well 17 7,71 342 168 1,86 7,84 174,2 25,77 13.092 5.372 31,44 24,36 0,32
PW-BO-B-O17 600185 7565278 12-10-2017 70 Well 17,2 7,75 344 168 1,81 7,10 174,2 25,89 13.231 5.385 31,92 24,55 0,35
PW-UQN-A-O17 599346 7564063 12-10-2017 40 Well 19 7,74 335 121 1,75 8,44 150,7 24,57 11.431 5.824 35,28 22,57 0,33
PW-UQN-B-O17 599346 7564063 12-10-2017 70 Well 19,4 7,7 324 169 1,76 8,73 162,5 25,26 11.768 6.282 35,66 23,45 0,33
MWL-UQN-A-O17 599325 7564072 13-10-2017 40 Well 19,1 7,65 312 1,74 8,88 156,1 24,74 11.379 4.752 35,40 22,63 0,33
PW-DQN-A-O17 598839 7563780 13-10-2017 40 Well 17,2 7,68 226 1,97 7,30 100,5 15,02 7.432 4.048 28,48 19,68 0,32
PW-DQN-B-O17 598839 7563780 13-10-2017 30 Well 17,1 7,71 225 1,93 7,34 94,1 15,12 7.544 4.217 28,61 20,08 0,31
MW-DQN-A-O17 598841 7563769 11-10-2017 39 Well 18,7 7,8 277 133 1,79 8,30 133,6 21,23 9.973 5.103 31,97 20,73 0,32
R-SI-2-O17 600244 7565351 12-10-2017 - River 15,8 8,86 178 105 2,25 4,42 85,5 10,16 5.031 2.206 21,01 19,82 0,25
R-SI-3-O17 599184 7563959 12-10-2017 - River 12,3 8,26 169 72 2,09 5,64 80,2 10,65 5.025 2.634 22,62 18,96 0,26
R-SI-4-O17 597906 7564078 13-10-2017 - River 18,6 8,79 247 1,95 7,08 113,3 17,84 8.528 4.342 29,06 20,51 0,23
R-SI-7-O17 596623 7563895 13-10-2017 - River 17,2 8,96 253 1,74 6,90 103,7 15,87 7.507 4.259 28,22 19,59 0,14
SP-SI-1-O17 599930 7564920 12-10-2017 - Spring 15,1 7,97 149 115 2,09 4,90 80,2 10,94 5.109 2.817 23,62 16,84 0,35
SP-SI-5-O17 597510 7564339 11-10-2017 - Spring 19,8 8,51 69,6 25 1,20 5,74 28,9 4,25 2.361 2.698 22,13 9,96 0,29
SP-SI-8-O17 596886 7564858 11-10-2017 - Spring 18,3 7,84 97,5 32 1,07 8,44 26,7 4,32 1.417 1.745 22,45 11,45 0,28
SP-SI-9-O17 597089 7564260 12-10-2017 - Spring 13,9 7,5 89,2 89 1,07 6,96 29,3 4,77 2.283 2.212 22,05 10,32 0,28
SP-SI-10-O17 600095 7563296 13-10-2017 - Spring 13,7 8,29 379 1,92 13,63 90,9 16,31 7.570 7.883 34,36 13,05 0,21
SP-SI-16-O17 599934 7564889 12-10-2017 - Spring 14,4 8,13 142,4 87 1,93 5,00 73,8 9,84 4.601 2.116 22,95 16,78 0,35
SP-SI-17-O17 599874 7564763 13-10-2017 - Spring 15,7 8,3 132 2,00 4,21 55,6 7,15 3.158 2.334 20,52 15,57 0,36
SP-SI-18-O17 599762 7564581 13-10-2017 - Spring 14,6 8,13 140 1,90 4,73 57,7 7,42 3.479 2.517 21,58 15,57 0,34
SP-SI-19-O17 599603 7564355 12-10-2017 - Spring 15,3 8,24 138 82 1,90 4,81 57,7 7,52 3.496 2.222 21,44 15,83 0,39
SP-SI-27-O17 599608 7564362 12-10-2017 - Spring 15 8,7 148 105 1,94 4,87 64,1 8,60 4.030 2.556 22,53 15,60 0,33
SP-SI-28-O17 599899 7564804 13-10-2017 - Spring 14,8 8,27 138 1,92 4,79 56,7 7,33 3.145 2.440 20,82 15,50 0,32
SP-SI-29-O17 598290 7563894 13-10-2017 - Spring 18 8,24 175 2,76 5,60 72,7 9,66 3.853 4.455 22,78 16,98 0,31
SP-SI-31-O17 596769 7563906 13-10-2017 - Spring 18,5 8,01 123 123 1,87 5,71 74,8 9,74 3.958 2.106 29,42 17,77 0,30
SP-SI-32-O17 597475 7564106 13-10-2017 - Spring 18 8,95 244 1,85 7,42 106,9 14,24 6.948 3.712 24,34 17,60 0,24
Table 2. Location, field parameters and chemical data for the dry season campaign.
20
Annex XI
12
Piper diagrams were used to summarize the main contrasts in chemical composition
between the different types of water in the Chilean part of the catchment. These
diagrams are similar for the rainy and dry season, so the Piper diagram for the dry
season is used for the data discussion (Figure 6). The Piper diagram for the rainy season
is presented in Appendix E. The Piper diagram shows that all the waters have a very
similar anionic composition excepting the waters of the springs located in the lower
course of the Silala River in Chile (SP-SI-5, SP-SI-8 and SP-SI-9). The main anion is
bicarbonate with slightly more sulfate in the springs of this lower part of the Silala
River. The cationic compositions of the analyses plot more or less along a line with the
spring waters located in the northern part of the Chilean lower river course, plotting
towards the high sodium end of the line compared to the borehole waters and the
Quebrada Negra spring water, which have a higher calcium content.
The waters in the Silala River basin in Chile are all either Sodium (Na) Bicarbonate or
Calcium (Ca) Bicarbonate water type. The spatial variation of the waters’ chemical
composition can be better visualized using Stiff diagrams. The Stiff diagram consists of
a polygonal shape of three parallel horizontal axes extending on either side of a vertical
zero axis. Cations are plotted in milliequivalents on the left side of the zero axes, one to
each horizontal axis, and anions are plotted on the right side. The Stiff diagrams do not
show significant differences between the chemical composition of the waters sampled in
the dry season and those sampled in the rainy season. The Stiff diagrams for the rainy
season are presented in Appendix E and the Stiff diagrams for the dry season presented
in Figure 7 are used for the discussion of the chemical data.
The Silala River and all but one of the springs in Chile are Na-Bicarbonate type water
with relatively high content of Ca, and in general no significant differences are observed
between the springs located in the upper or lower part of the river course in Chile. The
exception is the Quebrada Negra spring SP-SI-10-O17, which besides Na and Ca, is
also characterized by a relatively high proportion of Magnesium (Mg). The
groundwaters of wells sampled in Chile, which are Ca-Bicarbonate type water, tend to
have a different chemical composition to the river and spring waters. The high Na and
Ca content is probably related to weathering of silicate minerals, which is supported by
the high silica content of these waters, which ranges between 18 and 37 mg/L (Tables 1
and 2).
The chemical data have shown that the spring system located near the river in the upper
part of the river course in Chile does not have the chemical fingerprint associated with
groundwater discharge of the deep, perhaps regional, aquifer system. This pattern
suggests that the springs are part of a subsurface flow system associated with a perched
aquifer, which drains into the river. The chemical data do not preclude the possible
Annex XI
21
13
influence of local recharge for the spring system and the river. The chemistry of the
river and springs along the river are clearly related.
A difference in chemical composition is observed in the Silala River in Chile and the
groundwater along the river course. This difference is observed below the junction
between the Quebrada Negra and the Silala River. The Stiff diagrams show an
appreciable difference between the Silala River water R-SI-9-O17 below the junction
with the River water above the junction represented by R-SI-3-O17. This pattern is also
observed between the groundwater below the junction at PW-DQN-A-O17 and PWDQN-
B-O17 and the groundwater above the junction represented by well SPW-DQNSI-
O17. The waters below the junction tend to have more Mg in comparison to Ca and
Na than the water upstream of this junction. This change in chemical composition could
be associated with input of water from the Quebrada Negra for which the spring water is
characterized by higher Mg content compared to Ca and Na than the rest of the waters
found in the Silala River basin in Chile (Figure 7).
A clear difference is observed in the bicarbonate content. In its upper part in Chile, the
Silala River is characterized by a range of values between 80 and 128 mg/L, the springs
vary between 57 and 100 mg/L and the groundwaters show much higher bicarbonate
values between 157 and 206 mg/L. The higher values of bicarbonate are due to
dissolution of carbonates and possible influence of some input of CO2 of volcanic origin
that has dissolved in the deep groundwater flow system.
Figure 8 presents the Stiff diagrams of the waters of springs, wells and the Silala River
sampled in both Chile (rainy season) and Bolivia. The waters of the springs located in
the northern part of the Silala River in Bolivia (Cajones ravine) are characterized by low
salinity ranging between 113 and 129 μS/cm (Appendix F), which is similar to the
springs located in the northern part of the Silala River in Chile (Tables 1 and 2). These
samples correspond to points SP-SI-8-17, SP-SI-18-17 and SP-SI-19-17 in Chile and to
samples SI-1A, SI-7, SI-6 and SI-1 in Bolivia. The groundwater in the Cajones ravine is
also characterized by low salinity similar to the spring waters (Appendix F). The
groundwater was collected from shallow piezometers, DS-24S (2-4 m) and DS-24P
(7.2-8.2 m).
All these samples tend to be Na-Ca bicarbonate type as shown in the Stiff diagrams.
Much more saline spring waters, ranging between 254 and 394 μS/cm, are observed in
the easternmost part of the Silala River basin, in the Orientales wetland in Bolivia
(samples SI-3 and SI-8, see Appendix F). The groundwater in the Orientales wetland
has also relatively high salinity, similar to the springs. The groundwater in the
Orientales wetland was collected from shallow piezometers, DS-4S (5-10 m), DS-8
(8.7-14.8 m). These spring waters in the Orientales ravine have much higher salinity
22
Annex XI
14
than the springs in the Chilean territories and their conductivities are in the same salinity
range as the groundwater in the Chilean area. These waters also tend to be Cabicarbonate
water type, which is similar to the groundwater sampled in Chile.
Figure 6. Piper diagram showing dry season chemical compositions of borehole, spring, and
Silala River water in Chile.
Dry season
504 + Cl
100 Ca
CATION
b. Silala River samples
PIPER DIAGRAM
100
Ca+ Mg
0 0
♦ Springs Silala River samples
Cl
ANION
• Wells samples
100
Annex XI
23
15
Figure 7. Modified Stiff diagrams of the waters from Silala River area in Chile in the dry
season.
0
MIiitary
,, ..I P ost
SCALE
Na- ' - CI
Mg~'-SO,
Ca~'-HCO,
1 meq!l meq
Sample sites
• Springs
• Wells
,. River
24
Annex XI
16
Figure 8. Modified Stiff diagrams of the waters from Silala River area in Chile (rainy season)
and Bolivia.
2.2 Environmental isotope data
This section focuses on the evaluation of environmental isotope data collected from
springs, river and wells in the study area. The stable isotopes used in this research were
18O, 2H and 13C, while the radioactive isotopes were tritium (3H) and carbon 14 (14C).
Isotopic sampling was carried out in both the dry season and the rainy season. The 18O
and 2H provide information about the origin of groundwater, and therefore are used for
evaluation of recharge areas, and 3H and 14C provide information about groundwater
residence time. Carbon 13 (13C) provides information about geochemical reactions that
can affect the dissolved inorganic carbon (DIC) through the groundwater flow system
(Clark and Fritz, 1997). These tracers have been extensively used in groundwater
studies in Northern Chile (Magaritz et al., 1989; Aravena and Suzuki, 1990; Herrera et
al., 2006; Uribe et al., 2015).
SCALE
0
Mg Cl
Ca SO, --=---....--- 3 meq 3 meq HCO,
Na
Sample sites
• Springs
• Wells
,. River
Annex XI
25
17
2.2.1 δ18O and δ2H data
The isotope data for the river, springs and groundwater from wells collected during the
rainy season and dry season campaigns in Chile are reported in Tables 3 and 4,
respectively. One key aspect that needs to be defined to allow the interpretation of the
isotope data, using the typical diagram of δ 2H vs δ18O, is the local meteoric water line,
which reflects the isotopic composition of the precipitation in the study area. A
description of the preparation of the local meteoric water line is described below.
The isotopic characterization of precipitation has been made using data from the city of
La Paz for the period 1995-2009 (International Atomic Energy Agency (IAEA)) and
from precipitation data corresponding to different locations in northern Chile. Most of
the northern Chile data were obtained from Aravena et al. (1999), which relate to
locations higher than 4000 m.a.s.l. Precipitation data from the city of La Paz have been
used because of the continuous monitoring of the precipitation isotopic composition
(IAEA/World Meteorological Organization (WMO)) and the large amount of
information available for the different months of the year. All samples show a good
correlation between δ18O and δ2H at all sampling points, regardless of the proximity to
the study area. Having discarded the rain samples that were suspected of being affected
by evaporation, a local meteoric line has been calculated by linear interpolation using
least squares which has the following expression: δ2H = 7.9δ18O + 14. A special
characteristic of the precipitation in Northern Chile is the existence of an isotopic
gradient with altitude where the high-altitude rainfall tends to be isotopically more
depleted than rainfall at lower altitude (Fritz et al., 1981; Chaffaut, 1998; Aravena et al.,
1999; Uribe et al., 2015). This explains the rationale behind the use of environmental
isotopes in water resource studies in the Northern Chile, Bolivian and Peruvian
Altiplano regions.
Figure 9 and Figure 10 show these data compared with the global meteoric water line
(δ2H = 8δ18O + 10) and the local meteoric water line (δ2H = 7,9δ18O + 14). A clear
pattern is observed in these data. The springs located in the upper course of the river in
Chile have a different isotope fingerprint to the springs located in the northern part of
the lower course of the river (Figure 9 and Figure 10). The lower course springs plot
near the local meteoric water line with higher deuterium excess values (around 15‰)
while the upper springs in Chile are located below the local meteoric water line. Based
on the isotope data, the springs in the northern part of the lower course of the river in
Chile should represent local recharge. Furthermore, the data showed that some springs
located in the southern part of the lower river course in Chile showed a similar isotopic
fingerprint to the upper river course springs. This pattern suggests that these springs are
part of the same hydrogeological system that generates the springs in the upper course
of the river in Chile and/or part of a subsurface flow system fed by groundwater
26
Annex XI
18
discharge associated with the Quebrada Negra valley, represented by the spring SP-SI-
10-17, which has an isotopic composition in the range of the upper river course springs.
Concerning the river waters, they have a similar isotopic fingerprint to the upper springs
in Chile and the lower springs located in the southern part of the river (Tables 4 and 5),
therefore they plot in the same group. This is observed in the data collected in both the
rainy and dry season. The isotope data indicate that both types of water have a similar
origin. The isotopic data for the groundwater in both seasons also plotted as part of the
river and upper springs group, which suggests that all these waters are associated with
recharge areas at similar altitudes. However, the deep groundwater in the dry season
tends to separate from the group with isotope values slightly more depleted than the
river and the springs. This can imply that the regional aquifer is recharged at higher
altitude than the river and springs in Chile. The isotope composition of these waters is
all plotted below the local meteoric water line, which is a typical feature for
groundwater and springs in Northern Chile (Fritz et al., 1981; Magaritz et al., 1989;
Uribe et al., 2015). This pattern has been associated with evaporation during the waters’
residence time in the unsaturated zone (Magaritz et al., 1989). Therefore, assuming a
slope of 3 for the evaporation line in soil (Clark and Fritz, 1997) and extrapolating the
data using this slope, the evaporation line would intersect the local meteoric water line
around -14,5‰ of δ18O, which is within the range of isotope values measured for
precipitation above 3500 m.a.s.l (Aravena et al., 1999; Uribe et al., 2015).
The isotope data indicate that the river, the upper springs in Chile and the groundwater
are part of a regional flow system mainly recharged in the high Andes of Bolivia, which
is supported by the location of the river headwaters. However, some springs identified
in the Chilean side of the Silala River basin may correspond to more local flow systems.
Based on the isotope and chemical data, it is clear that the river and upper spring waters
in Chile could be closely related. It seems likely that the origins are from recharge to a
perched series of aquifers overlying the Silala Ignimbrite and possibly the Cabana
Ignimbrite and the widespread andesitic lava flow (SERNAGEOMIN, 2017) that forms
the eastern edge of the Orientales wetland. The water stored in these subsurface perched
units moves through alluvial deposits (Arcadis, 2017; SERNAGEOMIN, 2017) or
horizontal fractures in the near surface levels of the ignimbrites. The water level data
obtained in the new wells drilled in the deeper aquifer, as part of the hydrogeological
investigation (Arcadis, 2017), which showed the water level in the Ignimbrite aquifer is
lower than the river water level, tend to support this hypothesis.
Annex XI
27
19
Sample ID Water type δ18O VSMOW
(‰)
δ2H VSMOW
(‰)
R-SI-02-16 River -11.47 -91.7
R-Río 1-16 River -11.50 -91.3
R-SI-2-17 River -11.61 -92.5
R-SI-3-17 River -11.64 -91.8
SP-SI-01-16 Spring -11.67 -91.6
SP-SI-21-16 Spring -10.92 -82.1
SP-SI-5-16 Spring -11.54 -82.7
SP-SI-1-17 Spring -11.84 -92.6
SP-SI-5-17 Spring -11.72 -82.9
SP-SI-8-17 Spring -12.04 -83.7
SP-SI-9-17 Spring -12.01 -84.0
SP-SI-10-17 Spring -11.72 -89.4
SP-SI-15-17 Spring -11.83 -92.4
SP-SI-16-17 Spring -11.82 -92.3
SP-SI-17-17 Spring -11.77 -91.9
SP-SI-18-17 Spring -11.77 -91.8
SP-SI-19-17 Spring -11.79 -91.5
SP-SI-27-17 Spring -11.80 -91.8
SP-SI-28-17 Spring -11.78 -92.3
SP-SI-29-17 Spring -11.73 -91.4
SP-SI-31-17 Spring -11.72 -90.2
SPW-DQN-SI-16 Well -11.95 -93.2
PW-BO-A-16 Well -11.97 -93.9
PW-BO-B-16 Well -11.91 -92.2
CW-BO-A-16 Well -11.89 -93.5
CW-BO-B-16 Well -11.87 -93.5
PW-UQN-A-16 Well -11.95 -92.9
PW-UQN-B-16 Well -11.97 -93.2
MWL-UQN-A-16 Well -11.9 -92.6
PW-DQN-A-16 Well -11.73 -91.7
PW-DQN-B-16 Well -11.77 -92.0
MWL-DQN-A-16 Well -11.85 -92.5
Table 3. Stable isotope results of the rainy season samples.
28
Annex XI
20
Sample ID Water type δ18O VSMOW
(‰)
δ2H VSMOW
(‰)
R-SI-2-O17 River -12.15 -93.6
R-RIO-1-O17 River -12.09 -92.9
R-SI-3-O17 River -12.09 -92.8
R-SI-8-O17 River -12.05 -92.9
R-SI-9-O17 River -12.32 -93.1
R-SI-4-O17 River -12.26 -93.1
R-SI-7-O17 River -11.98 -90.0
SP-SI-10-O17 Spring -12.21 -90.8
SP-SI-28-O17 Spring -12.20 -92.8
SP-SI-16-O17 Spring -12.22 -93.0
SP-SI-17-O17 Spring -12.20 -92.4
SP-SI-18-O17 Spring -12.18 -92.8
SP-SI-19-O17 Spring -12.10 -91.4
SP-SI-27-O17 Spring -12.23 -92.7
SP-SI-1-O17 Spring -12.25 -93.1
SP-SI-32-O17 Spring -12.19 -92.4
SP-SI-5-O17 Spring -12.03 -84.3
SP-SI-8-O17 Spring -12.41 -84.0
SP-SI-9-O17 Spring -12.40 -84.1
SP-SI-31-O17 Spring -12.13 -91.8
SP-SI-29-O17 Spring -12.08 -92.0
SPW-DQN-SI-O17 Well -12.54 -94.6
PW-BO-B-O17 Well -12.53 -95.1
MWL-UQN-A-O17 Well -12.48 -94.6
PW-UQN-A-O17 Well -12.51 -94.6
PW-UQN-B-O17 Well -12.55 -94.9
MW-DQN-A-O17 Well -12.44 -93.9
PW-DQN-A-O17 Well -12.30 -93.2
PW-DQN-B-O17 Well -12.30 -93.3
PW-BO-A-O17 Well -12.52 -95.0
Table 4. Stable isotope results of the dry season samples.
Annex XI
29
21
Figure 9. Plot of δ18O and δ2H for river, spring water and wells water in the rainy season.
Figure 10. Plot of δ18O and δ2H for river, spring water and wells water in the dry season.
6180 {%.) SMOW
-13 -12 -11
l L l L i i l ,,,,""/ ,,,,
///,/
/'
,,,,,,,,""
,,,,
,,,,, ,,,"
,,,,"
~",,"
,,,,
\, ,,,,
,//,/
,,,,,,,,""
/
1
_
2
PW-DQN-8
-Sl-1
-A
-8
-A
-DQN-SI Legend
t:. Silala River rainy season
♦ Springs Silala River rainy season • Wells in Silala River rainy season
61"0 (o/oo) SMOW
-13 -12.8 -12.6 -12.4 -12.2 -12 .11y· -11.6 -11 .4
,,,,,/'
,,,, ,,,
SP-Sl-8_- ,,. -' ♦SP -Sl -5
/ SP-S1-9
~ \, ,,,,"
\, ,,-'
,,,,,,,,,,,/
· N- PW-80-A
PW-80-8
·1
1-28
Legend
t:. Silala River dry season
♦ Springs Silala River dry season
• Wells in Silala River dry season
-10
-70
b -72 r -74
-76
-78
-80 r -82 ;: l 0
-84 ::.
U)
-86 t
:i::
-88 :;;,
r -90
-92
-94
-96 r- -98
-100
-11
-80
-82
-84
-86
r
-88 ;:
0 ::.
-90 U) t
-92
:i:: ::,
-94
~ -96
-98
-100
30
Annex XI
22
2.2.2 Tritium data
The interpretation of tritium data in groundwater requires a reconstruction of the tritium
content of the precipitation during the last seven decades. One of the difficulties in
reconstructing the tritium input function in the study area is the lack of continuous
monitoring of tritium activity in rainwater from 1954 to the present. In South America,
there is no observation station with a continuous series of data. The most complete data
are from Porto Alegre and Rio de Janeiro, which are part of the IAEA monitoring
network. There are four observation stations at a latitude relatively close to the Silala
area. These are Cuzco (3246 m.a.s.l.) in Peru, La Paz (4071 m.a.s.l.) in Bolivia, and Los
Molinos (1300 m.a.s.l.) and Salta (1187 m.a.s.l.) in Argentina (Herrera et al., 2006)
(Figure 11). To reproduce the tritium input function, it is necessary to know its
concentrations in rainwater since 1953, when thermonuclear tests were initiated in the
atmosphere. The period between 1954 and 1968 of the series was completed with
tritium data from Porto Alegre and Rio de Janeiro, Brazil. The tritium input function for
the southern Hemisphere is presented in Figure 11. Based on this figure the tritium data
for recent precipitation in the study area should be between 3 and 5 TU.
Figure 11. Concentrations of monthly rainwater tritium measured at IAEA stations in the
Southern Hemisphere in South America (Herrera et al., 2006).
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
0
10
20
30
40
50
60
70
80
90
100
Porto Alegre
Cuzco
Salta
Los Molinos
La Paz
Leyenda
TRITIO (UT)
I I I
Annex XI
31
23
The tritium data for both rainy and dry seasons are presented in Tables 5 and 6. These
data showed that the springs, river water and well waters in Chile basically do not
contain tritium, indicating that these waters were recharged before the 1960s. This
conclusion is supported by tritium data collected in three springs in Bolivia, which
showed nil values of tritium in the Silala River basin in the Bolivian territory
(Appendix G).
Sample ID Collection Date TU Water type ± 1σ
PW-BO-B-16 21-12-2016 <0.05 Well 0.23
PW-UQN-B-16 22-12-2016 0.07 Well 0.23
PW-DQN-B-16 22-12-2016 0.22 Well 0.23
R-SI-2-16 20-12-2016 0.16 River 0.23
SP-SI-21-16 21-12-2016 0.18 Spring 0.22
SP-SI-5-16 21-12-2016 < 0.05 Spring 0.19
SP-SI-8-17 01-02-2017 <0.05 Spring 0.2
SP-SI-15-17 31-01-2017 0.31 Spring 0.29
SP-SI-10-17 01-02-2017 <0.05 Spring 0.11
R-SI.7-17 01-02-2017 <0.05 River 0.31
Table 5. Tritium data obtained in rainy season.
Sample ID Collection Date TU Water type ± 1σ
R-SI-2-O17 12-10-2017 < 0.8 River 0.7
R-SI-3-O17 12-10-2017 < 0.8 River 0.8
R-SI-7-O17 13-10-2017 < 0.8 River 0.8
R-SI-8-O17 13-10-2017 < 0.8 River 0.8
R-SI-9-O17 14-10-2017 < 0.8 River 0.8
SP-SI-8-O17 13-10-2017 < 0.8 Spring 0.8
SP-SI-10-O17 14-10-2017 < 0.8 Spring 0.7
SP-SI-18-O17 13-10-2017 < 0.8 Spring 0.7
SP-SI-31-O17 13-10-2017 < 0.8 Spring 0.8
SP-SI-32-O17 14-10-2017 < 0.8 Spring 0.6
SPW-DQN-SI-O17 11-10-2017 < 0.8 Well 0.7
Table 6. Tritium data obtained in dry season.
32
Annex XI
24
2.2.3 Carbon-14 and Carbon-13 data
By convention, the radiocarbon dating technique assumes that the 14C content of the
atmospheric carbon dioxide (CO2) was 100 percent modern carbon (pMC) at and before
1950 (before atmospheric nuclear testing) and was constant in the past. For example, if
a sample of wood has a 14C content of 50 pMC, which corresponds to half of the initial
14C of the atmospheric CO2, then based on the known 14C half-life of 5730 years, it can
be estimated that the wood sample has a radiocarbon age of 5730 years before 1950. In
the case of groundwater, the 14C gets into the groundwater during dissolution of soil
CO2 during recharge events. The CO2 from the soil has a 14C content of 100 pMC but
during groundwater flow in the aquifer, the 14C content can be affected by the input of
old carbon, for example from dissolution of carbonate, from old organic carbon
involved in redox processes such as sulfate reduction, or input of volcanic CO2 in
volcanic areas (Clark and Fritz, 1997).
The 13C data provide information about processes and input of old carbon to the
dissolved inorganic carbon along the groundwater flow system. δ13C values for CO2 soil
in the recharge areas of arid environments can be around -18‰ (Fritz et al., 1981).
In the Chilean part of the Silala basin, the δ13C values for groundwater during the rainy
season range between -7.3 and -8.0‰, the river waters vary between -8.0 and -9.1‰
and the springs range between -5.8 and -7‰. During the dry season, the groundwater is
characterized by δ13C values between -6.8 and -7.4‰ and the river showed values
between -5.9 and -7.9‰ and the springs range between -5.9 and -9.3‰.
The δ13C enrichment pattern observed in the dissolved inorganic carbon compared to
the expected δ13C value of -18‰ for CO2 in the recharge area should be associated with
dissolution of carbonate minerals during groundwater flow in the aquifer. The other
process that could control the 13C content in surface water is isotopic exchange between
dissolved CO2 and atmospheric CO2. However, because of the relatively high slope of
the Silala River implying fast flow, this process should not be significant. Carbonate
minerals tend to have δ13C values close to 0‰ (Clark and Fritz, 1997). This also should
be reflected in the 14C content, which will be influenced by the input of old carbon from
dissolution of carbonate minerals and radioactive decay during groundwater flow in the
aquifer. The other factor that could affect the 14C in the study area is some contributions
from volcanic CO2, which has been documented previously in the Loa River basin
(Aravena and Suzuki, 1990). This potential contribution will decrease the 14C of the
dissolved inorganic carbon in the groundwater since volcanic CO2 is devoid of 14C.
Typically δ13C values for volcanic CO2 range between -3 and -7‰ (Gerlach and
Thomas, 1986; Chivas et al., 1987).
Annex XI
33
25
Because of these complications, for this study, the 14C data will not be used to estimate
water residence time and it will only be used as a tracer to evaluate the rivergroundwater
interactions and river-springs interactions. The 14C data from the Silala
River area in rainy and dry seasons are reported in Tables 7 and 8, respectively.
The 14C content of the river at the sampling site in Chile near the border (R-SI-2-16,
Figure 12) in the rainy season has a 14C value of 26.66 pMC. Downstream, the 14C
content of the Silala River before reaching the Quebrada Negra increases to 45.97 pMC
(R-SI-3-17, Figure 12). A similar pattern is observed during the dry season. The
sampling site in Chile near the border (R-SI-2-O17) showed a value of 31.25 pMC,
increasing to a value of 39.15 pMC (R-SI-3-O17) before the junction with the Quebrada
Negra (Figure 13). The increase in 14C as the water flows from the upper course to the
middle course of the Silala River in Chile is attributed to an increase of the lateral
shallow groundwater contributions that have been recharged in the same area of the
Silala River. Further down-gradient near the junction with the Quebrada Negra, the 14C
content of the river was found to be 39.55 pMC at R-SI-8-O17 and 18.1 pMC at R-SI-
09-O17 (Figure 13). Further downstream the river shows an increase to a value of 32.53
pMC in the sampling point (R-SI-7-O17, Figure 13). The large decrease of 14C content
in the river after the junction is caused by a contribution from groundwater discharge
from the artesian well SPW-DQN-SI-O17, which is characterized by a 14C content of
8.36 pMC (Figure 13). The increase of 14C content in the last part of the river course
downstream is due to lateral contribution from the northern and southern part of the
basin. There is no information on C-14 values from river samples in the Bolivian study.
The 14C content of the springs located in the upper part of the river course in Chile have
values of 32.41 pMC (SP-SI-15-17, Figure 12) and 39.75 pMC (SP-SI-18-O17, Figure
13) during the rainy and dry season, respectively. These values are within the range of
14C content of the river during the rainy and dry season in this part of the basin. A range
of values between 23.96 and 34.49 pMC is observed in the springs (SP-SI-29-O17, SPSI-
32-O17 and SP-SI-31-O17, Figure 13) located in the southern lower course of the
river in Chile. Much higher 14C values are observed in the springs located in the
northern lower part of the river course (SP-SI-5 and SP-SI-8) in the rainy and dry
season with respect to the waters of the springs located close to the main course of the
Silala River (Table 7 and Table 8). These springs showed values between 67.44 and
78.39 pMC during the rainy and dry seasons (Figure 12 and Figure 13). A high 14C
value of 86.29 pMC was also reported in a spring located in the northern part in the
Bolivian sector associated with discharge in the foothills of the Cerro Inacaliri
(Appendix G). Lower 14C values of 25.67 and 30.67 pMC similar to the springs in the
Chilean sector are observed in the springs located in the Orientales wetland in Bolivia
(Figure 13). These springs have higher salinity than the northern (Cajones) wetland
34
Annex XI
26
springs, but similar to the groundwater from boreholes in Chile. This suggests that the
springs are associated with groundwater discharge of a regional groundwater flow
system. The spring located in the Quebrada Negra (SP-SI-10), which may represent
discharge of a regional flow system, perhaps recharged at higher altitude in Bolivia, has
a 14C value of 30.06 pMC and 27.57 pMC during the rainy and dry seasons, respectively
(Table 7 and Table 8).
The deep groundwater in Chile is characterized by much lower 14C values than the
springs and the Silala River and showed values of 9.93 (PW-BO-B-16) and 14.54 pMC
(PW-UQN-B-16) in the rainy season, and 8.36 (SPW-DQN-SI-O17), 9.15 (PW-BO-BO17),
9.96 (PW-UQN-B-O17), 21.82 (PW-DQN-A-O17) and 22.06 (PW-DQN-B-O17)
pMC in the dry season (Figure 12 and Figure 13). The lowest 14C value of 8.36 pMC in
the groundwater is observed in the artesian well SPW-DQN-SI-O17, which is flowing
under confined conditions.
The 14C data show an increase in 14C content along the groundwater flow system
comparing data above and below the junction with the Quebrada Negra. The
groundwater increases from 14.54 pMC (PW-UQN-B-16, Figure 12) above the junction
to values of 22 pMC below the junction (PW-DQN-A-O17 and PW-DQN-B-O17,
Figure 13). This pattern could be associated with a contribution from the Quebrada
Negra water, which is characterized by a 14C content of around 29 pMC. Reinterpretation
of drill cuttings in borehole MW-DQN (only 15 metres from PW-DQN)
has shown that the borehole penetrates only 3 metres of Fluvial deposits and below this
8 metres of Silala ignimbrite before entering Pliocene lavas (SERNAGEOMIN, 2017).
Downstream of this point the Silala River flows over bedrock (Silala Ignimbrite) and no
fluvial deposits are present. These geological changes may allow that groundwater flow
originating from the Quebrada Negra is forced to enter the river along this reach.
The higher salinity and lower 14C of the sampled groundwater compared to the river and
springs water indicates that the groundwater is part of a regional groundwater flow
system, which is not connected to the river and spring system in Chile. This tends to
support the hydrogeological conceptual model developed by Arcadis (2017), which
postulated the existence of a confined aquifer in the Silala River area in Chile.
Based on the 14C data, as part of the conclusions in the DHI (2018) report, it is
suggested a “relatively old age in the southern wetland (up to ~ 11,000 years old) and
a significant younger age for the northern wetlands (up to ~ 1,000 years)” (BCM,
Vol. 4, p. 103). These estimates are not correct since they do not take into account the
dilution effect due to dissolution of carbonates along the groundwater flow system and
the potential input of volcanic CO2, as was explained above.
Annex XI
35
27
ID sample Water Type
δ 13C (PDB) 14C
DIC pMC ± 1σ
R-SI-2-16 River -8 26.66 0.13
SP-SI-5-16 Spring -7 76.86 0.35
PW-BO-B-16 Well -7.3 9.93 0.08
PW-UQN-B-16 Well -8 14.54 0.09
R-SI-3-17 River -9.1 45.97 0.27
SP-SI-8-17 Spring -6.8 78.39 0.24
SP-SI-15-17 Spring -5.8 32.41 0.15
SP-SI-10-17 Spring -6.7 30.06 0.15
Table 7. 14C data for river, springs and wells obtained during the rainy season.
ID sample Water Type
δ 13C (PDB) 14C
DIC pMC ± 1σ
R-SI-2-O17 River -7.3 31.25 0.20
R-SI-3-O17 River -7.9 39.15 0.31
R-SI-7-O17 River -5.9 32.53 0.38
R-SI-8-O17 River -7.9 39.55 0.21
R-SI-9-O17 River -7.0 18.08 0.20
SP-SI-5-O17 Spring -6.8 70.66 0.41
SP-SI-8-O17 Spring -9.3 67.44 0.31
SP-SI-10-O17 Spring -7.9 27.57 0.18
SP-SI-18-O17 Spring -6.8 39.75 0.44
SP-SI-29-O17 Spring -8.7 34.49 0.49
SP-SI-31-O17 Spring -7.7 29.75 0.34
SP-SI-32-O17 Spring -5.9 23.96 0.20
SPW-DQN-SI-O17 Well -6.8 8.36 0.11
PW-DQN-A-O17 Well -7.4 21.82 0.14
PW-DQN-B-O17 Well -7.4 22.06 0.15
PW-BO-B-O17 Well -6.4 9.15 0.11
PW-UQN-B-O17 Well -7.3 9.96 0.18
Table 8. 14C data for river, springs and wells obtained during the dry season.
36
Annex XI
28
Figure 12. Distribution of 14C sampling points in the Silala River basin in Chile (for the rainy
season). This figure is complemented by Table 7, which contains the sample point values.
sl 1
Meters
MercatCJProjcctioo, WC.SM
SP-5I-5-16
(76.86) ♦
R-SI-3-17
(45.97)A
~ -
FCABln
PW-80-8-16
(9.93)
.{P-51-
Annex XI
37
29
Figure 13. Distribution of 14C sampling points in the Silala River basin in Chile (for the dry
season) and Bolivia (Appendix G). This figure is complemented by Table 8, which contains the
sample point values for Chilean analyses.
,oliri
'",. SP-S1-8-017 l (67.44)
~ SP-Sl·S-017
_g, SP-S1-32-017 • (70.66) PW-UQN-B-017
0 (23 96) (9.96)
Caj
Hilo
S/N-LXXIII
FCAB Intake
CODELCO . SPW-OQN-S1-017 \
Intake SP S''ll 0..,1/'""' (8.36) _ ,_ R-S1-3-017
\ ♦ • V • H ♦ ~ (39.15)
-----t29'.75') SP-S1-29-017 ~- i \~~R-S1-8-017
R-S1-7-017 (34.49) 10 Si/a/a _,... Q. (39.55)
Site6
(86.29).
Ina. , (3253) PW-DQN·A-017 (21.82) ""b,-Qct_o Ne ra
Police Station PW-DQN-8-017 (22 06) R-S1-9-017 i SP:-Sl·lO·Ol7
(18.1) -.{(27. 57)
Sample sites
• Springs
• Wells
" River
(14C pMC)
· 1
I'·
I
Slte4
(30.67) •
HitoS/N
38
Annex XI
30
3. CONCLUSIONS
The water of the Silala River is primarily related to spring discharge located in Bolivian
territory. The waters enter Chilean territory through the course of the Silala River and
through underground flows.
The chemical data show that the river, springs and groundwater of wells are
characterized by low salinity. The springs in the upper part of the river course in Chile
tend to be more saline than the springs located in the northern side of the lower river
course in Chile. The river has similar salinity to the upper springs in Chile, and the
groundwater from all wells has a higher salinity than the river and springs. In general,
the water is Na-bicarbonate type with differing degrees of Ca content. The groundwater
of wells is Ca-Na-bicarbonate type. The high silicate content of these waters indicates
that the main source of the chemical composition of the water is weathering of silicate
minerals. The chemical data suggest that the springs in the upper part of the river course
in Chile are not a reflection of groundwater discharge from the deeper aquifer,
indicating that the springs probably emerge from a subsurface flow associated with a
perched aquifer.
Springs and groundwater (collected from shallow piezometers) in the Cajones wetland
area in the Bolivian sector are characterized by salinity values and a chemical
composition similar to the waters of springs located in the northern part of the Silala
River in Chile (SP-SI-8, SP-SI-9 and SP-SI-5). Both spring systems seem to be
associated to local recharge occurring in the Cerro Inacaliri. Higher salinity than the
Cajones waters are observed in springs and groundwater in the Orientales wetland area,
which are likely to be associated with discharge from a regional aquifer system. Their
salinity and chemical composition are characteristic of the groundwater in the Chilean
sector.
The isotopic composition of δ18O and δ2H show that the springs located in the northern
part of the lower river course in Chile have a different isotopic fingerprint to the springs
located in the upper course of the river in Chile, which indicates a different origin. The
river water has a similar isotopic pattern to the upper springs in Chile indicating they are
likely to have a similar origin. Furthermore, the isotope data show the springs located in
the lower southern part of the river in Chile might be similar in origin to the Chilean
springs located in the upper river course. This could mean that they are part of the same
hydrogeological system and/or part of the subsurface flow system fed by a regional
groundwater flow system also associated with the spring discharge in the upper
Quebrada Negra. No δ18O and δ2H data were reported for the waters in the Bolivian
sector, which could be used for comparison with the results obtained in Chile.
Annex XI
39
31
The sampled groundwaters in wells tend to have a similar or slightly more depleted
isotope composition than the upper springs and the river in Chile. This is interpreted as
indicating that these waters were recharged from precipitation falling at a similar
altitude and/or from a relatively higher altitude. Based on the chemical and isotope data,
visual observation in the field and water level data in the wells compared to the river,
this information tends to confirm the hypothesis that the upper springs in Chile are
discharging features of a perched aquifer and that the deep water characterized in the
wells in Chile would correspond to a confined or semi confined aquifer in the volcanic
deposits of regional extent.
The tritium data in upper and lower springs, groundwater and river water show that the
tritium concentration is practically nil indicating these waters are not likely to be very
recent.
Concerning the 14C data, a wide range in values is observed. The springs representing
the lower northern course of the Silala River in Chile, which based on the stable isotope
data appear to represent local recharge, showed the highest 14C values ranging between
67.44 and 78.39 pMC. A similar 14C pattern is observed in springs discharging at the
foothill of the Cerro Inacaliri in the Cajones area located in the northern part in the
Bolivian sector. Both springs systems seem to be associated with recharge in the Cerro
Inacaliri area.
The river values in Chile increase from 26.66 and 31.25 pMC in the first sampling
location near the border to values of 45.97 and 39.15 pMC before the junction with the
Quebrada Negra during the rainy and dry seasons, respectively, indicating some
contribution of recent shallow groundwater into the river, related to precipitation events
during the rainy season. The river also receives a contribution from groundwater
discharge from an artesian well and lateral contributions from downstream northern and
southern areas in the lower part of the river course.
The Carbon-14 data of 32.4 and 39.7 pMC obtained for the upper springs in Chile,
which is within the range of 14C values of the river, support the conceptual model
postulated above based on the isotope, chemical and hydrogeological data. This model
includes an interaction between a perched aquifer, probably in alluvial deposits on the
flanks of the high mountains, and the river as result of a complex system of fractures
present in the near surface levels of Silala Ignimbrite. These waters are likely to be part
of a flow system recharged in the high Andes of Bolivia and the flanks of the Volcán
Apagado and Cerro Inacaliri in Chile.
In Chile, much lower 14C content is observed in the deep groundwater than the river and
springs water. This groundwater is characterized by values of 8.4 and 14.54 pMC in
water collected in the wells located in the upper course of the Silala River in Chile. The
40
Annex XI
32
14C content in the groundwater increases to values around 22 pMC in the lower course
of the Silala River, which could be related to a contribution of water from the Quebrada
Negra basin, which is characterized by 14C values around 29 pMC. Low 14C values in
the range of values of the groundwater in the Chilean sector are observed in the springs
and groundwater in the Orientales area in the Bolivian sector, associated with a regional
groundwater flow system.
The lower 14C content of the deep groundwater, beside longer residence time, could
reflect input of old carbon from dissolution of carbonates and possible influence of
volcanic CO2 and the latter could partly explain the higher concentration of bicarbonates
of the groundwater compared to river and springs waters.
Summarizing, the similarity between the chemical and isotopic composition of the
waters of the Silala River and the waters of the Chilean springs indicates that there is a
close relationship between the shallow aquifer and the Silala River, so it is likely that a
significant contribution to the flow in the river comes from the shallow perched aquifer.
The waters of the shallow aquifer would circulate through the alluvial deposits and the
Silala Ignimbrite (Arcadis, 2017). However, the waters of the deep aquifer show
chemical and isotopic differences to the waters of the shallow aquifer and the Silala
River, and contribute to the flow from the Orientales springs. It seems likely that these
waters are mixtures of deep groundwater and shallow perched groundwater. Differences
in chemical and isotopic composition in the deep confined aquifer system, found in
boreholes in Chile indicate that there is no current hydraulic connection between these
two systems in Chile. This agrees with the observations made by Arcadis (2017) that
assign a confined character to the waters of the deep aquifer.
Annex XI
41
33
4. REFERENCES
Aravena, R. and Suzuki, O., 1990. Isotopic evolution of rivers in Northern Chile. Water
Resources Research, 26 (12), 2887-2895.
Aravena, R., Suzuki, O., Peña, H., Pollastri, A., Fuenzalida, H. and Grilli, A., 1999.
Isotopic composition and origin of the precipitation in Northern Chile. Applied
Geochemistry, 14 (4), 411-422.
Arcadis, 2017. Detailed Hydrogeological Study of the Silala River. (Chile’s Memorial,
Vol. 4, Annex II).
Chaffaut, I., 1998. Precipitations d'Altitude, Eau Souterraines et Changements
Climatiques de L'Altiplano Nord-Chile. Universite de Paris Sud U.F.R. Scientifique
D'Orsay. Paris, France.
Chivas, A.R., Barnes, I., Evans, W.C., Lupton, J.E. and Stone, J.O., 1987. Liquid
carbon dioxide of magmatic origin and its role in volcanic eruptions. Nature, 326, 587-
589.
Clark, I.D. and Fritz, P., 1997. Environmental Isotopes in Hydrogeology. Lewis
Publishers, Boca Raton, Florida, pp. 342.
Custodio, E. and Llamas, M.R., 1983. Hidrología subterránea. Omega. Barcelona.
Danish Hydraulic Institute (DHI), 2018. Study of the flows in the Silala Wetlands and
Springs System (Bolivia’s Counter-Memorial, Volume 4, Annex 17).
Fritz, P., Suzuki. O., Silva. C. and Salati. E., 1981. Isotope hydrology of groundwaters
in the Pampa del Tamarugal, Chile. Journal of Hydrology, 53, 161-184.
Gerlach, T.M. and Thomas, D.M., 1986. Carbon and sulphur isotopic composition of
Kilauea parental magma. Nature, 319, 480-483.
Herrera, C. and Aravena, R., 2017. Chemical and Isotopic Characterization of Surface
Water and Groundwater of the Silala River Transboundary Basin, Second Region,
Chile. (Chile’s Memorial, Vol. 4, Annex III).
Herrera, C., Pueyo, J., Sáez, A. and Valero-Garcés, B., 2006. Relación de aguas
superficiales y subterráneas en el área del lago Chungará y lagunas de Cotacotani, norte
de Chile: Un estudio isotópico. Revista Geológica de Chile, 33 (2), 299-325.
IAEA/WMO, 2015. Global Network of Isotopes in Precipitation (GNIP). Available at:
https://www.iaea.org/services/networks/gnip.
Latorre, C. and Frugone, M., 2017. Holocene Sedimentary History of the Río Silala
(Antofagasta Region, Chile). (Chile’s Memorial, Vol. 5, Annex IV).
42
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Magaritz, M., Aravena, R., Pena, H., Suzuki, O. and Grilli, A., 1989. Water chemistry
and isotope study of streams and springs in northern Chile. Journal of Hydrology, 108,
323-341.
SERNAGEOMIN (National Geology and Mining Service), 2017. Geology of the Silala
River Basin. (Chile’s Memorial, Vol. 5, Annex VIII).
Uribe, J., Muñoz, J.F., Gironás, J., Oyarzún, R., Aguirre, E. and Aravena, R., 2015.
Assessing groundwater recharge in an Andean closed basin using isotopic
characterization and a rainfall-runoff model: Salar del Huasco basin, Chile.
Hydrogeology Journal, 23, 1535-1551.
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35
APPENDIX A
Materials used in the sampling events included:
• Notebook and pencil.
• Containers for sampling.
• Ice Packs.
• Transparent adhesive tape.
• Scissors or carton.
• Container or bottle for measurements of physical and chemical parameters in situ.
• Equipment for in situ measurements (pH meter, conductivity meter, thermometer).
• Replacement batteries.
• Measuring tape.
• Photographic camera.
• Bailer for manual sampling with rope (optional).
• Submersible pump, controller and generator in case the sampling is carried out
through the well drain.
• Latex gloves.
• Distilled water for the washing of the multiparameter probes.
The containers used for each sampling point is listed below as a reference.
• 1 plastic container of 1000 mL without additives, labeled for analysis of General
Parameters.
• 1 plastic container of 500 - 1000 mL with additive included (H2SO4) inside, labeled
for nutrient analysis.
• 1 plastic container of 500 mL with additive included (NaOH) inside, labeled for
cyanide analysis.
• 1 500 mL plastic container with additive included (HNO3) inside, labeled for total
metal analysis.
• 1 plastic container of 250 - 500 mL without additives, labeled for total suspended
solids (SST) analysis.
• 1 plastic container of 250 mL without additives, labeled for analysis of dissolved
metals.
• 1 plastic container with double lid of 100 - 250 mL, without additives, labeled for
isotopic analysis of deuterium (δ2H) and oxygen (δ18O) of the water.
Each of these containers was labeled with the following information:
• Name of the sample.
Annex XI Appendix A
44
36
• Date of sampling.
• Place of sampling (basin or place name or coordinates, etc.)
• Type of sample (groundwater, surface, residual, precipitation, etc.)
At each of the sampling points mentioned above, the following in situ parameters were
measured:
• pH
• Conductivity
• Alkalinity
• Temperature
After sampling, the following information was entered on a spreadsheet:
• Sampling time
• Indicate the characteristics of the sample taken, whether it is filtered or not, and
whether it contains preservatives or additives, and label with the type of additive.
• The label of each container is protected with thick transparent tape to prevent it from
getting wet and deforming or erasing the labeled information.
The field pH measurement was performed using a Hanna portable pH/mV meter, model
HI9124, which has a precision range of ± 0.01 pH unit. The same equipment was used
to measure temperature, which has a precision range of ± 0.4 °C. The equipment was
calibrated before obtaining the first sample of each day, using two buffers, 4 and 7. The
field conductivity was measured using a Hanna multi-range portable conductivity meter
with waterproof temperature compensation, model HI-9033. This equipment has a
precision range of ± 1%. Finally, the alkalinity was measured with the "Digital Tester -
Water Alkalinity Checker HI772", which performs the measurements using the
colorimetric method. Since this alkalinity measurement methodology is not validated,
the value obtained in the field will only be used as a reference for those obtained in the
laboratory and by the modeling, considering the concentrations of HCO3. For water
filtration, a 0.45 mm filter was used, along with a Geotech Geopump™ Series I and II
peristaltic pump, which are designed for single or multiple stage pressure or liquid
suction.
In the case of carbon 14 sampling, these steps were followed:
• The water was taken from the mouth of the well, spring, or river.
• Before collecting the sample, the water was allowed to flow for a sufficient time so
that the collected water comes directly from the aquifer, spring, or river.
• The bottle was filled but leaving the neck of the bottle empty to allow the liquid to
expand during transport. During this step the peristaltic pump with the filter was used.
• Adhesive tape was placed around the cap to prevent exchange or loss of CO2 from the
water.
Annex XI Appendix A
45
37
APPENDIX B
Pictures of some of the sampling locations for the second field campaign:
Picture B1. Sampling of the spring SP-SI-5-17. The up gradient area was under vegetation, so
the whole sample set was filtered using the peristaltic pump to avoid any type of contamination.
Picture B2. The Silala River sample point, just across the Chile-Bolivia boundary, in Chile.
Annex XI Appendix B
46
38
Pictures of some of the sampling locations for the third field campaign:
Picture B3. R-SI-7-17 sampling point.
Picture B4. SP-SI-8-17 sampling point.
Annex XI Appendix B
47
39
Picture B5. SP-SI-9-17 sampling point.
Picture B6. SP-SI-16-17 sampling point.
Annex XI Appendix B
48
40
Picture B7. Spring SP-SI-2-17 sampling point.
Picture B8. Spring SP-SI-5-17 sampling point.
Annex XI Appendix B
49
41
APPENDIX C
The anions were determined by ion chromatography (Cl-, SO42-, NO3-) and volumetric
method (HCO3-), and cations by plasma emission spectrometry (ICP-OES). δ2H and
δ18O were measured on a gas-source isotope ratio mass spectrometer (Finnigan Delta S).
The hydrochemical data presented in stiff diagrams correspond to those with better
analytical quality. To evaluate the quality of the chemical analyzes the ionic balance
was carried out in all samples, where the sum of milliequivalents of anions must be
practically equal to the amount of milliequivalents of cations. This condition is checked
taking into account the ionic contributions of the majority elements calculating the
balance error by the following formula (Custodio and Llamas, 1983):
𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 (%) = 200 𝑥𝑥
Σ 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 − Σ 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎
Σ 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 + Σ 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎
In general, samples with balance errors greater than those admitted are discarded for
comparison with other samples and/or analysis dates. Negative balance errors indicate
that the concentration of some of their anionic species have been overestimated, or that
cationic species analyzes have underestimated some of these concentrations. Positive
balance errors indicate otherwise. The errors allowed (in absolute value) are generally
up to a maximum of 10%, although sometimes for very dilute waters, with electrical
conductivities (EC) of less than 200 μS/cm, slightly higher errors can be accepted.
Water samples were analyzed for both oxygen and hydrogen isotopes in Isotope Tracer
Technologies, on a Picarro CRDS (Model L1102-i). The Picarro CRDS isotopic water
analyzers provides both δ18O and δ2H stable isotope ratios with high precision in one
fast measurement. The instrument is equipped with a high precision autosampler,
capable of making consistent small volume injections into the vaporizer. In addition, the
instrument is configured with a unique vaporization module that converts the liquid
water sample to the vapour phase in a flash process at 140°C. The vapour is then
delivered into the CRDS cavity for analysis. This process avoids any possible
fractionation effects that may occur with other liquid/vapour transitions, such as
nebulizers. The Picarro analyzers are equipped with a thermally controlled optical
cavity that ensures minimal drift, even in the harshest environments. In addition, an
onboard wavelength monitor enables the absorption lines unique to H2
16O, H2
18O, and
HD16O to be scanned repeatedly, quickly and precisely.
Three to four calibrated internal standards are included at the beginning and end of
every run, as well as after every 10 samples. The employed internal standards have been
calibrated to VSMOW, GISP, and SLAP. The results are evaluated and corrected
against standards that bracket the samples, and then reported against the international
Annex XI Appendix C
50
42
reference material. Precision is 1.0 per mil or better for δ2H and 0.1 per mil or better for
δ18O based on repeated internal standards.
Tritium was measured by liquid scintillation spectrometry on samples that were first
distilled to remove non-volatile solutes, and then enriched by electrolysis by a factor of
about 9. Enriched samples were mixed 1:1 with Ultimagold Low Level Tritium (R)
cocktail, and counted for 1500 minutes in a Quantulus 1220 Spectrometer in an
underground counting laboratory at the Isotope Trace Technologies. The detection limit
under these conditions is 0.6 TU. Standardization is relative to NIST SRM 4361C.
Tritium is reported in Tritium Units. 1TU = 3.221 Picocuries/L per IAEA, 2000 Report.
1TU = 0.11919 Becquerels/L per IAEA, 2000 Report.
Due to the large amount of dissolved sulfate and the low dissolved inorganic carbon
concentrations in water, the 14C content was determined by accelerator mass
spectrometry (AMS) in a United States laboratory. The CO2 was prepared at the Isotope
Tracer Technologies Laboratory and send to the AMS lab for analysis. AMS dating
involves accelerating the ions to extraordinarily high kinetic energies followed by mass
analysis. Samples are converted to graphite prior to AMS carbon dating. Although more
expensive than radiometric dating, AMS dating has higher precision, and needs small
sample sizes. The standard used was OX: 1.05 x e-10; OX2: 1.35 x e-10; C6: 1.5 x e-10;
and C7: 0.5 x e-10, and the typical standard deviation is 5 to 10% of Standard values.
The 13C DIC analyses were measured using a Finnigan Mat, DeltaPlus XL IRMS in the
Isotope Tracer Technologies, with a standard IT2-27, IT2-34, NBS-18, NBS-19 and a
typical standard deviation of 0.2 per mil.
REFERENCES
Custodio, E. and Llamas, M.R., 1983. Hidrología subterránea. Omega, Barcelona.
Annex XI Appendix C
51
43
APPENDIX D
Annex XI Appendix D
Approved by:
ISOTOPE TRACER
TECHNOLOGIES L C
Orlan Shouakar-Stash, PhD
Director
Isotope Tracer Technologies Inc.
695 Rupert St. Unit B, Waterloo, ON, N2V l ZS
Tel: 519-886-5555 I Fax: 519-886-5575
Email: [email protected]
Website: www.it2isotopes.com
Isotope Analyses for:
Arcadis-Chile
IT2 FILE#
170006
2017-02-16
52
44
Annex XI Appendix D
2/3
File Number:
#
1
2
3
4
5
ISOTOPE TRACER
TF.Cll:-.lOLOGIES INC
170006
Sample ID Collection
Date
Sll·B 2016-12-21
S12·1 2016-12·21
513 2016·12·22
Silalal-1 2016-12-22
Sl2-II 2016-12-22
6 SilalalA(Previously SllA) 2016-12-22
7 S14·A 2016·12·21
8 SllA 2016-12·21
9 5ilalal•II 2016·12·22
10 S14-B 2016-12·21
11 S12B-I 2016·12·22
12 S1-02 2016-12-20
13 S1-01 2016-12-20
14 Rio 2016-12·21
15 S1·11 2016·12·21
16 S1-21 2016-12-21
17 Sl-05 2016-12-21
Tritium is reported in Tritium Units.
Time
15:30
19:2S
17:50
18:1S
11:05
19:20
15:40
13:00
16:20
16:25
13:40
15:20
16:00
17:45
13:44
12:12
15:15
ITU~ 3.22 I Picocurries/L per IAEA, 2000 Report.
ITU~ 0.I 1919 Becquerels/L per IAEA, 2000 Report.
Approved by:
O~SS-t2zd
Orfan Shouakar-Stash, PhD
Director
Isotope Tracer Technologies Inc.
695 Rupert St. Unit B, Waterloo, ON, N2V 125
Tel: 519-886-5555 I Fax: 519-886-5575
Email: orfan@)it2isotopes.com
Website: www.it2isotopes.com
Sample# E'H (ULL) Repeat
42768 X <0.05
42769
42770
42771
42772 X 0.07
42773
42774
42775
42776 X 0.22
42777
42778
42779 X 0.16
42780
42781
42782
42783 X 0.18
42784 X < 0.05
± la
0.23
0.23
0.23
0.23
0.22
0.19
Client: Arcadis Chile
Address: Antonio Varas 621
Providencia, Santiago
8320000
Tel: 56 2 23816229
Attn.: Ximena Orrego
201 7-02-16
E-mail: [email protected]
E-mail: [email protected]
695 Rupert St. Unit B - Waterloo• Ontario -N2V 125 • Tel. 519-886-5555 • Fax: 519-886-5575 • www.it2isotopes.com
53
45
Annex XI Appendix D
3/3
ISOTOPE TRACER
TECHNOLOGIES INC
File Number: ~
# Sample ID Collection
Date Time
1 511-B 2016-12-21 15:30
2 512-1 2016-12-21 19:25
3 513 2016-12-22 17:50
4 Silalal-1 2016-12-22 18:15
5 512-11 2016-12-22 11:05
6 SilalalA(Previously SllA) 2016-12-22 19:20
7 514-A 2016-12-21 15:40
8 SllA 2016-12-21 13:00
9 Silalal-11 2016-12-22 16:20
10 514-B 2016-12-21 16:25
11 512B-1 2016-12-22 13:40
12 51-02 2016-12-20 15:20
13 51-01 2016-12-20 16:00
14 Rio 2016-12-21 17:45
15 51-11 2016-12-21 13:44
16 51-21 2016-12-21 12:12
17 51-05 2016-12-21 15:15
IJC DIC Anal)SCS
Sample#
42768
42769
42770
42771
42772
42773
42774
42775
42776
42777
42778
42779
42780
42781
42782
42783
42784
Instrument Used: Finnigan Mat, DeltaPlus XL IRMS, Germany.
Standard Used: IT2-27/ IT2-34/ NBS-I 8/NBS-I 9
Typical Standard deviation: ± 0.2 %o
14C DIC Anal)S<S
Instrument Used: AMS (Accelerator Mass Spectrometry)
Standard Used:
OXI: l.05xe- IO
OX2: 1.35 x e-1 O
C6: 1.5 x e-10
C7: 0.5 x e-10
Typical Standard deviation: 5 to 10% of Standard values listed above
Approved by:
O~SStad
Orf an Shoua kar-Stash, PhD
Director
Isotope Tracer Technologies Inc.
695 Rupert St. Unit B, Waterloo, ON, N2V lZS
Tel: 519'88&.SSSS I Fax: 519·88&.5S75
Email: [email protected]
Website: www.it2isotopes.com
6"c Result Repeat
DIC PDB
X -7.3 -7.5
X -8.0
X -8.0 -7.7
X -7.0 -7.3
Client: Arcadis Chile
Address: Antonio Varas 621
Providencia, Santiago
8320000
Tel: 56 2 23816229
Attn.: Ximena Orrego
20 17-02-16
E-mail: [email protected]
E-mail: [email protected]
14c Fraction of Modern
DIC pmc ± lo
X 9.93 0.08
X 14.54 0.09
X 26.66 0.13
X 76.86 0.35
695 Rupert St. Unit B - Waterloo - Ontario -N2V 125 - Tel. 519-886-5555 - Fax: 519-886-5575 - www.it2isotopes.com
54
46
Annex XI Appendix D
Approved by:
ISOTOPE TRACER
TECHNOLOGIES 11 C
Orlan Shouakar-Stash, PhD
Director
Isotope Tracer Technologies Inc.
695 Rupert St. Unit B, Waterloo, ON, N2V lZS
Tel: 519-886-5555 I Fax: 519-886-5575
Email: orfan@)it2isotopes.com
Website: www.it2isotopes.com
IT2 FILE#
170031
2017-04-11
55
47
Annex XI Appendix D
1/3
ISOTOPE TRACER
IT Cll'.\01.0C;JFS 1,c
FIie Numher: !.1Qfil
# sample ID Collection
Date
1 SP-SI-S-17 2017--02--01
2 Blank Sample I
3 SP-Sl-31-17 2017-02-02
4 R-51-3-17 2017--02-01
s R-Sl--&-17 2017--02--01
6 R-51-26--17 2017--02--01
7 SP-S1-16--17 2017--01-31
8 SP-51-8-17 2017-02-01
9 SP-51-15-17 2017-01-31
10 SP-S1-9-17 2017-02-01
11 SP-51-1-17 2017-01-31
12 R-51-2-17 2017-01-31
13 R-51-4-17 2017-02-01
14 SP-51-10-17 2017-02-01
15 SP-51-29-17 2017-02-01
16 R-S1-7-17 2017-02-01
17 SP-51-28-17 2017-01-31
18 SP-51-17-17 2017-01-31
19 SP-51-18-17 2017-01-31
20 SP-51-27-17 2017-01-31
21 SP-51-19-17 2017-01-31
Time
14:00
I
12:00
17:20
1340
17:19
18:30
11:15
18:07
12:45
16:18
15:24
13:30
11:00
15:30
17:19
18:10
17:55
17:10
15:30
15:50
Do not run as per Ramon's instructions on Feb. 23, 2017
j180 & 211 Analyses j
lnslrumenl Used: Cavi1y Ring Down Spectroscopy (CRDS)
CRDS (Model L2130-i) (Picarro. California, USA)
Sranda r d Ulro:
Field Parameters
Alkalinity pH Temp.
jppm) rCJ
48 8.05 20.2
I I I
75 7 19.1
22 7.33 18.3
90 7.68 213
119 9.02 18.4
48 8.18 15.5
7.61 19.2
43 8.11 15.6
7.5 18.S
63 7.92 15.2
66 9.03 17.1
96 7 64 208
74 7.05 13.6
44 7.22 21.S
119 9.02 18.4
17 7.13 11.S
28 7.25 IS.I
19 7.13 15.6
83 6.87 16.6
28 7 16.1
IT2-12A / IT2-13A / ITI-00 Calibrated with IAEA Standards (V-SMOW. S LAP. and GISP)
Typical Sca ndard de,ia11on:
(" O:l:0.1"-) f H:i:.1"-)
Approved by:
Orfan Shouakar-Stash, PhD
Director
Isotope Tracer Technologies Inc.
695 Ru~n St. Unit 8, Wner1oo, ON, N2V 125
T~:51~5555I Fax:519-&&S-5575
lm:tl:orf .... itlkotOpff.(Offl
Wfflltt : -.it2kotoptt.(om
Sample# 6''o
Conductivity H,0
(mS/cm)
160 43058 X
I 43059 X
210 43060 X
220 43061 X
320 43062 X
215 43063 X
84 43064 X
88 43065 X
131 43066 X
90.7 43067 X
170 43068 X
100 43069 X
330 43070 X
290 43071 X
220 43072 X
215 43073 X
230 43074 X
170 43075 X
220 43076 X
220 43077 X
190 43078 X
.,,,,
Client : Arcadis Chile
Address: Antonio Varas 621
Providencia, San1iago
8320000
Tel: 56 2 23816229
Ann.: Natalia Navarrete
Ann.: Ximcna Omgo
2017-04-11
E-mail: [email protected]
E-mail: [email protected]
Stdv 6'H .,,,, """ VSMOW H,0 VSMOW
·11.72 0.03 X -82.9 0.2
-10.92 0.02 X -77.9 0.2
-11.72 0.02 X -90.2 0.4
-11.64 0.01 X -91.8 0.1
X
X
-11.82 0.02 X -92.3 0.1
-12.04 0.03 X -83.7 0.4
-11.83 0.03 X -92.4 0.3
-12.01 0.03 X -84.0 0.3
-11.84 0.03 X -92.6 0.3
-11.61 0.03 X -92.S 0.1
X
-11.72 0.03 X -89.4 0.3
-11.73 0.03 X -91.4 0.2
X
-11.78 0.02 X -92.3 0.1
-11.77 0.02 X -91.9 0.1
-11.77 0.02 X -91.8 0.1
-11.80 0.02 X -91.8 0.1
-11.79 0.02 X -91.S 0.1
695 Rupert St. Unit 8 - Waterloo - Ontario -N2V lZS- Tel. 519-886-SSSS- Falt: 519-886-5575 - www.it2iSOtOpM.COm
56
48
Annex XI Appendix D
2/3
ISOTOPE TRACER
TITII S.OU)C,IFS l'-C
File Number : 11Qfil
• Sample 10 Collectioo
Date
1 SP-S1-5-17 2017-02-01
2 Blank Sample I
3 SP-Sl-31-17 2017--02--02
4 R-S1-3-17 2017-02-01
5 R-Sl-6-17 2017-02-01
6 R-S1-26-17 2017-02-01
7 SP-Sl-16-17 2017-01-31
8 SP-S1-8-17 2017-02-01
9 SP-Sl-15-17 2017-01-31
10 SP-S1-9-17 2017-02--01
11 SP-S1-1-17 2017-01-31
12 R-51-2-17 2017-01-31
13 R-51--4-17 2017-02-01
14 SP-S1-10-17 2017-02-01
15 SP-Sl-29-17 2017-02-01
16 R-S1-7-17 2017-02-01
17 SP-Sl-28-17 2017-01-31
18 SP-Sl-17-17 2017-01-31
19 SP-Sl-18-17 2017-01-31
20 SP-Sl-27-17 2017-01-31
21 SP-Sl-19-17 2017-01-31
Tme
14:00
I
12:00
17:20
13:40
17:19
18:30
11:15
18:07
12:45
16:18
15:24
13:30
11:00
15:30
17:19
18:10
17:S5
17:10
15:30
15:50
Do not run as per Ramon's instructions on Feb. 23, 2017
1311 ANALYSES I
Tritium is reported in Tritium Units.
ITU• 3.221 Picocurries/1.. per IAEA 2000 Report.
ITU-0.1 1919 Bccquerels/l per IAEA. 2000 Report.
Approved by:
Orfan Shouakar-Stash, PhD
Director
Isotope Tracer Technologies Inc.
695 Ru~n St. Unit 8, wu~rloo, ON, N2V us
T~: Sl~SSSS I fax: S19-AU-SS7S
Emal: orf~llsotopes..com
W«Klt-, WWW.ltlkotOf>U.COffl
Alkalinity
loom
48
I
7S
22
90
119
48
43
63
66
96
74
44
119
17
28
19
83
28
Field Parameters
pH Temp. Conductivity
·c mS/cm
8.05 20.2 160
I I I
7 19.l 210
i.33 18.3 220
7.68 21.3 320
9.02 18.4 m
8.18 15.S 84
7.61 19.2 88
8.11 15.6 131
7.5 18.5 90.7
7.92 15.2 170
9.03 17.1 100
7.64 20.8 330
7.0S 13.6 290
7.22 21.5 220
9.02 18.4 m
7.13 11.5 230
7.2S 15.1 170
7.13 15.6 220
6.87 16.6 220
7 16.1 190
Sample# Ultra-'H Repeat
43058
430S9
43060
43061
43062
43063
43064
43065 X < 0.05
43066 X 0.31
43067
43068
43069
43070
43071 X < 0.05
43072
43073 X <0.05
43074
4307S
43076
43077
43078
Cl lent: Areadis Chile
Addrns: Antonio Varas 621
Providencia. Santiago
8320000
Tel: 56223816229
Ann.: Natalia Navartttc
Attn.: Ximcna Orrego
2017-04-11
£-man: [email protected]
E-mail: xime [email protected]
tlo
0.20
0.29
0.11
0.31
695 Rupert St. Unit B -Waterloo - Ontario -N2V 12S - Tel. S19--886-5555 - Fax: S19--886-557S - www.it2isotopes.com
57
49
Annex XI Appendix D
3/3
ISOTOPE TRACER
ITUISOl.()(;1rs 1,(
Fllr Numtwr : !.2Qfil . Sample ID Collection
Date Time
1 SP-SI-S-17 2017--02-01 14:00
2 Blank Sample I I
3 SP-Sl-31-17 2017--02-02 12:00
4 R-51-3-17 2017--02-01 17:20
5 R-Sl--&-17 2017--02--01 13:40
6 R-S1-26-17 2017--02--01 17:19
7 SP-Sl-16--17 2017--01-31 18:30
8 SP-51-8-17 2017-02-01 11:15
9 SP-Sl-15-17 2017--01-31 18:07
10 SP-Sl-9-17 2017--02--01 12:45
11 SP-Sl-1-17 2017--01-31 16:18
12 R-Sl-2-17 2017--01-31 15:24
13 R·Sl-4-17 2017-02-01 1330
14 SP-Sl-10.17 2017-02-01 11:00
15 SP-Sl-29-17 2017--02--01 15:30
16 R-Sl-7-17 2017--02--01 17:19
17 SP-Sl-28-17 2017--01-31 18:10
18 SP-Sl-17-17 2017--01-31 17:55
19 SP-Sl-18-17 2017-01-31 17:10
20 SP-Sl-27-17 2017--01-31 15:30
21 SP-Sl-19-17 2017--01-31 15:50
Do not run asper Ramon's instructions on Feb. 23, 2017
Alkalinitv
jppm)
48
I
75
22
90
119
48
43
63
66
96
74
44
119
17
28
19
83
28
Oient asked to run 14C analysis for this ~mple in email received Feb. 14
Oient asked to run 14C anatys!s for this sample in email received Feb. 23
juc DIC Anatnes
lnslrumenl Used:
Finnigan MAT, Deka""'"' XL IRMS, Germany.
Standard Used:
rr'-21
11'.34
NDS-18
NDS-19
Typica l Sta ndard de,iallon:
± 0-2"-
lnstrumenl Used:
AMS (Accelerator Mass Spectrometry)
Standard Used:
OXI: 1.05 x e-10
OX2: l.35xe-10
C6: Uxe-lO
C7: O.S x c-10
Typica l Standard de,lalion:
5 to 10'/4 ofStanda,d values listed abcwe
Approved by:
Orfan Shouakar-Stash, PhD
Director
Isotope Trace r Technologies Inc.
695 Rupert St. Unit B, Waterloo, ON, NlV l ZS
Tel:S19-&86-SSS5 1 F.u:Sl9-&86-557S
Emal : orl_.,itlko!:~
We!Kll:•:-.ltlkot-.com
Field Parameters Sample•
H Temo. Conductivitv
rCJ (mS/cm)
8.05 20.2 160 43058
I I I 43059
7 19.1 210 43060
7.33 18.3 220 43061
7.68 21.3 320 43062
9.02 18.4 215 43063
8.18 15.5 84 43064
7.61 19.2 88 43065
8 .11 15.6 131 43066
7.5 18.S 90.7 43067
7.92 15.2 170 43068
9.03 17.1 100 43069
764 208 330 43070
7.05 13.6 290 43071
7.22 21.5 220 43072
9.02 18.4 215 43073
7.13 11.5 230 43074
7.25 15.1 170 43075
7.13 15.6 220 43076
6.87 16.6 220 43077
7 16.1 190 43078
6"c Result I
DIC PDB
X -9.l
X -6.8
X -5.8
X -6.7
X
O lent: Arcadis Chile
Address: Antonio Varas 621
Providencia, Santiago ,n,0000
Tt l: 56 2 23816229
Altn.: Na1alia Navarrc-tc
Altn.: Ximena Orrego
2017..()4..I I
E-mail: [email protected]
[.mall: ,[email protected]
Repeat "c Fraction of Modern
DIC = < ...
X 45.97 0.27
X 78.39 0.24
-6.1 X 32.41 0.15
X 30.06 0.15
X
695 Rupert St. Unit 8 - Waterloo - Ontario -N2V 125- Tel. 519-886-5555- Fa11.: 519-886-5575 - www.it2isotopM.com
58
50
Annex XI Appendix D
Approved by:
ISOTOPE TRACER
TECHNOLOGIES INC
Orfan Shouakar-Stash, PhD
Director
Isotope Tracer Technologies Inc.
695 Rupert St. Unit 8, Waterloo, ON, N2V lZS
Tel: 519·88ti-SSSS I Fax: 519·88ti-5575
Email: [email protected]
We bs ite-; www.lt2lsotopes.com
Isotope Analyses for:
Universidad Catolica
del Norte
IT2 FILE#
170286 & 170287
2019-01-08
59
51
Annex XI Appendix D
file Numbu S:amplo: 10
170287 ft·S1-Z-017
170287 R·RI0-1-017
170287 R·SH-017
170286 R·S1·8-017
170287 R·Sl-9-017
170286 R·Sl-4-017
170286 R·S1 •7-017
170287 SP-SH0-017
170287 SP-Sl-28-017
170287 SP-SH6-017
170286 SP-SH7-017
170286 SMHS-017
1702 .. SP-SH~7
170287 SP-Sl-27-017
170287 S.P-51-1-017
170287 SP-Sl-32-017
170287 S.P-Sl•S-017
170287 S.P-51·8-017
170286 S.P-51-9-017
170286 SP-Sl-31-017
1702 .. SP-Sl·2~7
170286 SPW-OQN•Sl-017
170287 PW-80-8-017
170287 MWl.·UON•A-017
170287 PW·UClN-A-017
170287 PW-UQN-8-017
170286 MW-OQN·A-017
1702 .. PW-OQN•A-017
170286 PW-OQN•&-017
170287 PW-80-A-017
AMS (.4m lent« Mass Specttometty)
Sfaodard Used:
OXl: l.0h e:-10
OXJ: Uhe:-10
C6: 15xe-10
CJ: 05 x e-10
T)-pical St.aodard deri•tioo:
S to I 0% of Sr.arid.mi \'ab.I.es listed abo\--e
...C.ol lection
12·10--2017
12·10--2017
12·10--2017
U -10--2017
t ,H 0--2017
1HO--l017
U -10--2017
t ,H 0--2017
13·10--2017
12·10--2017
13·10--2017
13·10--2017
12·10--2017
12·10--2017
12·10--2017
14·10--2017
10-10--2017
U ·10--2017
12·10--2017
U -10--2017
U -10--2017
U ·10--2017
12·10--2017
U -10--2017
12·10-2017
12·10-2017
U ·10--2017
U -10--2017
U -10--2017
12·10--2017
j180&2H(C:RDS) j
lostnlmeot Used: Ca\'ity Rieg Do-a'll Spectroscopy (CR.DS)
CRDS (Mod,! l.lUIH) (Piwro. c.ufuntia. USA~
Sfaodard Used:
S~ell' •c
"= l>C
U :43 47576 X
17:45 47SB6
18:30 47578 X
15:30 47563 X
12:00 47'580 X
14:00 47'51-9
11:00 47'558 X
11:25 47'57' X
17:40 47'588
1S:45 47'584
17:15 47572
16:30 47'564 X
11:50 47'568
12:05 47'583
1S.:10 47'582
14:00 47581 X
I 47574 X
16:35 47573 X
10:30 47571
11:30 475S.9 X
13:35 47'560 X
13:23 47565 X
12:45 47575 X
I 47'5 ..
18:00 47'587
16:30 47'Sn X
17:15 47'570
14:S6 47561 X
1S.:SO 47562 X
19:00 47'SB5
Jl".IA 2B I In-13A / fT2-00 Calibrated W!lh lo\EA Swid..uds (V-SY.OW. SLAP. IIOO GISP)
1)]lkal St.aodard deri•tion:
("0=0.1%.) tH • lX.)
ApprOYed by:
Orlen 5houekw·Ste$h, PhD
Director
h otope T ~er T echnoloeie-l Inc.
6S3 A--.1pcrt St. Unit 8, W""100, ON, N2\I U,
T.i:SlM:86-SSSS I r .. : S19,88:6.SS,S
-c..a:-,.-..~---
14Cyr 8P
9343
7533
7452
13736
9021
10350
7410
114n
mo
3164
9738
8SS.1
19939
19210
18530
12230
12141
Ro:$uh ,•, ""' • 0.3125 0.00,
45 0.3915 0 .0022
4l 0.3955 0 .002.1
rn 0.18087 0.00197
93 0.3253 o.oua
54 0.2757 0 .0018
.. 0.3975 0 .0044
.6.7 0.2396 0.00, .. 0.7066 0 .0041 0.6744 0 .0031
" 0.2975 0 .0034
115 0.3449 0 .0049
102 0.0836 0 .0011
100 0.0915 0 .0011
1<6 0.0996 0 .0018
.5.3 0.2182 0 .0014 0.Zl06 0 .0015
Clieat: Uai\-ersidad Catt>lic.11 d.el None
Address: ~ 0610
Depanamec10 de Ci.enciti Geolog,:icai
Amof;\pS!a.Cltile
Tel: 55-235 5968
Atta.: Christian Hemra Lameli
E-mail:: che r~ r:apucn.d
•"<> Aw.r I SU,v •'It Aw,
201!>-01-08
5,.,
H,O VSMOW H,O VSMOW
X ·12.15 o.oz X -93.6 0.2
X ·12.09 0.03 X -92.9 0.3
X ·12.09 0.03 X -92.B 0.3
X ·12.05 0.04 X -92.9 0.2
X ·12.32 0.06 X -93.1 0.5
X ·12.l§ 0.04 X .. ,~ O.l
X ·11.98 0.01 X -90.0 0.4
X ·12.21 0.02 X -90.B 0.1
X ·12.Z0 0.02 X -92.B 0.1
X ·12.22 0.01 X -93.0 0.3
X ·12.Z0 0.01 X -9ZA 0.3
X ·1U8 0.01 X -92.B 0.1
X ·1UO 0.01 X -91.4 0.4
X ·12.23 0.03 X -92.7 0.3
X ·12.25 0.03 X -93.1 0.1
X ·12.19 0.05 X -9ZA 0.3
X ·1ZAO 0.02 X ·= 0.2
X ·12.13 0.03 X -91.B 0.3
X ·12.08 0.02 X -92.0 0.1
X ·12.54 0.04 X -94.6 0.3
X ·12.53 0.02 X -95.1 0.1
X ·1ZAi 0.02 X -94.6 0.1
X ·12.51 0.04 X -94.6 0.1
X ·12.55 0.03 X -94.9 0.1
X ·12.44 0.01 X .93.9 0.1
X ·12.30 0.01 X -93.2 0.3
X ·12.30 0.02 X -93.3 0.0
X ·12.52 0.01 X -95.0 0.1
60
52
Annex XI Appendix D
Approved by:
ISOTOPE TRACER
TECHNOLOGIES INC
Orfan Shouakar-Stash, PhD
Director
Isotope Tracer Technologies Inc.
695 Rupert St. Unit B, Waterloo, ON, N2V 125
Tel: 519·886-5555 I Fax: 519·886-5575
Email: [email protected]
Website: www.it2isotopes.com
Isotope Analyses for:
Universidad Catolica
del Norte
IT2 FILE#
170286
2017-12-07
61
53
Annex XI Appendix D
l/2
ISOTOPE TltACEII
TFCll '-,'01.0CIFS I'\;(
Filt> 1'"umbu: 170286
• 5ample1D C.Ollectioo
Date
1 R-S1-7-017 13-10-2017
2 SP-S1-31-017 13-10-2017
3 SP-S1-29-017 13-10-2017
4 PW-DQN-A--017 13-10-2017
5 PW-OQN-8-017 13-10-2017
6 R-S1-8-017 13-10-2017
7 SP-S1-18-017 13-10-2017
8 SP-W-DQN--017 11-10-2017 • SP-S1-8-017 11-10-2017
10 SP-S1-5-017 11-10-2017
11 SP-51-19-017 12-10-2017
12 R-S1-4-017 13-10-2017
13 MW-OQN-A--017 11-10-2017
14 SP-S1-9-017 12-10-2017
15 SP-S1-17-017 13-10-2017
ji3c DIC Analysts
lrntru.meut Used:
Finnigan MAT. Odtfl-XL IRMS, Germany_
Standard Ustd:
n'-27
rr2-14
NBS-IS
NBS-19
Typical Sraudard de,Ution:
±0_2~
Orlan Shouakar-Stash, PhD
Dirertor
Isotope Tracer Technok>gies Inc..
69S Rupen St. UM 8, Wate rloo, ON, N2Y lZS
TRI: Sl 9-a86,-SSSS I Fu :Sl~SS7S
E.....i: ~opH,,C<lffl
Website:-.itlis«opes.M)ffl
Time
11:00
11:30
13:35
14:56
15:50
15:30
16:30
13:23
16:35
18:30
11:50
14:00
17:35
10:30
17:15
Sample# 613c Result
DIC
47558 X -5.9
47559 X -7.7
47560 X -8.7
47561 X -7.4
47562 X -7.4
47563 X -7.9
47564 X ....
47565 X ....
47566
47567
47568
47569
47570
47571
47572
! u c DIC Analyses
Insn'llment Used:
AMS (Accela:lror ~ Spectrometty)
Standard Used.:
OXl : 1.0Sxc-10
OX2: 1.3Sxc-10
C6: l.Sx c-10
C7: 0.5x e- 10
Typical S(andal'd de,iation:
5 to 10-/4 of Standard values listed above
Reoeat
PDB
-6.1
-7.3
-6.6
UC
DIC
X
X
X
X
X
X
X
X
Client: Universidad Catolica dd Norte
Addrtss: Ang,mos 0610
Dcpartamcnto de Cimcias Geologicas
Antofagasta, Cbile
Tel: SS-2355968
Ann.: Christian Herrera Lamcli
E-mail: [email protected]
Result
14Cyr BP ± F14C
9021 93 0.3253
9738 92 0.2975
8551 115 0.3449
12230 S3 0.2182
12141 56 0.2206
7452 42 0.3955
7410 88 0.3975
19939 102 0.0836
695 Rupert.St. Unit B- Waterloo - Ontar'lo-N2V 125- Tel. 519-886-5555 - Fax: 519-886-S57S - www.it2isotopes..c.om
2017-12-07
' 0.0038
0.0034
0.0049
0.0014
0.0015
0.0021
0.0044
0.0011
62
54
Annex XI Appendix D
2/2
•
l
2
3
4
5
6
7
8 • 10
11
12
13
14
15
ISOT OPE T llACElt
'Tl·Tll'-:01.0( ,IFS 1-...:(
l i0286
Sam~ID Collection
Date
R-Sl-7-017 13-10-2017
SP-S1-31-017 13-10-2017
SP-S1-29-017 13-10-2017
PW-CXlN-A-017 13-10-2017
PW-OQN-B-017 13-10-2017
R-Sl-8-017 13-10-2017
SP-S1-18-017 13-10-2017
SP-W-OQN-017 11-10-2017
SP-S1-8--017 11-10-2017
SP-S1-5-017 11-10-2017
SP-S1-19-017 12-10-2017
R-Sl-4-017 13-10-2017
MW-OQN-A-017 l M 0-2017
SP-S1-9-017 12 -10-2017
SP-Sl-17-017 13-10-2017
11,0 & 2H (CRDS) I
Instrument Used: Cavity Ring I)o\\.n Spectroscopy (CRDS)
CRDS (Model L2130-i) (Picarro, California, USA).
Standard Uwd:
Samoleff 61so
Tlme H,O
11:00 47558 X
11:30 47559 X
13:35 47500 X
14:56 47561 X
15:50 47502 X
15:30 47563 X
16:30 47564 X
13:23 47565 X
16:35 47566 X
18:30 47567 X
11:50 47568 X
14:00 47569 X
17:35 47570 X
10:30 47571 X
17:15 47572 X
ITT-128/ IT2-13A/ ID-00 Calibrated with lAEA Standards (V-SMOW, SLAP, aM GISP)
Typical S1and.1rd d~,iariou:
(
110 ±0.1%.) (1H ± 1"-)
Orlan Shouakar-Stash, PhD
Director
l~tope Tracer Tee~ Inc.
695 Ru pen St. Unit 8, Wate rklo, ON, N2V 125
To,l: 519-&86-5555 l fu: 519---U6---5575
-•~iUi<.Gtopu..u,m
Wff!Sillt:www~opu.com
A,e, stdv O'H
VSMC/,/,/ H,O
-11.98 0.01 X
-12.13 0.03 X
-12.08 0.02 X
-12.30 0.01 X
-12.30 0.02 X
-ll.05 0.04 X
-12.18 0.01 X
-12.54 0.04 X
-12.41 0.00 X
-12.03 0.03 X
-12.10 0.01 X
-12.26 0.04 X
-12.44 0.01 X
-U.40 0.02 X
-12.20 0.01 X
Q ient: Univmidad Ditolica dd Norte
Address: Angamos 0610
~odeCil"Ilcias~logicas
Antofagasta, Chile
Tel: SS-2355968
Attn.: Christian Hen'° Lamcli
L-mail: cherrera@uc;n.d
·- stdv
VSMOW
-9) .0 0.4
-91.8 0.3
-92.0 0.1
-93.2 0.3
-93.3 0.0
-92.9 0.2
-92.8 0.1
-9-1.6 0.3
.a,.o 0.2
.a,_3 0.2
-91.4 0.4
-93.1 0.3
-93.9 0.1
.a,_1 0.2
-92.4 0.3
695 Rupert St. Unit B-Waterloo -Onta00-N2V 1Z5 - Tel. 519-886-5555 - Fax: 519-886-557S - www.it2isotopes.com
2017-12-07
63
55
APPENDIX E
Figure E1. Piper diagrams for the rainy season.
Annex XI Appendix E
100
• (SP-Sl-9-17)
S04 + Cl
Na+ K 0
100
Ca 0
CATION
100
0 Cl
ANION
S04
100
River samples ~----------~ River samples
♦(SP-Sl-5-17) I &(R-Sl-7-17) I ■(SP-Sl-31-17) X(SP-Sl-1 0-17) + (R-S1-4-17)
Springs samples
e (SP-Sl-29-17) o (R-Sl-3-17) &(R-Sl-2-17) ■(SP-Sl-27-17) (SP-Sl-1 9-17) + (SP-Sl-1&-17)
e (SP-Sl-16-17) +(SP-Sl-8-17) &(SP-Sl-1-17) - (SP-Sl-17-17) X(SP-Sl-15-17) + (SP-Sl-2&-17)
64
56
Figure E2. The Stiff diagrams of water samples collected during the second campaign in the
Silala River basin (rainy season).
Annex XI Appendix E
CODELCO lntali.e "'-/.- ~
<- /
lnacaliri
Police St..tion
600 1200
Mete,s
~ r<aiorPro,rtiD11,wtS8-1
1800
.......
-9/oStfa/a
PW-DQN-A-016
PW-DQN-B-016
MW-DQN·A-016
/'/, Na Cl • Springs
(
j Mg so, • Wells / I Ca ---,----HCC, "' River
3meq j 3meq
I
65
57
Figure E3. The Stiff diagrams of water samples collected during the third campaign in the
Silala River basin (rainy season).
Annex XI Appendix E
/i/
0 600 ~$
SCALE
1100
Meters
1800
Sample sites
Cl
Me-QtOI P,ojN:tion. W<iS !4
Mg
• Springs
( Ca
so, ,, River
3meq [ 3meq
HCO,
66
58
APPENDIX F
Date Organization Country Sample name Water type
T
(°c)
pH
lab
EC
(μS/cm)
Cl
(mg/l)
SO4
(mg/l)
Ca
(mg/l)
Mg
(mg/l)
NO3
(mg/l)
Si
(mg/l)
Na
(mg/l)
K
(mg/l)
HCO3
(mg/l)
Error
(%)
mar-
00 Diremar Bolivia Laguna Khara Lake 10 8,3 715 112,38 16,5 11,83 19,61 0,1 54 136 27 110,26 49,5
oct-16
VRHRMMAya
Bolivia SI-1 Spring 15 8,64 115,2 6,94 7,29 7,7 2,28 2,41 17,37 8,8 1,9 31,41 10,9
oct-16
VRHRMMAya
Bolivia SI-1R Spring 15,9 8,58 112,9 6,75 7,43 7,2 2,31 2,39 16,52 8,6 1,8 29,78 10,8
oct-16
VRHRMMAya
Bolivia SI-2 Spring 15,6 8,04 244 7,98 9,81 18,47 6,79 2,67 21,31 17 2,8 115,24 -2,8
oct-16
VRHRMMAya
Bolivia SI-3 Spring 14,5 7,91 254 7,32 10,05 17,1 8,07 2,55 22,44 17 2,95 118,5 -2,7
oct-16
VRHRMMAya
Bolivia SI-4 Spring 15,5 8,8 229 7,6 7,33 16,67 6,49 2,75 20,19 17 2,7 109,81 -1,5
oct-16
VRHRMMAya
Bolivia SI-5 Spring 9,2 8,64 285 6,18 9,81 19,9 9,49 1,34 22,26 17 3,71 127,44 4,9
oct-16
VRHRMMAya
Bolivia SI-6 Spring 16,6 8,51 113,8 7,13 6,61 7,93 1,72 2,3 17,27 8,7 2 24,16 22,6
oct-16
VRHRMMAya
Bolivia SI-7 Spring 16,1 8,53 128,6 6,46 9,6 8,74 2,64 2,39 23,38 9,8 2,1 37,79 8,7
oct-16
VRHRMMAya
Bolivia SI-8 Spring
16,1
5 7,69 394 8,55 10,02 29,87 15,57 2,3 31,65 17 5,21 210,19 -7,4
oct-16
VRHRMMAya
Bolivia SI-9 Spring 15 8,57 123,5 6,84 7,74 9,73 3,14 2,39 17,46 9,6 2 47,72 3,3
oct-16
VRHRMMAya
Bolivia SI-10 Spring 14,2 8,23 96,4 6,08 7,12 6,87 1,95 1,85 23,01 7,5 2,6 36,24 -5,0
oct-16
VRHRMMAya
Bolivia SI-11 Spring 15,5 8,61 85,8 5,42 8,36 6,21 1,97 1,71 16,99 6,5 2,1 24,16 7,6
oct-16
VRHRMMAya
Bolivia SI-1 Spring 5,82 8,87 191,6 6,94 11,74 6,53 9,4 2,58 16,19 13,68 1,34 76,95 -0,6
oct-16
VRHRMMAya
Bolivia SI-1A Spring 16,2 8,85 113,3 6,75 10,53 5,75 1,45 1,91 13,99 13,52 1,94 36,36 0,8
oct-16
VRHRMMAya
Bolivia SI-2A Spring 15,6 8,48 237 7,98 10,77 14,33 6,19 2,05 17,69 21,08 2,93 115 -6,5
oct-16
VRHRMMAya
Bolivia SI-3A Spring 15,5 8,45 253 7,32 13,43 15,63 7,06 2,13 18,13 23,18 3,13 125,15 -4,7
oct-16
VRHRMMAya
Bolivia SI-4A Spring 15,7 8,57 228 7,6 11,62 10,18 5,59 2,3 17,78 22,07 2,83 101,47 -7,4
oct-16
VRHRMMAya
Bolivia SI-5A Spring 16,7 9,62 294 6,18 3,53 15,95 8,8 0,04 18,66 24,07 4,63 120,08 19,3
oct-16
VRHRMMAya
Bolivia SI-6A Spring 16,6 9,06 115,2 7,13 10,17 5,33 1,34 1,99 15,84 13,85 1,94 45,66 -14,8
oct-16
VRHRMMAya
Bolivia SI-7A Spring 16,2 9,1 127,3 6,46 12,22 6,18 1,78 1,88 16,11 15,38 1,94 54,12 -14,2
oct-16
VRHRMMAya
Bolivia SI-8A Spring 16,6 8,32 410 8,55 20,99 30,47 15,68 2,24 30,73 24,24 5,73 208,02 -2,6
Annex XI Appendix F
67
59
Date Organization Country Sample name Water type
T
(°c)
pH
lab
EC
(μS/cm)
Cl
(mg/l)
SO4
(mg/l)
Ca
(mg/l)
Mg
(mg/l)
NO3
(mg/l)
Si
(mg/l)
Na
(mg/l)
K
(mg/l)
HCO3
(mg/l)
Error
(%)
oct-16
VRHRMMAya
Bolivia SI-9A Spring 15,5 9,16 122,7 6,84 11,49 5,95 1,67 1,99 15,05 14,83 1,84 51,58 -15,0
oct-16
VRHRMMAya
Bolivia SI-10A Spring 14,7 9,06 99,3 6,08 9,81 4,08 0,9 1,66 14,52 11,95 1,94 37,21 -17,7
oct-16
VRHRMMAya
Bolivia SI-11A Spring 15,5 9,31 85,2 5,42 10,77 6,06 1,23 1,66 16,11 8,89 1,94 33,82 -13,1
jun-00 SERGEOMIN Bolivia
Silala Boca toma
(canal) Spring N/A 7,65 176 7,16 9,05 10,8 4,85 N/A N/A 23 2,5 106 -6,0
jul-00 SERGEOMIN Bolivia
Silala Sur Canal
Sur Spring N/A 7,7 112 7,16 7,82 6,6 1,09 N/A N/A 20 1,9 68,93 -11,0
ago-
00 SERGEOMIN Bolivia
Silala Norte
Canal Norte Spring N/A 7,9 207 8,95 9,47 12,8 6,43 N/A N/A 25,8 2,9 131,76 -9,7
sept-
00 SERGEOMIN Bolivia Silala Sur Pozo Groundwater N/A 7,7 124 7,16 11,11 6,6 1,82 N/A N/A 20 1,9 69,93 -12,2
oct-00 SERGEOMIN Bolivia Silala Norte Pozo Groundwater N/A 8,35 95 7,16 4,12 6,4 1,7 N/A N/A 15 2 50,02 5,0
nov-
00 SERGEOMIN Bolivia
Silala Norte
Vertiente Spring N/A 7,4 96 7,1 9,05 5,4 2 N/A N/A 18 2 56,12 -3,1
dic-00 SERGEOMIN Bolivia
Silala Norte
Vertiente Spring N/A 7,7 120 7,16 9,47 6,4 1,82 N/A N/A 23 2 75,03 -6,8
ene-
01 SERGEOMIN Bolivia
Silala Sur
Bofedal Spring N/A 7,5 340 7,16 13,99 25,4 13,71 N/A N/A 30 5,1 218,99 -6,2
feb-01 SERGEOMIN Bolivia Silala Sur Pozo Groundwater N/A 7,55 237 7,52 11,94 11,4 4,12 N/A N/A 29 3,1 150,06 -25,9
nov-
17 SERGEOMIN Bolivia
DS-24P 7.2-8.2
m* Groundwater 13,9 8,94 104,7 4,6 13,47 8,65 1,13 1,71 17,5 9,26 1,36 91,622 -67,3
nov-
17 SERGEOMIN Bolivia DS-4S 5-10 m* Groundwater 12,9 8,81 249 7,54 10,36 17,85 4,26 3,29 0,93 20,87 2,05 93,818 8,8
nov-
17 SERGEOMIN Bolivia DS-8 8.7-14.8 m* Groundwater 12,7 8,8 293 11,41 12,74 20,09 9,93 4,89 22,73 25,78 2,35 92,72 31,6
nov-
17 SERGEOMIN Bolivia DS-24S 2-4 m* Groundwater 12,6 8,64 132,6 7,67 19,46 8,53 3,97 2,5 18,26 12,8 1,26 30,378 14,7
Table F1. Presentation of the chemical data from Bolivian lake, spring and well samples contained in DHI (2018)
and cited in this report.
Annex XI Appendix F
68
60
APPENDIX G
Table G1. Tritium and 14C data presented by DHI (2018) and cited in this report
(BCM, Vol. 4, p. 92).
Annex XI Appendix G
Table 14 Tritium and 14C results (Sergeotecmin, 2005 (Bolivian) and Arcadis, 2017 (Chilean)).
Date 3H (UT) 14C (pMC) Reported Apparent
Age (years)
Bolivian collected test results
Site 2: Southern Wetland Up- 0±0.13 25.67±0.26 10,950±80·
Gradient
Site 4: Intermediate Site 0±0.13 30.67±0.27 9 ,490±70·
Site 6: Northern Wetland 0±0.14 86.29±0.83 1,180±80
Annex XII
Herrera, C. and Aravena, R., 2019. Chemical
Characterization of Surface Water and Groundwater
of the Quebrada Negra, Second Region, Chile
69
70
Annex XII
71
CHEMICAL CHARACTERIZATION OF SURFACE WATER AND
GROUNDWATER OF THE QUEBRADA NEGRA, SECOND REGION, CHILE
Christian Herrera (PhD)
Associate Professor, Universidad Católica del Norte
Ramón Aravena (PhD)
Emeritus and Adjunct Professor, University of Waterloo
January 2019
72
Annex XII
GLOSSARY
Alkalinity: The name given to the quantitative capacity of an aqueous solution to
neutralize an acid.
Anion: An ionic species, with a net negative charge.
Cation: An ionic species, with a net positive charge.
Headwater: A tributary stream of a river, close to or forming part of its source.
Hydrochemical: Dealing with the chemical characteristics of bodies of water.
Ion: An atom or molecule with a net electrical charge due to the gain or loss of one or
more electrons.
Ion chromatography: A chromatography process that separates ions and polar
molecules based on their affinity to an ion exchanger.
Plasma emission spectrometry: An analytical technique used for the detection of trace
elements. It is a type of emission spectroscopy that uses the inductively coupled plasma
to produce excited atoms and ions that emit electromagnetic radiation at wavelengths
characteristic of a particular element.
Recharge: Groundwater recharge (or deep drainage or deep percolation) is a hydrologic
process whereby water that has infiltrated the surface moves downward from the
unsaturated zone to groundwater. Recharge is the primary method through which water
enters an aquifer. Its source can be precipitation or surface water.
Salinity: The concentration of dissolved salts in water.
Annex XII
73
TABLE OF CONTENTS
1. INTRODUCTION.....................................................................................................1
2. LOCATION OF THE INVESTIGATED AREA......................................................1
3. OBJECTIVE OF THE REPORT...............................................................................1
4. METHODOLOGY....................................................................................................2
5. GEOCHEMISTRY....................................................................................................4
6. CONCLUSIONS .......................................................................................................7
7. REFERENCES ..........................................................................................................8
74
Annex XII
Annex XII
75
1
1. INTRODUCTION
The National Director of the Dirección Nacional de Fronteras y Límites del Estado
(DIFROL) of the Ministry of Foreign Affairs, Mrs. Ximena Fuentes, requested a study
concerning the hydrochemical characterization of the Quebrada Negra area located in
the transboundary basin of the Silala River in the northern region of Chile, as part of a
study aimed at deepening the hydrogeological knowledge of this basin.
The study of the chemical evolution of surface and groundwater in the Quebrada Negra
area can contribute to the understanding of the complex interaction between the surface
waters and the groundwater and mechanisms of local and regional recharge to the river
flow. In this context, the hydrogeochemical study of groundwater has been an important
approach to understand the flow of groundwater and to validate or discard hypotheses
about the conceptual understanding of the hydrogeology. This report was elaborated
under the supervision and instruction of Professors Howard Wheater and Denis Peach.
2. LOCATION OF THE INVESTIGATED AREA
The Quebrada Negra area is a major ephemeral tributary of the Silala River
transboundary watershed in Chile (Figure 1 and Figure 2), which reaches the Silala
River from the southeast, some 1700 metres downstream from the international border.
The headwaters of the Silala River are located above 4300 m.a.s.l. in Bolivian territory
where the perennial river flow originates from two wetland areas, the Cajones ravine
and the Orientales area, which are fed by groundwater from many springs. After the
river enters a ravine it crosses into Chilean territory.
3. OBJECTIVE OF THE REPORT
The main objective of this report is to characterize the chemical composition of the
surface waters and groundwater of the Quebrada Negra area in the Silala River basin.
This information will be used to complement the analysis of the data collected in the
Quebrada Negra as part of the study, “Chemical and isotopic characterization of
surface water and groundwater of the Silala River transboundary basin, Second Region,
Chile” (Herrera and Aravena, 2019).
76
Annex XII
2
4. METHODOLOGY
For the hydrogeochemical characterization of the waters of the Quebrada Negra, 7
samples of surface water (surface runoff) and groundwater were collected in the study
area during November 2018. Groundwater samples were obtained in shallow
piezometers from 1 to 2.5 metres deep. The location of the sampling points can be
found in Figures 1 and 2.
The chemical analysis included major cations and anions. The anions were determined
by ion chromatography (chloride, sulfate, nitrate) (Cl-, SO4
2-, NO3-) and volumetric
titration (bicarbonate) (HCO3-), and cations (sodium, potassium, calcium, magnesium)
(Na+, K+, Ca2+, Mg2+) by plasma emission spectrometry (ICP-OES). The hydrochemical
data presented in Stiff diagrams correspond to those with better analytical quality. To
evaluate the quality of the chemical analyzes the ionic balance was carried out for all
samples, where the sum of milliequivalents of anions must be practically equal to the
amount of milliequivalents of cations. This condition is checked considering the ionic
contributions of the majority elements calculating the balance error by the following
formula (Custodio and Llamas, 1983):
In general, samples with balance errors greater than those permitted are discarded for
comparison with other samples and/or analysis dates. The errors allowed (in absolute
value) are generally up to a maximum of 10%, although sometimes for very dilute
waters, with electrical conductivities (EC) of less than 200 μS/cm, slightly higher errors
can be accepted.
L cations - I anions
error(%) = ZOO x L cations+ I anions
Annex XII
77
3
Figure 1. Location map of the study area in the Silala River transboundary watershed.
Figure 2. The Quebrada Negra area in the Silala River basin showing the sampling location of
surface runoff, spring and groundwater.
0
0
SILALA RIVER BASIN
GROUNDWATER
CATCHMENT
/
~--R,as,f91a .
Quebrada/'
Negro
800 1600
Meters (J Mercator P/o;e.~ iOII, WGS &4
50 100
Meters
MercatorProje<lion. W6Sl4
150
68'01'5~ W
MIiitary
Post
..I
~SIio/a
Om
HitoS/N
Hito:b----""'"-
SIHXXV
,_/""
78
Annex XII
4
5. GEOCHEMISTRY
The chemical data for groundwater and surface runoff are presented in Table 1. These
data show a wide range in electrical conductivity (EC) values that vary between 249 and
450 μS/cm. The surface runoff samples with EC values of 249 and 262 μS/cm show the
lowest values, which are closer to the range of values for the Quebrada Negra spring
SP-SI-10, ranging between 290 (rainy season) and 379 μS/cm (dry season) (Herrera and
Aravena, 2019). The waters of the deep piezometers tend to have the highest EC values.
The value of 450 μS/cm is very close to EC values of groundwater of wells in other
regions of the Chilean and Bolivian sector of the Silala River topographic catchment
(Herrera and Aravena, 2019).
The waters are mainly Ca-Na-Bicarbonate type (Figure 3), like the chemical
composition, for the rainy season, of the spring sample SP-SI-10-17 analyzed in the
previous study (Herrera and Aravena, 2019), however there is one groundwater and one
surface runoff water sample that is Na-Ca-Bicarbonate. The chemical composition of
the Quebrada Negra waters tends to be similar to the springs in the Orientales area in
Bolivia and the groundwater in the Chilean sector (Figure 4).
One key difference between the Quebrada Negra spring and the other springs in the
Silala River basin in the Chilean sector is its relative higher magnesium (Mg) content.
Mg is the second most abundant cation in the more saline groundwater (16 F-D) in the
Quebrada Negra (Table 1 and Figure 3). Based on a relative increase in the Mg content
in the river down-gradient from the intersection of the Quebrada Negra with the Silala
River, it was postulated that this pattern was related to the input of water from the
Quebrada Negra (Herrera and Aravena, 2019). The additional chemical data collected in
the Quebrada Negra supports this hypothesis.
One of the characteristics of the Quebrada Negra water in the present study is the
bicarbonate content, which as mentioned above is much higher in two of the waters
analyzed than that in the waters that have been analyzed in the other regions of the
Chilean and Bolivian sector of the Silala River topographic basin. It was postulated
(Herrera and Aravena, 2019) that part of the bicarbonate in the groundwater in the Silala
River catchment could be associated to a contribution of volcanic CO2.
Annex XII
79
5
Sample
ID Date
Coordinates
Hour Water
Type
pH
lab Depth T °C EC Lab
uS/cm
Alkalini
ty
mg/L of
CaCO3
Cl
mg/L
SO4
mg/L
HCO
3
mg/L
Ca
mg/L
Mg
mg/L
K
mg/L
Si
mg/L
Na
mg/L
NO
3
mg/
L
x Y
22 S 16-11-
2018
599931.84 7563358.63 14:20 Piezometer 6.99 1.07 21.3 332 150 2.41 0.38 193.9 23.32 11.101 13.158 30.61 21.63 0.5
11 F 16-11-
2018
600022.35 7563348.83 15:07 Surface
runoff
6.71 19.3 262 120 1.46 10.45 145.1 19.27 8.404 7.599 31.4 17.88 <
0.5
14 Z 16-11-
2018
600006.51 7563323.11 15:33 Surface
runoff
7.21 20.4 249 144 2.1 14.9 123.1 19.32 7.966 7.76 37.27 15.79 <
0.5
16 S-D 16-11-
2018
599998.85 7563333.92 16:47 Piezometer 6.7 2.31 10.9 450 226 1.44 2.74 285.3 38.3 14.895 16.06 16.25 19.89 <
0.5
16 S-S 16-11-
2018
599998.85 7563333.92 16:40 Piezometer 6.53 0.81 10.8 290 147 1.01 5.34 173.1 21.7 9.669 9.889 30.42 17.13 <
0.5
16 F-D 16-11-
2018
599999.69 7563348.95 17:11 Piezometer 6.61 2.03 7.3 378 217 0.92 28.86 302.4 56.37 17.356 13.226 35.1 16.63 <
0.5
16 F-S 16-11-
2018
599999.69 7563348.95 17:41 Piezometer 6.83 0.85 11.6 343 218 0.74 0.5 215.8 29.89 11.883 12.44 40.29 17.98 <
0.5
Table 1. Location and chemical data of the water in the Quebrada Negra. The letter “D” indicates “deep” and “S” stands for “shallow” level, as
defined by Muñoz and Suárez (2019).
80
Annex XII
6
Figure 3. Modified Stiff diagrams of the waters in the Quebrada Negra including the spring
water sample SP-SI-10-17 (rainy season) (Herrera and Aravena, 2019).
Figure 4. Modified Stiff diagrams of the waters of Silala River topographic basin (see Figure 8
from Herrera and Aravena (2019) with the Quebrada Negra samples from Table 1 (this report)
included).
Cl
so 4
3 meq i 3 meq HCO,
.,,--800 1600
( Meterf
Me rcator Projec' tion, WGS 84
Sample sites
♦ Springs
• Wells
■ Surface runoff
s1'.1
OS-24P
0S-245
SI- I . ---. ~ !\toles
ca·o ( O' 1
1,7
.)
I
I
\
Na
Mg
Ca
SCALE
3 meq i 3 meq
Sample sites
• Springs
• Wells
6 River
Cl
so.
HCO
■ Surface runoff
'
Annex XII
81
7
6. CONCLUSIONS
A wide range in salinity is observed in the Quebrada Negra waters. Some of these
waters tend to be more saline than surface and groundwater analyzed in the Chilean and
Bolivian sectors of the Silala River basin, whereas others are similar in salinity. This
wide range in salinity observed in this small area is likely to reflect a complex
interaction between deep and shallow groundwater flow systems, suggesting that the
waters are varying mixtures of two different groundwater systems. The higher salinity
and high bicarbonate of these waters is likely to be associated with discharge of a
regional groundwater flow system, whereas the lower salinity, lower bicarbonate waters
suggest a closer association with a local flow system. Hydraulic head measurements in
some of the piezometers (Muñoz and Suárez, 2019) show an upward gradient indicating
a potential for groundwater discharge from a deeper flow system. The existence of
faults in this area could explain discharge of a more saline groundwater from a deeper
regional groundwater flow system. The low salinity water represented by the spring
sample SP-SI-10-17 (see Figure 4) and one of the surface runoff water samples in the
Quebrada Negra could well correspond to the discharge of a shallow groundwater flow
system.
The new chemical data in the Quebrada Negra agree with previous data from the spring
SP-SI-10 which showed that this water has relatively more Mg than the springs and the
Silala River in the Chilean sector of the catchment. This finding supports the hypothesis
of a contribution of the Quebrada Negra to the Silala River based on relative changes in
Mg in the river between up and down gradient of the intersection of the Silala River
with the Quebrada Negra.
82
Annex XII
8
7. REFERENCES
Custodio, E. and Llamas, M.R., 1983. Hidrología subterránea. Omega. Barcelona.
Muñoz, J.F. and Suárez, F., 2019. Quebrada Negra Wetland Study. (Chile’s Reply,
Vol. 3, Annex XIII).
Herrera, C. and Aravena, R., 2019. Chemical and isotopic characterization of surface
water and groundwater of the Silala River transboundary basin, Second Region, Chile.
(Chile’s Reply, Vol. 3, Annex XI).
Annex XIII
Muñoz, J.F. and Suárez, F., 2019. Quebrada Negra Wetland Study
83
84
Annex XIII
85
QUEBRADA NEGRA WETLAND STUDY
José Francisco Muñoz (PhD)
Professor, Pontificia Universidad Católica de Chile
Francisco Suárez (PhD)
Associate Professor, Pontificia Universidad Católica de Chile
Assistants:
María José Fuenzalida, Civil Engineer
Magdalena Lagos, Civil Engineer, MSc
Magdalena Mendoza, Civil Engineer
Tomás Oportus, Civil Engineer
Andrés Pereira, Civil Engineer, MSc
Pedro Sanzana, Civil Engineer, MSc, PhD
Andrés Sarabia, Civil Engineer, MSc
Fernanda Stegmaier, Civil Engineer
January 2019
86
Annex XIII
GLOSSARY
This glossary of hydrological terms is based on the following:
• http://www.wmo.int/pages/prog/hwrp/publications/international_glossary/…
_2012.pdf
• http://www.nws.noaa.gov/om/hod/SHManual/SHMan014_glossary.htm
• http://www.geo.utexas.edu/faculty/jmsharp/sharp-glossary.pdf
Conductivity: Hydraulic Conductivity is a property of a porous medium which,
according to Darcy’s law, relates the specific discharge to the hydraulic gradient.
Discharge: Volume of water flowing per unit time, for example through a river crosssection
or from a spring or a well.
Evaporation: Process by which water changes from liquid to vapour.
Evapotranspiration: Combination of evaporation from free water surfaces and
transpiration of water from plant surfaces to the atmosphere.
Gauge: (verb) To estimate an amount by using a measuring device.
Groundwater: Subsurface water occupying the saturated zone (i.e. where the pore
spaces (or open fractures) of a porous medium are full of water).
Landsat: Group of satellites built and placed in orbit by the USA for high-resolution
observation of the Earth’s surface.
Net Radiation: Difference between incident and reflected radiation.
Normalized Difference Vegetation Index: Indicator that can be used to analyze
remote sensing measurements and assess whether the target being observed contains
live green vegetation or not.
Penman-Monteith Approach: Method for estimating evapotranspiration.
Psychometric Constant: Constant that relates the partial pressure of water in air to the
air temperature.
River Basin: Area having a common outlet for its surface runoff.
Spring: Place where groundwater emerges naturally from the rock or soil.
Soil Heat Flux Density: Heat flux entering the ground per unit area.
Annex XIII
87
Wells: Any artificial excavation or borehole constructed with the aim of either
exploring for or producing groundwater, or injection, monitoring or dewatering
purposes.
Wetland: Areas under or contiguous to open water or with a shallow water table,
including swamps, marshes, bogs, wet meadows, river overflows, mud flats, and natural
ponds. Wetlands are typically characterized by water-loving vegetation (phreatophytes
or, in areas with brackish water, halophytes).
88
Annex XIII
Annex XIII
89
TABLE OF CONTENTS
1. INTRODUCTION ..................................................................................................... 1
1.1 Objective ............................................................................................................ 1
1.2 Summary of the methodology ............................................................................ 1
1.3 Structure of the report......................................................................................... 2
2. SUMMARY AND CONCLUSIONS ........................................................................ 2
3. STUDY AREA .......................................................................................................... 4
4. METHODS .............................................................................................................. 11
4.1 Quebrada Negra Wetland meteorological station ............................................ 11
4.1.1 Anemometer.................................................................................................. 14
4.1.2 Net radiometer .............................................................................................. 14
4.1.3 Tipping bucket rain gauge ............................................................................ 15
4.1.4 Ambient temperature and relative humidity probe ....................................... 15
4.1.5 Soil sensors ................................................................................................... 16
4.2 Spatial and temporal distribution of vegetation cover...................................... 18
4.2.1 Spatial distribution of vegetation cover ........................................................ 18
4.2.2 Temporal evolution of vegetation cover ....................................................... 20
4.3 Evapotranspiration estimations ........................................................................ 21
4.3.1 Potential evapotranspiration ......................................................................... 21
4.3.2 Spatial distribution of estimated actual evapotranspiration .......................... 21
4.4 Soil characterization ......................................................................................... 23
4.4.1 Field campaign to determine peat depth, describe soil particle
distribution and permeability ........................................................................ 23
4.4.2 Field saturated hydraulic conductivity .......................................................... 35
4.4.3 Thermal properties ........................................................................................ 37
4.5 Groundwater level monitoring ......................................................................... 37
4.5.1 Monitoring network ...................................................................................... 37
4.5.2 Ground water level measurements ................................................................ 44
5. RESULTS AND DISCUSSION .............................................................................. 44
90
Annex XIII
5.1 Quebrada Negra Wetland meteorological station ............................................ 45
5.1.1 Air temperature ............................................................................................. 45
5.1.2 Precipitation .................................................................................................. 45
5.1.3 Relative Humidity ......................................................................................... 46
5.1.4 Wind speed and Wind direction.................................................................... 47
5.1.5 Net radiation ................................................................................................. 48
5.1.6 Soil heat flux ................................................................................................. 49
5.2 Spatial and temporal distribution of vegetation cover...................................... 49
5.2.1 Spatial distribution of vegetation cover ........................................................ 49
5.2.2 Temporal evolution of vegetation cover ....................................................... 55
5.3 Evapotranspiration estimates ............................................................................ 61
5.3.1 Potential evapotranspiration ......................................................................... 61
5.3.2 Spatial distribution of estimated actual evapotranspiration .......................... 61
5.4 Soil characterization ......................................................................................... 64
5.4.1 Peat depth determination .............................................................................. 64
5.4.2 Soil particle distribution................................................................................ 64
5.4.3 Falling-head Permeability Test results ......................................................... 67
5.4.4 Field saturated hydraulic conductivity .......................................................... 68
5.4.5 Thermal properties ........................................................................................ 73
5.5 Groundwater level monitoring ......................................................................... 73
5.5.1 Spatial interpolation ...................................................................................... 73
5.5.2 Groundwater profiles .................................................................................... 77
5.5.3 Continuous monitoring records .................................................................... 80
5.5.4 Discussion ..................................................................................................... 80
6. CONCLUSIONS...................................................................................................... 82
7. REFERENCES ........................................................................................................ 85
APPENDIX A ................................................................................................................. 88
APPENDIX B ................................................................................................................. 91
APPENDIX C ................................................................................................................. 94
APPENDIX D ................................................................................................................. 95
Annex XIII
91
1
1. INTRODUCTION
The National Director of the Dirección Nacional de Fronteras y Límites del Estado
(DIFROL) of the Ministry of Foreign Affairs of Chile, Mrs. Ximena Fuentes, requested
professors José Francisco Muñoz and Francisco Suárez to perform hydrological studies
of the Quebrada Negra wetland, which is within the Silala River basin.
This final report describes the field work, data analysis and results obtained from a
monitoring programme developed for the Quebrada Negra wetland, which is an
undisturbed wetland located within the Silala topographic catchment in Chile, of
comparable nature and areal extent to the Bolivian Cajones and Orientales wetlands.
The characterization of this wetland will help to understand the hydrological and
hydrogeological processes that are occurring in the various wetlands located in the
headwaters of the basin. In addition, satellite products were used to compare vegetation
activity and evaporation rates from the Quebrada Negra with the Cajones and Orientales
wetlands. This study was led by Drs. José Francisco Muñoz and Francisco Suárez,
under the supervision and instruction of Drs. Howard Wheater and Denis Peach.
1.1 Objective
The objective of this work is to characterize the Quebrada Negra wetland by: (1)
measuring meteorological variables, with the aim of determining potential evaporation;
(2) characterizing the vegetation cover in the Quebrada Negra, Cajones and Orientales
wetlands using satellite products; (3) estimating actual evapotranspiration in the
Quebrada Negra, Cajones and Orientales wetlands using satellite products; (4)
characterizing the main soil properties (soil particle distribution, hydraulic conductivity
and thermal properties); and (5) measuring groundwater levels, to characterize the
groundwater-surface water interactions. The collection of these data will thus help in
understanding the hydrological functioning of the Quebrada Negra wetland and its
water balance.
1.2 Summary of the methodology
The main activities of this work can be separated into five main groups: (1) activities
related to the analysis of meteorological data to estimate potential evapotranspiration in
the Quebrada Negra wetland; (2) activities related to the spatial and temporal
characterization of the vegetation cover in the Quebrada Negra, Cajones and Orientales
wetlands using satellite products; (3) activities related to the estimation of actual
evapotranspiration in the Quebrada Negra, Cajones and Orientales wetlands using
satellite products; (4) activities related to soil characterization; and (5) activities related
to groundwater level monitoring.
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Annex XIII
2
Activities of the first group include: deployment of a meteorological station with soil
sensors to measure necessary variables for energy balance and potential
evapotranspiration estimation using the Penman-Monteith equation (Allen et al., 1998).
Activities of the second and third group consider the use of satellite images to estimate
spatial and temporal distribution of vegetation cover in the Quebrada Negra, Cajones
and Orientales wetlands, and to estimate actual evapotranspiration in those wetlands
using a vegetation index (Groeneveld et al., 2007).
Activities of the fourth group include: a field campaign in which peat depth was
determined and soil samples were collected to determine soil particle distribution and
hydraulic conductivity with a falling head permeameter; execution of slug tests at
selected monitoring points to determine the field hydraulic properties of the wetland
deposits by using the Cooper et al. model (Cooper et al.,1967).
Activities of the fifth group consider the following: construction of a network of 82
monitoring points consisting of pairs of piezometers; field campaigns to measure the
water levels at each well with a water level dipper; and continuous water level
measurements at 5 monitoring points distributed inside the main wetland area, using
pressure transducers.
1.3 Structure of the report
The structure of the remainder of this report is as follows: Chapter 2 provides a
summary and the conclusions of the study; Chapter 3 describes the study area; Chapter
4 depicts the methods used in this study; Chapter 5 describes the main results; Chapter 6
presents the main conclusions; and Chapter 7 lists the references cited in this report.
2. SUMMARY AND CONCLUSIONS
In this study, during the transition from winter to spring (June to November 2018), the
meteorological conditions, the vegetation cover and the groundwater levels of the
Quebrada Negra wetland (Chile) were captured and analyzed. The vegetation cover of
the Cajones and Orientales wetlands (Bolivia) was also analyzed. The results include a
detailed meteorological description of the Quebrada Negra to estimate potential
evapotranspiration; the spatial (July to November 2018) and temporal (January 1986 to
April 2017) distribution of vegetation cover of the Quebrada Negra, Cajones and
Orientales wetlands; and measurements of groundwater level in the Quebrada Negra
wetland from August to October 2018.
Annex XIII
93
3
To analyze the spatial distribution and the temporal evolution of the vegetation cover in
the three wetlands mentioned above, Sentinel-2 and Landsat images were used. NDVI
images were obtained for each of three wetlands. The high-resolution (10 m) Sentinel-2
data set was used to analyze the spatial distribution of the vegetation cover (July to
November 2018), and the coarser resolution (30 m) LANDSAT product series was used
to analyze its temporal evolution (January 1986 to April 2017).
Sentinel-2 NDVI data show, for each of the three wetlands, that the vegetation covers
the whole of the available flat valley bottom area and extends up the adjacent hillslopes
where slopes are less than approximately 15%. The maximum observed area of
vegetation cover in Quebrada Negra was 4.12 ha in October 2018 and the mean area
was 2.9 ha. Although the total area covered by vegetation changed, the extent of the
vegetation cover in a studied lateral cross section did not vary. However, an increase in
vegetation cover in the Quebrada Negra wetland during the studied period was observed
in river cross sections located downstream and upstream of the studied cross section,
where the width of vegetation cover increased in the north-south direction.
Monthly vegetation cover over the period 1986-2017 from LANDSAT data shows that
vegetation cover peaks between April and May and there is strong variability for all the
sites, especially in the Cajones wetland, during the December-May period. Vegetation
coverage increased from July to December 2018 as seen from the Sentinel-2 images,
which is consistent with the historical average variation curves (1986-2017) obtained by
the LANDSAT images. Nevertheless, the values obtained from Sentinel and LANDSAT
products are not directly comparable as the latter are less accurate. However,
LANDSAT presents a longer period over which imagery is offered and therefore,
allows for more years to be considered in the analysis.
Actual evapotranspiration was estimated using the Groeneveld et al. method
(Groeneveld et al., 2007) at the annual time scale. This method was developed to
estimate actual evaporation using remotely sensed NDVI data, for arid and semi-arid
areas where evaporation is dominated by vegetation fed by shallow groundwater
sources. The estimates of annual actual evapotranspiration showed that the highest
annual value was observed in the Cajones wetland and the lowest in the Quebrada
Negra wetland.
Two pits were excavated in the Quebrada Negra wetland, where a high content of
organic material was found. For this reason, particle distribution tests could not be
performed for all of the samples obtained. Saturated hydraulic conductivity of the peat
present in the Quebrada Negra wetland was measured and estimated in the laboratory
using a falling head permeameter and in the field with slug tests, with good agreement,
showing relatively low permeabilities. Although measured hydraulic conductivities
94
Annex XIII
4
show that the soil is semi-pervious to impervious, during the excavation of the pits, they
needed to be constantly drained, because of water ingress.
The Quebrada Negra wetland exists because it is fed by groundwater. However,
groundwater levels show a complex and spatially heterogeneous behavior. In much of
the main wetland area, the vertical hydraulic gradient is mostly close to zero and
dominated by downwelling gradients. Upwelling occurs at specific locations within the
wetland, and there is evidence of spring emergence close to the base of the adjacent
lateral hillslopes, at the upstream boundary of the wetland area, and there are upwelling
gradients in the downslope ravine. Groundwater emerges within the main wetland,
flows through distinct surface channels and re-infiltrates. The groundwater levels in the
Quebrada Negra wetland show that there is an overall groundwater gradient parallel to
the topographic gradient in the downhill direction towards the Silala ravine, i.e., the
Quebrada Negra hydrogeological system feeds the Silala River system. This connection
between the waters of the Quebrada Negra and the Silala hydrogeological systems is
also supported by the geochemical analyses performed by Herrera and Aravena (Herrera
and Aravena, 2019(a) and 2019(b)). They found high concentrations of Magnesium in
the Quebrada Negra wetland as well as in the Silala River downstream of the junction of
the two ravines. Therefore, there is a strong connection between these two
hydrogeological systems.
3. STUDY AREA
The study area is the Silala River basin, a transboundary watershed shared by Bolivia
(upstream) and Chile (downstream). The Silala River basin is located in the Andean
Plateau of the Atacama Desert, approximately 300 km northeast of Antofagasta. The
Silala River originates in Bolivian territory and flows towards the Antofagasta Region
in Chilean territory (Figure 3-1). The Silala River is one of the main tributaries of the
San Pedro de Inacaliri River, which in turn is a tributary of the Loa River. The Loa
River is the longest Chilean river (440 km long) and the main watercourse in the
Atacama Desert. It drains to the Pacific Ocean where its outlet is located at latitude
21°26’ S.
Annex XIII
95
5
Figure 3-1. The Loa River and its main tributaries. The Silala River topographic catchment
(delineated in black) and groundwater catchment (delineated in green) are also shown.
The Quebrada Negra wetland is a densely vegetated area of approximately 30,000 m2
(3 ha) on average (over the measurement period of June 2018 to November 2018),
which has developed in the Quebrada Negra ravine, at ~4200 m.a.s.l. (Figure 3-2).
Under the present climate, the Quebrada Negra ravine does not have a significant
21 S
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96
Annex XIII
6
perennial surface flow, but geochemical analysis suggests that there is a strong
connection between its waters and the Silala River waters downstream of the junction
with the Quebrada Negra ravine (Herrera and Aravena, 2019(b)). These authors show
high concentrations of Magnesium in the Quebrada Negra wetland as well as in the
Silala River downstream of the Quebrada Negra confluence. The Quebrada Negra
wetland exhibits a green vegetation cover over almost the entire extent of the wetland,
as shown in Figure 3-3 to Figure 3-6. Small surface flow networks are observed to occur
extensively in the wetland (Figure 3-5), where spring flows emerge, flow overland in
inter-connected natural networks of surface channels, and subsequently infiltrate. Some
of the springs that feed the wetland emerge at the base of the rocky slopes that border
the wetland, which is evidenced by vegetation growing at or towards the base of the
hillslopes (Figures 3-3, 3-5 and 3-6) particularly on the southern side of the ravine.
Downstream of the wetland, an ephemeral stream has been observed. The spatial extent
of this streamflow changes with the season, but at least since October 2016 has never
reached the Silala River.
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7
Figure 3-2. Location of the Quebrada Negra wetland.
Figure 3-3. Photograph of the Quebrada Negra wetland (taken from the northern slope).
S/LALA RIVER BASIN
GROUNDWATER
CATCHMENT
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0c ====800i====16c0:0:====:::;2400 (r Meters
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98
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Figure 3-4. Photograph of the Quebrada Negra wetland (taken from the southern slope).
Figure 3-5. Photograph taken at the Quebrada Negra wetland (looking upstream).
Figure 3-6. Photograph taken at the Quebrada Negra wetland (looking downstream).
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An unmanned aerial vehicle (UAV) was used to take pictures from ~100 metres height
to build a more detailed map of the study site and its surroundings, to determine the
topography, and to be able to work using a GIS platform. Figure 3-7 to Figure 3-9 show
some of the pictures taken and Figure 3-10 presents a three-dimensional surface model
produced from the image analysis.
Figure 3-7. Photograph of Quebrada Negra wetland meteorological station (QWS) site with
fence.
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Figure 3-8. Photograph of the Quebrada Negra wetland (main wetland area).
Figure 3-9. Photograph of the Quebrada Negra wetland and river bank.
Meters
PSAD56 /UTM zone19S
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Figure 3-10. Three-dimensional surface model produced from image analysis, Quebrada Negra
wetland.
4. METHODS
This section presents the methods used to investigate the Quebrada Negra wetland.
First, a description of the Quebrada Negra Wetland meteorological station is provided
(4.1). Then, the methods utilized to investigate the spatial and temporal distribution of
the vegetation cover of the Quebrada Negra wetland are described. This methodology
will also be applied to understand the temporal dynamics of the vegetation cover in both
Cajones and Orientales (Bolivia) wetlands (4.2). Later, the methods used to investigate
evapotranspiration processes in the wetland are presented (4.3). Next, the approach
utilized to characterize the soils of the wetland is described (4.4). Finally, a description
of the groundwater monitoring network is provided (4.5).
4.1 Quebrada Negra Wetland meteorological station
A meteorological station was installed in the Quebrada Negra wetland to monitor
various environmental variables. Table 4-1 shows a list of components of the station,
Figure 4-1 shows the deployment of the station and Figure 4-2 shows the heights above
ground level of the different components of the station. The data provided by these
components are being collected every 15 minutes. A Broadband Global Area Net
(BGAN) module was added on 29 August and allows satellite transmission of the data
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that can be accessed remotely through the internet. A data gap exists between 21 and
29 August that was due to a technical issue when installing the satellite transmission.
Instrument Model Manufacturer Quantity
Weather-Resistant Enclosure, 16 x 18
inches ENC16/18 Campbell Sci. 1
Datalogger CR1000X Campbell Sci. 1
16- or 32-Channel Relay Multiplexer AM16/32B Campbell Sci. 1
12V Power Supply with Charging
Regulator and 7Ah Rechargeable
Battery
PS200 Campbell Sci. 1
Propeller anemometer 05103 R.M. Young 1
Pressure transducer U20L-04 Onset HOBO 1
Ambient temperature and relative
humidity probe CS215 Campbell Sci. 1
Tipping bucket rain gauge TE525WS Texas
Electronics 1
Averaging soil thermocouple probe TCAV Campbell Sci. 1
Self-calibrating soil heat flux plate HFP01SC Hukseflux 2
Soil water content reflectometer CS655 Campbell Sci. 1
4-Component net radiometer CNR4 Kipp & Zonen 1
Broadband Global Area Net (BGAN) - - 1
Table 4-1. List of components of the Quebrada Negra Wetland meteorological station.
Additionally, MODIS satellite images were used to identify snowfall events. The
MODIS snow algorithm output contains scientific data sets of snow cover, quality
assurance, local attributes and global attributes (Hall et al., 2006). The temporal
distribution of the snow cover in the Silala River basin was generated considering the
same reported period as for the monitoring stations.
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13
Figure 4-1. Deployment of the Quebrada Negra Wetland meteorological station.
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Figure 4-2. Heights above ground level of the different components of the Quebrada Negra
Wetland meteorological station.
4.1.1 Anemometer
Measurements of wind speed are required at 2 metres height to obtain evaporation
estimates using the FAO Penman-Monteith equation (Allen et al., 1998). The tallest
element of the station must be the lightning rod, so the anemometer was installed on a
cross-arm, secured to the ground and connected with a nu-rail to the cross-arm
supporting the net radiometer to improve stability of the installation (Figure 4-1). The
orientation of the sensor is such that north direction is recorded as zero degrees.
4.1.2 Net radiometer
The net radiometer was mounted on a cross-arm with the included nu-rail. The sensor is
pointing towards the North. The elevation with respect to the ground is 160 centimetres
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(Figure 4-2), in agreement with manufacturer recommendations (of at least 150
centimetres).
4.1.3 Tipping bucket rain gauge
A 2 metres length 1.25-inch steel pipe was inserted 1 metre into the ground to support
the tipping bucket. The steel pipe was located as far from the central mast as the tipping
bucket’s cable length allowed, to minimize potential interference from other structures.
The tipping bucket was installed so that the rim is at least 5 centimetres above the pipe.
The height to the rim is 118 centimetres (Figure 4-2), which is within typical values
reported by the World Meteorological Organization (WMO), which recommends
installing the tipping bucket between 0.5 and 1.5 metres above ground level (WMO,
2014). The tipping bucket cannot be installed at a lower height as the installation of a
snowfall adapter is required and the gauge must stand above any snowpack. The total
height of the tipping bucket with snowfall adapter is ~90 centimetres. The distance to
the closest obstruction is greater than twice the difference in height, in agreement with
WMO recommendations (WMO, 2014).
The cables from the tipping bucket, solar panel and soil sensors were buried to prevent
rodent damage (Figure 4-3).
Figure 4-3. Solar panel, tipping bucket and buried cables of the Quebrada Negra Wetland
meteorological station.
4.1.4 Ambient temperature and relative humidity probe
The ambient temperature and relative humidity probe was installed inside the solar
radiation shield at 170 centimetres above the ground (Figure 4-2). This height is within
the range recommended by the WMO (WMO, 2014).
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4.1.5 Soil sensors
The array of soil sensors consists of two self-calibrating soil heat flux plates
(HFP01SC), an averaging soil thermocouple probe (TCAV) and a water content
reflectometer (CS655). These sensors were deployed as depicted in Figure 4-4.
Figure 4-4. Soil sensors layout.
Figure 4-5 shows a photograph of the installation of the soil heat flux plate. If the 12
centimetres mark in the measuring tape is considered the ground surface, it can be seen
that the soil heat flux plate is located at 12 centimetres depth (0 centimetre mark), as
shown in Figure 4-4.
--- Up\o"\m
6cm
CSS55 6 .5cm
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Figure 4-5. Soil heat flux plate installation.
During installation, the hole became flooded relatively quickly and soon the soil heat
flux plates were completely submerged. Figure 4-6 shows the final conditions of the
array of sensors installed, with the soil heat flux plates under water.
Figure 4-6. Soil sensors at the Quebrada Negra Wetland meteorological station.
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4.2 Spatial and temporal distribution of vegetation cover
The Normalized Difference Vegetation Index (NDVI) is an indicator of vegetation vigor
and it is calculated from satellite data using the red (R) and the near-infrared (NIR)
bands in the electromagnetic spectrum (Groeneveld and Baugh, 2007):
NDVI =
NIR − R
NIR + R
(1)
Since chlorophyll almost completely absorbs the red light and strongly reflects the NIR
portion of the spectrum, the difference between both bands is a strong indicator of the
health of vegetation (Groeneveld et al., 2007). The NDVI varies from -1.0 to 1.0, and
according to Alcayaga, low, positive NDVI values (between 0.2 and 0.4) represent
shrub and grassland (Alcayaga, 2017).
Two complimentary satellite products, Sentinel-2 (10 m resolution) and LANDSAT (30
m resolution), were used to compare the vegetation cover of the Quebrada Negra
wetland (in Chile) with the Orientales and Cajones wetlands (in Bolivia). Sentinel-2
satellite images are obtained every 5 days and LANDSAT images every 15 days.
Nevertheless, the values obtained from Sentinel-2 and LANDSAT products are not
directly comparable because the latter are less accurate. However, LANDSAT presents
a larger period over which imagery is offered and therefore allows for more years to be
considered in the analysis.
4.2.1 Spatial distribution of vegetation cover
For the analysis of spatial distribution of vegetation cover of the Quebrada Negra
(Chile), Cajones and Orientales (Bolivia) wetlands, monthly NDVI maps were
calculated for July, August, September, October and November 2018, using the optical
images provided by the Sentinel-2 mission (Table 4-2). Only images where no clouds in
the studied wetlands occurred were used. To generate the monthly averaged NDVI
maps, one NDVI map was generated for each sensed date, and these images were
averaged in time for each month.
The aim of the Sentinel-2 mission, developed by the European Space Agency, is to
monitor temporal variability in land surface conditions (due to its high revisit time), and
the data can be used at the study area to monitor changes in vegetation. The sensors on
Sentinel-2 satellites have 13 spectral bands; bands 4 and 8 are the R and NIR bands,
respectively (Zhu et al., 2015).
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Date Name
03/07/2018 S2A_MSIL1C_20180703T143751_N0206_R096_T19KER_20180703T180946
08/07/2018 S2B_MSIL1C_20180708T143749_N0206_R096_T19KER_20180708T191932
18/07/2018 S2B_MSIL1C_20180718T143749_N0206_R096_T19KER_20180718T192157
17/08/2018 S2B_MSIL1C_20180817T143739_N0206_R096_T19KER_20180817T192123
22/08/2018 S2A_MSIL1C_20180822T143751_N0206_R096_T19KER_20180822T192224
27/08/2018 S2B_MSIL1C_20180827T143739_N0206_R096_T19KER_20180827T192139
01/09/2018 S2A_MSIL1C_20180901T143741_N0206_R096_T19KER_20180901T182920
06/09/2018 S2B_MSIL1C_20180906T143739_N0206_R096_T19KER_20180906T195021
16/09/2018 S2B_MSIL1C_20180916T143739_N0206_R096_T19KER_20180916T192127
21/09/2018 S2A_MSIL1C_20180921T143741_N0206_R096_T19KER_20180921T181736
26/09/2018 S2B_MSIL1C_20180926T143739_N0206_R096_T19KER_20180926T200955
01/10/2018 S2A_MSIL1C_20181001T143741_N0206_R096_T19KER_20181001T181115
11/10/2018 S2A_MSIL1C_20181011T143751_N0206_R096_T19KER_20181011T181532
21/10/2018 S2A_MSIL1C_20181021T143751_N0206_R096_T19KER_20181021T180732
26/10/2018 S2B_MSIL1C_20181026T143749_N0206_R096_T19KER_20181026T192118
31/10/2018 S2A_MSIL1C_20181031T143751_N0206_R096_T19KER_20181103T085637
05/11/2018 S2B_MSIL1C_20181105T143749_N0206_R096_T19KER_20181105T192245
10/11/2018 S2A_MSIL1C_20181110T143751_N0207_R096_T19KER_20181110T181533
15/11/2018 S2B_MSIL1C_20181115T143749_N0207_R096_T19KER_20181115T182029
20/11/2018 S2A_MSIL1C_20181120T143751_N0207_R096_T19KER_20181120T181100
Table 4-2. Sentinel-2 images used to calculate monthly NDVI map.
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Before calculating the NDVI, the R and NIR bands were pre-processed and
atmospherically corrected by dark object subtraction (DOS). The DOS is based on the
assumption that within the image, there are some pixels in complete shadow and
therefore, the reflectance sensed by the satellite is due only to atmospheric scattering
(Chavez, 1996). This process was carried out using the Semi-Automatic Classification
Plugin from QGIS plugin (Congedo, 2018).
After the R and NIR bands were atmospherically corrected, the NDVI was calculated
for each Sentinel-2 image. The NDVI values of each pixel, for each month, were
averaged and NDVI maps for July, August, September, October and November 2018
were obtained.
To visualize where the vegetation cover is located within the terrain in each wetland, the
spatial distribution of vegetation estimated with the NDVI obtained from the Sentinel-2
images (averaged between July and November 2018) was combined with the
topographic information from a digital elevation model (AW3DTM). The topographical
information source was a Digital Elevation Model (DEM) with 5 m horizontal
resolution, acquired from the Advanced Land Observing Satellite (ALOS) Word 3D
Digital Terrain Model (NTT DATA and RESTEC, 2014).
Additionally, it is important to mention that the comparison of a cross section of
vegetation cover considers the period between June and November and hence the annual
maximum extent of vegetation cover is not included. The maximum extents of
vegetation cover occur between January and March. However, it is possible to show the
variation in the dynamics of the extent of vegetation coverage of the Cajones and
Orientales wetlands over the studied period, but for the Quebrada Negra wetland the
variation of spatial extent was less than the resolution of the sensor for the studied
period.
4.2.2 Temporal evolution of vegetation cover
The temporal evolution of the vegetation cover of the Quebrada Negra (Chile) and
Cajones and Orientales (Bolivia) wetlands was analyzed using the historical repository
of Landsat images (30 m resolution) for the period 1985-2017. To obtain this time
series, the Google Earth Engine platform (Gorelick et al., 2017) and the computational
tool developed by Sproles (Sproles et al., 2018) were used. The tool developed by
Sproles (Sproles et al., 2018) allows obtaining the snow cover area through the NDSI
values, and the script was modified for this study to derive the NDVI values (equation
(1)).
To obtain the time series of vegetation cover over Cajones, Orientales and Quebrada
Negra, we first filtered out the striped and distorted NDVI images every 8 days through
visual inspection (314 valid images remaining were considered). Different Landsat
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missions were considered: LANDSAT-5 between 1986-1999, LANDSAT-7 between
2000-2002 and between 2012-2013, LANDSAT-8 for 2014-2017.
4.3 Evapotranspiration estimation
Evapotranspiration (ET) is the combination of two separate processes that occur
simultaneously, whereby water is lost on the one hand from the soil surface by
evaporation and on the other hand from the crop (vegetation) by transpiration (i.e. due
to evaporation within the plant leaf). Soil evaporation is mainly determined by the
fraction of the solar radiation reaching the soil surface and the water availability.
Transpiration is mainly determined by the meteorological conditions, plant cover and
the water available to the plant root system (Allen et al., 1998).
4.3.1 Potential evapotranspiration
Potential evaporation (ETo) is the ET rate for a reference surface, normally a
hypothetical grass reference crop with specific characteristics (Allen et al., 1998). ETo
assumes that water is unlimited and is an idealized value that does not depend on crop
type, crop development and management practices.
Many methods are available in the literature to determine ETo (Allen et al., 1998;
Summer and Jacobs, 2005; Yoder et al., 2005). The FAO Penman-Monteith method is
recommended by the FAO for the calculation of ETo (Allen et al., 1998). Also, Garcia et
al. (Garcia et al., 2004) demonstrated that the FAO Penman–Monteith approach is
suitable in the Bolivian Altiplano.
FAO Penman-Monteith equation
The FAO Penman-Monteith approach calculates ETo (mm day-1) using the following
equation (Allen et al., 1998):
ETo =
0.408Δ(Rn − G) + γ 900
T + 273 u2(es − ea)
Δ + γ(1 + 0.34u2)
(2)
where Rn is the net radiation at the crop surface (MJ m-2 day-1); G is the soil heat flux
density (MJ m-2 day-1); T is the mean daily air temperature measured at 2 m height (℃);
u2 is the wind speed at 2 m height (m s-1); es and ea are the saturation and actual vapor
pressure, respectively, and the term (es – ea) is called the vapor pressure deficit (VPD,
kPa); Δ is the slope of the saturated vapor pressure-temperature curve (kPa ℃-1) and γ is
the psychometric constant (kPa °C-1).
4.3.2 Spatial distribution of estimated actual evapotranspiration
Actual evapotranspiration (ETa), and its spatial distribution, can be estimated by
associating the NDVI with ETo and precipitation measurements. Because the amount of
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chlorophyll that a plant has is directly related to the rate of photosynthesis, and during
photosynthesis the plant transpires water (Tucker and Sellers, 1986; Sellers et al., 1992),
the NDVI can be used as an indicator of ETa. Groeneveld et al. (2007) proposed a
methodology suitable for arid and semi-arid areas where near surface groundwater
supports vegetation, to produce a first-order estimate of annual ETa as a function of
NDVI, annual ETo and annual precipitation:
ETa,NDVI = (Annual ETo − Annual precipitation) ⋅ NDVI′ + Annual precipitation (3)
where ETa,NDVI is the estimated annual ETa, and NDVI’ is the spatially averaged raw
mid-summer NDVI (peak season NDVI) normalized by setting bare soil values
(NDVI0) at 0 and values of full vegetation cover (NDVIs) at 1.0, as in equation (4).
NDVI′ =
NDVI − NDVI0
NDVIs − NDVI0
(4)
To estimate the annual ETa,NDVI, which requires mid-summer NDVI, Sentinel-2 satellite
images from December 2017, January 2018 and February 2018 were used. Although
mid-summer in the Altiplano is characterized by intense precipitation events, it was
observed that in general the peak season NDVI in the studied area is also observed in
the Austral summer. Because data from the Quebrada Negra wetland meteorological
station were not available for an entire year, Quebrada Negra station (DGA) data were
used to calculate annual precipitation (the DGA’s Quebrada Negra station is ~800 m
from the Quebrada Negra wetland station) and UC meteorological station data were
used to estimate ETo (1 June 2017 to 31 May 2018). It was not possible to estimate
annual ETo with Quebrada Negra station (DGA) records, because this station does not
measure all the variables that are necessary to estimate potential evapotranspiration.
One NDVI map was generated for each satellite image (Table 4-3), as described in
Section 4.2.1. Only images where there were no clouds in the studied wetlands were
used. Note also that the images used correspond to the ones obtained during the
summer, as required by the Groeneveld et al. method (Groeneveld et al., 2007), in
which peak season NDVI is used. To analyze the sensitivity of this method to the
selection of the mid-summer NDVI value, ETa,NDVI was calculated for each date using
the spatially averaged NDVI’ for each NDVI map (NDVI > 0.2). The annual
precipitation data were obtained from Quebrada Negra station (DGA) and the annual
ETo, calculated with the FAO Penman-Monteith method (Allen et al., 1998), were
obtained from the UC meteorological station.
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Date Name
25/12/2017 S2A_MSIL1C_20171225T143751_N0206_R096_T19KER_20171225T180226
30/12/2017 S2B_MSIL1C_20171230T143739_N0206_R096_T19KER_20171230T192131
09/01/2018 S2B_MSIL1C_20180109T143749_N0206_R096_T19KER_20180109T180001
14/01/2018 S2A_MSIL1C_20180114T143741_N0206_R096_T19KER_20180114T180438
18/02/2018 S2B_MSIL1C_20180218T143749_N0206_R096_T19KER_20180218T211409
23/02/2018 2A_MSIL1C_20180223T143751_N0206_R096_T19KER_20180223T180301
28/02/2018 S2B_MSIL1C_20180228T143749_N0206_R096_T19KER_20180228T193153
Table 4-3. Satellite images used to estimate annual actual evapotranspiration.
Additionally, to observe the spatial distribution of ETa,NDVI, equation (3) and (4) were
applied for each pixel in the images used to obtain the ETa,NDVI map, as presented in
equations (5) and (6):
ETa,NDVI,j = (Annual ETo − Annual precipitation) ⋅ NDVI′(j) + Annual precipitation (5)
NDVI′(j) =
NDVI(j) − NDVI0
NDVIs − NDVI0
(6)
where ETa,NDVI,j is the estimated annual ETa in the pixel “j” of an NDVI image, and
NDVI’(j) is the raw mid-summer NDVI (peak season NDVI) of pixel “j”, normalized
by setting bare soil values (NDVI0) at 0 and values of full vegetation cover (NDVIs) at
1.0, as in equation (4).
4.4 Soil characterization
4.4.1 Field campaign to determine peat depth, describe soil particle distribution and
permeability
Three sites were chosen to carry out soil characterization within the Quebrada Negra
wetland (P1, P2 and SA in Figure 4-7). The pit excavations and the soil sampling
collection were performed at the Quebrada Negra wetland between 22 and 23
November 2018. The “P” locations correspond to the middle (P1) and downstream (P2)
sections of the wetland, respectively. At each “P” location, a trial pit was excavated to
extract soil samples for the soil characterization. The “SA” location corresponds to a
site where a soil auger was used to determine the depth of the peat.
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Figure 4-7. Pit locations (P1 and P2 in yellow), soil auger hole location (SA in pink) and
Quebrada Negra wetland meteorological station (QWS in blue) at the Quebrada Negra
wetland.
The pits excavated for this study (P1 and P2 in Figure 4-7) had a step at 0.5 m, and
another at 1.5 m, to allow sample collection with Shelby tubes (see Section 4.4.1.3), and
a deeper zone where water that emerged was accumulated and then removed. A
schematic of the excavated trial pits at P1 and P2 is shown in Figure 4-8. This scheme
includes the labeling system used for the Shelby tubes sample collection. Figure 4-9
shows the excavation work at the Quebrada Negra wetland. More photographs of the
pits can be found in Appendix A.
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25
Figure 4-8. Trial pit design for soil characterization at the Quebrada Negra wetland. The
labeling system used for the Shelby tubes sample is depicted. PX is for the trial pit at which the
sample was collected, whether at pit P1 or P2. S50 and S150 refer to a sample taken at 50 (S50)
or at 150 (S150) cm depth respectively. V and H identify Vertical and Horizontal samples
respectively.
Figure 4-9. Excavation work of (a) P1 middle of the wetland and (b) P2 downstream, at the
Quebrada Negra wetland.
11..-\ic,.J c.t-rt.
Sample at 50 cm vertical
PX_SSO_V
11..-\ic,.J =
Sample at 150 cm vertical
PX_Sl SO_V
"tiflMAA b-,~
.,.< .:,«C<.:.\..<\
'.'.. .
Sample at SO cm horizontal
PX_SSO_H
~"\,..l"",c
Sample at 150 cm horizontal
PX_SlSO_H
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4.4.1.1 Peat depth determination
Peat depth determination at the Quebrada Negra wetland was performed using a soil
auger (similar to that presented in Figure 4-10). The location for the hole made with the
soil auger to identify the peat depth was approximately 5 metres to the southwest of the
Quebrada Negra meteorological station (see Figure 4-7).
Figure 4-10. Soil auger similar to that used at the Quebrada Negra wetland.
Soil samples at different depths were photographed and stored every 20 to 50
centimetres. Figure 4-11 shows peat samples taken between 30 and 190 centimetres
depths at the Quebrada Negra wetland. As explained above, the 14 samples collected
from the soil auger hole are labeled SA (Figure 4-7), where SA is soil auger and the
remaining digits are the means of the depths at which the sample was taken. MX is the
sample collection number used in the field campaign. Photographs of the other samples
can be found in Appendix B.
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Figure 4-11. Soil samples between 30 and 190 cm deep at the Quebrada Negra wetland for peat
characterization.
4.4.1.2 Soil particle distribution
Soil samples for soil particle distribution analysis were taken as follows: five at pit P1,
six at pit P2 and 14 samples were extracted from the soil auger excavation. These
samples were analyzed by Dictuc’s Geotechnical and Soil Mechanics Laboratory using
the methodology proposed by the American Society of Testing Materials in “Standard
Test Method for Particle-Size Analysis of Soils D422” (ASTM, 2007). Sample
preparation according to the D421 standard (ASTM, 2007) is carried out before the soil
particle distribution analysis. This preparation consists of separating the sample using a
No. 10 sieve by dry sieving and washing. The retained fraction in sieve No. 10 is then
washed, dried and weighed.
The fraction that passes the No. 10 sieve is then separated into a series of fractions using
75 mm, 50 mm, 37.5 mm, 25 mm, 19 mm, 9.5 mm, 4.75 mm, 2.36 mm, 1.18 mm, 0.6
mm, 0.3 mm, 0.15 mm and 0.075 mm. After that, the resulting sample fractions are
weighed on the balance to determine the mass of each.
Particle distribution analyses of the soil samples are presented in Figure 4-12 and Figure
4-13. The samples are labeled as PX_SX, after the pit where they were collected (PX)
and a sample number (SX). MX is the sample collection number used in the field. The
soil samples collected contained a large number of roots and organic matter, especially
the samples that correspond to the upper few centimeters of soil (P1_S1 in Figure 4-12
and P2_S1 in Figure 4-13). This material had to be removed from the sample in the
sample washing stage (before sieving). The 14 samples collected from the soil auger
SA_l00-120 SA_170-190
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hole are labeled SA_ (Figure 4-7), where SA is soil auger and the rest are the means of
the depths at which the sample was taken. MX is the sample collection number for the
laboratory.
Figure 4-12. Soil samples at different depths for soil particle distribution analysis in pit SP1.
Ml) Pl S1 (Surf. level) M2) Pl S2 (90-100 cm) M3) Pl S3 (110-120 cm)
M4) Pl S4 (150-165 cm) MS) Pl S5 (150-155 cm)
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29
Figure 4-13. Soil samples at different depths for soil particle distribution analysis in pit SP2.
M6) P2_S1 (Surf . level) M7) P2_S2 (13-25 cm) M8) P2_S3 (23-40 cm)
M9) P2_S4 (60-l00cm) Ml0) P2_S5 (150-160cm) Mll) P2_S6 (~2m)
' ' . ' .
120
Annex XIII
30
4.4.1.3 Shelby tubes for saturated hydraulic conductivity tests
Thin-walled tubes (Shelby tubes) were used to take undisturbed soil samples at 0.5 and
1.5 m depth at the two trial pits. The tube used for this study and corresponding
dimensions are shown in Figure 4-14. At each of these depths, horizontal and vertical
samples were taken to determine soil saturated hydraulic conductivity (Ks) in both
directions (Figure 4-8). A total of eight samples were taken with the thin walled tubes, 4
at SP1 and 4 at SP2. The samples are labelled as shown in Figure 4-8. Later these
samples were analyzed by the Geotechnical and Soil Mechanics department of Dictuc to
undergo falling-head permeability tests to determine hydraulic conductivity.
Figure 4-14. Photograph of one of the Shelby tubes used for collecting the soil samples at the
Quebrada Negra wetland.
Undisturbed soil sampling was performed using the methodology proposed by the
American Society of Testing Materials in “Standard Practice for Thin-Walled Tube
Sampling of Fine-Grained Soils for Geotechnical Purposes D1587” (ASTM, 2015). The
standard indicates the following procedure for soil sampling.
0
i
D
L
- 6.53 cm
= 91.44 cm
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121
31
First, loose material has to be removed as carefully as possible. Then, the tube head is
fitted concentrically and coaxially to ensure a uniform application of force to the tube
when applying pressure. At the time of sampling, without rotation, the tube must be
driven into the ground with a great and continuous push until reaching a point of
rejection or until the tube head meets the ground. After introducing the tube into the
ground, there should be a waiting period between 5 and 15 minutes before removing the
tube, to generate soil adhesion inside the tube. Before taking the sample, the tube should
be rotated once and then removed from the ground. Finally, the upper and lower part of
the tube must be sealed and labeled, and then transported to the laboratory (ASTM,
2015).
The thin-walled tubes inserted for this study took between 10 seconds and 5 minutes to
bury them approximately 50 cm in the pits’ wall or in the steps of the pits.
In some cases, due to the amount of roots in the pit (e.g., see Figure 4-15), or due to the
difficulty of placing the tube in the correct position, it took more time than that
recommended as standard. Sometimes manual pressure was not enough to insert the
tubes to the required depth (e.g. P1_S50_V, P2_S50_V, P2_S50_H, P2_S150_H). For
those cases, the help of a sledge hammer was required to insert the tube to
approximately 50 cm, the sample length required for laboratory analysis.
After inserting the thin walled tubes, they were left buried with the sample for 5 to 8
minutes for the soil to adhere to the tubes.
122
Annex XIII
32
Figure 4-15. First 60 cm from the surface level at Pit P1 at the Quebrada Negra wetland.
The high groundwater level at the Quebrada Negra wetland makes the soil slurry-like at
depth, making it difficult to remove the samples because of the low adhesion to the
tube. At both pits the soil samples (or part of them) came out of the tube when they
were being removed, in which case the sampling was repeated (sampling points
P1_S50_V, P1_S50_H, P1_S150_V, P1_S150_H and P2_S150_V). In the case of the
samples taken at 1.5 m vertically (P1_S150_V and P2_S150_V), it was decided to dig
around the buried tube and then the tube was tilted to extract the sample intact.
In Figure 4-9 the level of water at the bottom of the pits is shown. The bottom of the pit
had to be constantly drained, due to a continuously rising water level.
More details of the eight thin-walled tube soil sample collection carried out in this study
are described in Appendix C.
4.4.1.4 Falling-head Permeability Test
To obtain values for the soil saturated hydraulic conductivity (Ks) of cohesive sediments
with low conductivities, a falling-head permeameter should be used (Fetter, 1994). For
this study, falling-head permeability tests were performed in the laboratory to obtain Ks.
The falling-head permeability test consists of measuring the flow of water that passes
Annex XIII
123
33
through a (relatively short) soil sample inside a permeameter (Figure 4-16). A set of
standpipe tubes (or vertical falling-head tubes) are attached to the permeameter (see
Figure 4-17). To fulfill the falling head permeability tests, the following materials are
required:
− Permeameter cell (see Figure 4-16)
− Standpipe panel fitted with glass standpipe tubes of different diameters, each
with a valve at its base and a connected tube (see Figure 4-17)
− Balance sensitive to 0.01 g.
Figure 4-16. Permeameter cell for falling-head permeability tests (Head and Epps, 2011).
Furthermore, Figure 4-17 shows a general falling-head permeability test configuration
together with the one used for this study.
t Water
inlet
Pinch clip
Rubber
tubing
Wing nuts - ,
Flat rubber
sealing rings
3 tie-rods-- ·- 1 -~--~-
--=_=___:_----= -=~_
Sample-n-17.::::... ~ )===~
I-+=---=-D
Feet
through perforations
r Top plate
- Steel wool packing
Cell body
~ , - (core cutter)
L
Wire gauze
~ , Cutting edge
Perforated baseplate
124
Annex XIII
34
Figure 4-17. a) General falling-head permeability test configuration (Head and Epps, 2011); b)
falling-head permeability test used for this study.
The initial water level of the standpipe tube must be measured at the beginning and the
water level must be again measured after some time (generally, a few hours). The rate at
which water will drain from the standpipe tube into the sample chamber is the change in
head with time multiplied by the cross-sectional area of the standpipe tube (Fetter,
1994). This means that the diameter of the standpipe determines the duration of the test.
The Ks of the sample can be obtained from Equation (7):
𝐾𝐾𝑠𝑠 =
𝐴𝐴𝑡𝑡𝐿𝐿
𝐴𝐴𝑐𝑐𝑡𝑡
ln
ℎ0
ℎ1
(7)
where Ks (m/s) is the soil saturated hydraulic conductivity; L is the sample length (m);
Ac (m2) is the sample cross-section; At (m2) is the falling-tube cross-section; t (s) is the
recorded time; h0 (m) is the initial water level in the standpipe; and h1 (m) is the final
water level in the standpipe.
a)
II
t
Mercury
manometer
Vacuum line
Overflow
Beaker
(Sdt'attn dpip e tubes
i erent diameters)
A
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125
35
4.4.2 Field saturated hydraulic conductivity
Slug tests were performed to obtain the field saturated hydraulic conductivity in the
radial direction (Kr) and the specific storage representative of field conditions. The slug
test consists of measuring the recovery of head (water level) in a well after a nearinstantaneous
change in head (water level) in that well (Butler, 1997). This can be done,
for example, by rapidly introducing a solid object or equivalent volume of water into the
well (or removing the same), causing an abrupt increase (or decrease) in water level.
Following this sudden change, the water level in the well returns to static conditions as
water moves out of the well or into it (when the change was a decrease in water level) in
response to the gradient imposed by the sudden change in head (Butler, 1997). These
head changes through time, which are termed the response data, can be used to estimate
the hydraulic conductivity of the formation through comparisons with theoretical
models of test responses (Butler, 1997). Under certain conditions, the slug test can also
be used to obtain an estimate of the specific storage (Butler, 1997).
In this case, the experiments were carried out by removing a defined volume of water,
which is usually referred to as a slug-out, or withdrawal test. The recovery was
measured at 5 second intervals using HOBO MX2001 Water Level Loggers.
To determine the hydraulic properties from the field data, the analytical model proposed
by Cooper et al (1967). was used. The analytical solution to the mathematical model
defined by Cooper et al. can be written as:
𝐻𝐻(𝑡𝑡)
𝐻𝐻0
= 𝑓𝑓(𝛽𝛽, 𝛼𝛼) (8)
where 𝛽𝛽 = 𝐾𝐾𝑟𝑟𝐵𝐵𝐵𝐵/𝑟𝑟𝑐𝑐
2 (dimensionless time parameter); 𝛼𝛼 = (𝑟𝑟𝑤𝑤
2𝑆𝑆𝑠𝑠𝐵𝐵)/𝑟𝑟𝑐𝑐
2 (dimensionless
storage parameter); Kr (m/s) is the radial component of the hydraulic conductivity; Ss
(1/m) is the specific storage; B (m) is the formation thickness for fully-penetrating well,
length of well screen otherwise; H (m) is the deviation of head in well from static
conditions; H0 (m) is the magnitude of initial displacement; rw (m) is the effective radius
of well screen; rc (m) is the effective radius of well casing; and t (s) is the time;
The solution of equation (8), when plotted as normalized head vs. the logarithm of β,
forms a series of type curves, with each type curve corresponding to a different value of
α. The method to determine the hydraulic conductivity and specific storage then
consists of plotting the recovery records in terms of the dimensionless time parameter
(β) by adjusting the values of the hydraulic conductivity (Kr) to best fit one of the type
curves corresponding to a specific value of α, which corresponds to a value for the
specific storage (Ss). Figure 4-18 presents an example of field data fitted to the type
curves.
---
126
Annex XIII
36
Figure 4-18. Example of slug test data adjusted to the Cooper et al. type curves (Cooper et al.,
1967).
1 -
0.9
0 .8
0.7
0.6
i.. 0.5
::c
0 .4
0.3
0.2
0.1
0
0.001
r--r--- ,..
,-,.. - t--
,-......__ ---r--.. r-- .i....f ~
.........._ I ' i'-i'-..
' I '
0.01
~ ~ '~ tr--- ♦ ~ "' "
,I "" N:' "
\
\
.,.
\ '
I". •► ' I'\ ◄
\ ' ~ ·r \
\ I\ t
I\ I \
I I
0.1
II I
♦ Obs
- a=10-1
\ - a = 10-2
~\ - a=10-•
- a=10-•
~\ \ - a = l 0- 5
\\' \\ - a = 10-7
- a=1o-•0
~~ 0 \ \
\
\ ~ ~ \ ~
\ ~ I\ \ ' \
1\1\
' '\~ r~ ~
".' ''1HI ·1 ~
1 10 100
Annex XIII
127
37
4.4.3 Thermal properties
Before backfilling the hole excavated for the soil sensors installation, thermal properties
of the soil (thermal conductivity K, volumetric specific heat C and diffusivity D) were
measured with a Thermal Properties Analyzer (KD2 Pro, Decagon), as shown in Figure
4-19. Measurements were taken at three different points of the uncovered portion of the
vertical wall (Figure 4-19), of the underwater portion of the vertical wall and of the
horizontal bottom of the hole, for a total of nine measurements.
Figure 4-19. Thermal properties of soil measured at the unsaturated vertical wall.
4.5 Groundwater level monitoring
4.5.1 Monitoring network
A network of monitoring points was designed to monitor groundwater levels in the
Quebrada Negra at two different depths simultaneously. To achieve this, each
monitoring point consists of a pair of piezometers as represented in the layout in Figure
4-20. The piezometers were marked with “D” indicating “deep” level and with “S” for
“shallow” level.
128
Annex XIII
38
Figure 4-20. Pair of piezometers layout per monitoring point.
The piezometers were built using 50 mm diameter PVC tubes, with a 0.3 m screen
consisting of 10 mm holes covered with geotextile fabric glued on the inside walls. The
installation was performed by digging holes with an earth auger with a 60 mm bit as
shown in Figure 4-21, then the PVC tubes were inserted, and the holes were backfilled
with sand taken from nearby locations.
11D" "S"
50mm~,
0.3m 0.5m
ol:I·_ :o~
0 i? Oc, C)
~o·<:) 0 ,,,,o <>
., 01:70 0 ,_o........,,.. ~~ ~ .
• t: 1 m •• •• •
2.5 m
n,m
Annex XIII
129
39
Figure 4-21. Use of earth auger at study site.
Initially, two locations were selected to test the piezometers and correspond to: (1) at
the stream bank, and (2) inside the wetland (Figure 4-22). One shallow piezometer (1.5
m length) was installed at test site 1 (Figure 4-23) and a pair of piezometers was
installed at test site 2 (Figure 4-24) as described in Figure 4-20. Table 4-4 shows
measurements of water table depth respective to ground surface, one week after the
installation of these piezometers.
130
Annex XIII
40
Figure 4-22. Location of test sites.
Figure 4-23. Shallow piezometer (1.5 m length) inserted 1 m at test site 1.
Annex XIII
131
41
Figure 4-24. Pair of piezometers installed at test site 2.
Piezometer 1-shallow 2-shallow 2-deep
Depth to groundwater (cm) 49 12 23
Table 4-4. Depth of water table at test piezometers.
According to these preliminary results, useful measurements can be expected to be
obtained with this piezometer design (Figure 4-20), even on the stream bank. Therefore,
82 monitoring points were constructed, distributed as shown in Figure 4-25 and Figure
4-26. The numbers indicate relative position or transect, increasing in the downstream
direction. On the main grassland, where multiple monitoring points per transect were
installed, the letter indicates its position relative to the northern or southern limits of the
wetland, “A” being the northernmost monitoring point of the transect and “Z” the
southernmost.
132
Annex XIII
42
Figure 4-25. Layout of the monitoring wells in the Quebrada Negra ravine.
Figure 4-26. Layout of the monitoring wells in the Quebrada Negra wetland. Locations with
sensors for continuous groundwater level monitoring are depicted in blue and locations where
the groundwater level is monitored at a monthly time scale are shown in red.
S99800
50 100
Meters
_____i'S AD56/U1Mzone 19>
Annex XIII
133
43
The locations of the monitoring wells were measured using a multi-frequency GPS
receiver (Carlson BRx5 GNSS receiver, Carlson Software Inc., Maysville, KY), but due
to battery constraints, the positions of both piezometers could only be identified at the
monitoring points between locations 21 to 25, for the rest only the position of the
northernmost piezometer of the pair was recorded. Table 4-5 compiles the information
of each monitoring point.
Point
X deep
(PSAD56
19S)
Y deep
(PSAD56
19S)
X shallow
(PSAD56
19S)
Y shallow
(PSAD56 19S)
Top
Elevation
deep
(m.a.s.l.)
Top
Elevation
shallow
(m.a.s.l.)
Distance
Topground
deep (m)
Distance
Topground
shallow
(m)
Depth
deep
(m)
Depth
shallow
(m)
01 600360.183 7563693.641 4290.61 1.05 0.20 1.95 1.31
02 600340.906 7563696.889 4287.47 1.32 0.53 1.69 0.97
03 600321.426 7563698.013 4284.64 0.86 0.74 2.14 0.76
04 600300.385 7563697.771 4280.38 0.72 0.63 2.28 0.87
05 600282.143 7563695.873 4277.31 0.70 0.42 2.30 1.08
06A 600262.778 7563700.269 4274.53 0.51 0.49 2.49 1.01
06M 600262.583 7563693.566 4274.81 0.48 0.49 2.52 1.01
06Z 600262.78 7563687.209 4275.22 0.83 0.61 2.17 0.89
07A 600258.677 7563703.156 4273.91 0.88 0.61 2.12 0.89
07F 600258.128 7563696.144 4274.08 0.67 0.48 2.33 1.02
07S 600258.542 7563692.737 4274.91 0.62 0.49 2.39 1.01
07Z 600257.255 7563684.215 4274.65 0.99 0.62 2.01 0.89
08A 600247.716 7563708.4 4273.54 0.97 0.58 2.03 0.92
08F 600247.255 7563700.426 4273.27 0.70 0.55 2.30 0.95
08M 600246.984 7563693.836 4273.397 0.77 0.58 2.24 0.92
08S 600246.753 7563687.865 4273.76 0.75 0.45 2.25 1.05
08Z 600246.903 7563681.637 4273.90 0.86 0.62 2.14 0.88
09A 600242.554 7563709.332 4273.28 1.10 0.56 1.90 0.94
09F 600242.423 7563701.545 4272.81 0.68 0.57 2.32 0.93
09M 600242.263 7563693.782 4272.70 0.64 0.59 2.36 0.91
09S 600241.612 7563687.849 4272.96 0.83 0.57 2.17 0.93
09Z 600241.309 7563681.235 4273.11 0.81 0.47 2.19 1.03
10A 600237.456 7563710.454 4272.66 0.96 0.54 2.04 0.96
10F 600237.214 7563702.513 4272.51 0.84 0.65 2.16 0.85
10M 600237.213 7563694.099 4272.08 0.80 0.56 2.20 0.94
10S 600236.647 7563687.929 4272.48 0.78 0.46 2.22 1.04
10Z 600237.107 7563680.968 4272.56 0.71 0.61 2.29 0.89
11A 600232.933 7563710.657 4272.15 0.84 0.54 2.16 0.96
11F 600232.868 7563702.475 4271.95 0.69 0.58 2.31 0.92
11M 600232.237 7563694.431 4271.71 0.66 0.60 2.34 0.90
11S 600232.382 7563687.413 4271.61 0.61 0.63 2.39 0.87
11Z 600232.14 7563679.816 4271.83 0.73 0.53 2.27 0.97
12A 600227.373 7563711.535 4271.56 1.03 0.49 1.98 1.01
12F 600227.551 7563702.481 4271.01 0.70 0.63 2.30 0.87
12M 600227.248 7563695.334 4271.17 0.68 0.61 2.33 0.89
12S 600227.312 7563687.646 4270.92 0.58 0.51 2.43 0.99
12Z 600227.514 7563678.89 4271.92 0.77 0.58 2.23 0.92
13A 600223.124 7563711.995 4271.13 1.11 0.55 1.89 0.95
13F 600222.179 7563702.568 4270.31 0.64 0.48 2.36 1.02
13M 600222.178 7563695.211 4270.45 0.66 0.48 2.34 1.02
13S 600222.105 7563687.631 4270.12 0.55 0.50 2.45 1.00
13Z 600221.977 7563678.212 4270.09 0.85 0.53 2.15 0.97
14A 600217.892 7563712.441 4270.20 1.00 0.72 2.01 0.78
14F 600217.003 7563702.418 4269.75 0.62 0.50 2.38 1.00
14M 600216.787 7563694.948 4269.56 0.72 0.56 2.28 0.94
14S 600216.041 7563687.063 4269.04 0.66 0.60 2.34 0.90
14Z 600216.836 7563677.136 4269.65 0.89 0.56 2.11 0.95
15A 600212.883 7563712.677 4269.49 0.94 0.53 2.06 0.97
15F 600212.503 7563702.694 4269.15 0.68 0.52 2.32 0.98
15M 600212.085 7563695.346 4268.95 0.75 0.72 2.25 0.78
15S 600211.808 7563687.244 4268.73 0.66 0.61 2.34 0.89
134
Annex XIII
44
Point
X deep
(PSAD56
19S)
Y deep
(PSAD56
19S)
X shallow
(PSAD56
19S)
Y shallow
(PSAD56 19S)
Top
Elevation
deep
(m.a.s.l.)
Top
Elevation
shallow
(m.a.s.l.)
Distance
Topground
deep (m)
Distance
Topground
shallow
(m)
Depth
deep
(m)
Depth
shallow
(m)
15Z 600211.557 7563676.352 4268.60 0.53 0.53 2.47 0.97
16.5 600205.043 7563706.83 4267.80 0.67 0.46 2.33 1.04
16A 600208.303 7563713.129 4269.33 1.04 0.73 1.96 0.77
16F 600207.832 7563702.559 4268.05 0.97 0.65 2.03 0.85
16M 600207.582 7563695.472 4267.97 0.61 0.60 2.39 0.90
16S 600206.996 7563687.524 4267.93 0.69 0.63 2.31 0.87
16Z 600206.988 7563677.444 4268.52 1.49 0.61 1.51 0.89
17A 600203.536 7563713.539 4268.48 1.31 0.65 1.69 0.85
17F 600203.393 7563703.192 4267.69 0.68 0.41 2.32 1.09
17M 600203.299 7563696.284 4267.21 0.62 0.47 2.38 1.03
17S 600202.842 7563688.892 4267.23 0.80 0.53 2.20 0.97
17Z 600202.568 7563680.999 4267.58 0.92 0.59 2.08 0.91
18A 600198.278 7563713.45 4267.78 1.41 0.57 1.59 0.93
18F 600198.046 7563703.702 4267.09 0.51 0.63 2.49 0.87
18M 600197.967 7563698.223 4266.54 0.71 0.48 2.29 1.02
18S 600198.177 7563690.617 4266.67 0.74 0.58 2.26 0.92
18Z 600198.357 7563682.497 4267.11 0.99 0.51 2.01 0.99
19A 600193.244 7563713.938 4266.96 1.68 0.62 1.32 0.88
19F 600193.126 7563705.399 4266.24 0.68 0.53 2.32 0.97
19S 600192.779 7563698.847 4265.76 0.66 0.45 2.34 1.05
19Z 600192.192 7563692.131 4265.48 0.42 0.41 2.58 1.09
20A 600188.667 7563713.975 4266.02 1.36 0.55 1.64 0.95
20M 600188.411 7563705.304 4265.56 0.65 0.48 2.35 1.02
20Z 600187.99 7563695.638 4265.25 0.76 0.63 2.24 0.87
21A 600182.234 7563714.576 600182.381 7563714.185 4265.205 4263.92 1.85 0.57 1.15 0.93
21M 600182.192 7563706.095 600182.244 7563706.567 4264.42 4264.28 0.77 0.47 2.23 1.03
21Z 600182.181 7563698.901 600182.171 7563698.559 4264.86 4264.37 0.93 0.52 2.07 0.98
22 600139.982 7563712.238 600139.878 7563711.906 4259.87 4259.48 0.80 0.43 2.20 1.07
23 600071.769 7563741.156 600071.592 7563740.753 4251.97 4251.68 0.79 0.45 2.21 1.05
24 599985.429 7563772.838 599985.232 7563772.582 4243.91 4243.43 0.99 0.47 2.01 1.03
25 599872.601 7563798.155 599872.782 7563798.576 4237.15 4236.86 0.90 0.67 2.10 0.83
Table 4-5. Location, elevation and depth of groundwater level monitoring grid.
4.5.2 Ground water level measurements
Levels at each piezometer were measured manually with a water level dipper on a
monthly schedule starting in August 2018. Additionally, an array of 10 Water Level
Logger sensors (HOBO® MX2001, Onset Computer Corporation, Bourne, MA) were
installed in pairs at 5 monitoring points distributed inside the main grassland. The
location of these sensors is highlighted in blue in Figure 4-26. These sensors can
measure simultaneously barometric pressure, water pressure and temperature to
determine the water level, and were programmed to record all these variables at 15
minutes intervals.
5. RESULTS AND DISCUSSION
The results obtained from the various investigations performed in the Quebrada Negra
wetland, including comparison with the Bolivian wetlands, are presented in this section.
Annex XIII
135
45
5.1 Quebrada Negra Wetland meteorological station
The data measured by the Quebrada Negra Wetland meteorological station are
temperature, precipitation, relative humidity, wind speed and direction, net radiation,
soil moisture, soil temperature, and soil heat flux. These data are collected every 15
minutes.
The Quebrada Negra Wetland meteorological data collected from 14 June 2018 to 29
November 2018 are presented in the next section on a daily time-scale. These data are:
air temperature and relative humidity, precipitation, wind speed and direction, net
radiation (four components of radiation), soil moisture, soil temperature, and soil heat
flux. Unfortunately, because of the work performed during the installation of the
satellite transmission system, data between 21 and 29 August 2018 were lost.
5.1.1 Air temperature
Figure 5-1 shows the maximum, mean and minimum temperature time series at
Quebrada Negra. The daily maximum temperatures vary between -3 and 17 °C, while
the daily minima vary between -11 and 1 °C for the study period. The temperatures
slowly rise as winter ends and summer approaches.
Figure 5-1. Temperature time series at the Quebrada Negra Wetland meteorological station.
5.1.2 Precipitation
Figure 5-2 shows daily precipitation at the Quebrada Negra wetland. Seven precipitation
events were identified during the study period, with a maximum precipitation of 4.3 mm
on 20 July 2018. Figure 5-3 shows the snow cover percentage in the Silala River basin
between June and November 2018. As shown here, precipitation events detected by the
meteorological station since June 2018 correspond to snowfall events. Figure 5-3
evidences a higher number of snowfall events than those registered by the Quebrada
20
15
E.. 10
~
~ i 0
.\: -5
-10
-15
06/12 06/26 07/10 07/24 08/07
- Tmean - Tmin - Tmax
08/21 09/04 09/18 10/02 10/16 10/30 11/13 11/27
136
Annex XIII
46
Negra Wetland meteorological station. It should be noted that Figure 5-3 shows the
snow cover of the whole basin, considering zones that have a much higher elevation
than that of the Quebrada Negra wetland meteorological station. However, analysis of
individual satellite images showed that there was abundant snow at the Quebrada Negra
while the pluviometer remained reporting zero precipitation. This phenomenon probably
occurs due to the inherent limitations of pluviometers designed to capture rainfall.
Figure 5-2. Precipitation time series at the Quebrada Negra Wetland meteorological station.
Figure 5-3. Snow cover percentage in the Silala River basin (obtained from MODIS images).
5.1.3 Relative Humidity
Figure 5-4 shows the maximum, mean and minimum daily relative humidity time series
at Quebrada Negra. Figure 5-5 shows the relationship between the precipitation and
relative humidity, which tends to increase before rainfall events.
0
06/12 06/26 07/10 07/24 08/07
50
4S
40
~..: ~ § 2S 120
~ ~i I .. I I . I l.111.. _ _ 111
06/12 06/16 07/10 07/24 08/07
08/21 09/04
08/11 09/04
09/18 10/02 10/16 10/30 11/13 11/27
09/18 10/02 10/16 10/30 11/13 11/27
Annex XIII
137
47
Figure 5-4. Daily maximum, mean and minimum relative humidity time series at the Quebrada
Negra wetland meteorological station.
Figure 5-5. Daily mean relative humidity (lower, in blue) and precipitation (upper, in orange)
time series at the Quebrada Negra wetland meteorological station.
5.1.4 Wind speed and Wind direction
Figure 5-6 shows the maximum, mean and minimum daily wind speed time series at the
Quebrada Negra.
Figure 5-6. Daily mean, minimum and maximum wind speed time series at the Quebrada Negra
wetland meteorological station.
120
100
~ j 80
§ 60
"' ·.",J,;, 40
::.
20
120
*
140 ~
► 100 ..t.,:
- RHmean - RHmin - RHmax
06/26 07/10 07/24 08/07 08/21 09/04 09/18 10/02 10/16 10/30 11/13 11/27
0
.E 80
.E f: J ! -~ ~ 6 !
! :: 1111111l1l~11~l1~l11lll l1 I I I m1~ IIIJ111•11ll _ 111~1lllllllll1l1111llllll111ll l11111~111~11h111lmll111l.1i1ll~i I" !
9
8
06/12 06/26 07/10 07/24 08/07 08/21 09/04 09/18 10/02 10/16 10/30 11/13 11/27
- Wind mean - Windmin - Windmax
06/26 07/10 07/24 08/07 08/21 09/04 09/18 10/02 10/16 10/30 11/13 11/27
138
Annex XIII
48
Figure 5-7 shows the wind rose for daytime (between 8:00 and 21:00) and night-time
(between 21:00 and 8:00) at Quebrada Negra. During daytime the predominant wind
direction is from the west, while at night-time the strongest winds come from the east.
Figure 5-7. Wind rose at the Quebrada Negra wetland meteorological station. Left: daytime
wind rose. Right: nighttime wind rose.
5.1.5 Net radiation
Figure 5-8 shows the mean daily net radiation and precipitation time series at the
Quebrada Negra. Mean net radiation rises as winter ends and summer approaches.
When comparing the net radiation with precipitation, it can be appreciated that mean
daily net radiation decreases with rainfall events, resulting in negative values in some
cases.
Figure 5-8. Mean daily net radiation (lower, in blue) and precipitation (upper, in orange) time
series at the Quebrada Negra wetland meteorological station.
Wind Speeds in mis - W, ~9
- 8 S Ws<9
_ , s ws<a
6 < ws < 7
- 5 < Ws<6
- 4 < Ws<S
- 3 S Ws"''
- 2 S W5 <3
- 1SW5<2
- 0 :SWs<1
20
15
Wind Rose 2018-11-29 9-20 hrs.
N~
S(180')
,..,
. ·. 11.2%
. 8.4111,
5.6',
~ 10
tr•1~lll~l11l\,..,111,1i~li~
{
::.
;; 5
0
-5
06/12 06/26 07/10 07/24 08/07 08/21
E(90')
Wind Speeds in mis - w, ~ 7 Wind Rose 2018-11-29 21-8 hrs.
- 6 S Ws<7
- S S Ws<6
11iiiiii14 < Ws <S
- 3 <W5 <4
- 2 < Ws<3
- 1 S W5 <2
- OS W5 <1
W(270")
11111
09/04 09/18
I! I
10/02
N~
S(180')
10/16 10/30
7.2!1
181<
14 .4%
10.8%
11/13 11/27
E(90')
0
ze
E lj
4 .i_
~
5 0.
6
7
Annex XIII
139
49
5.1.6 Soil heat flux
Figure 5-9 shows the daily average soil heat flux time series at the Quebrada Negra
wetland. Fluxes directed downwards (towards the ground) are considered positive,
while fluxes directed upwards (towards the atmosphere) are considered negative.
Soil heat flux rises as summer approaches. The negative values observed during winter
could be attributed to the presence of snow on the surface and low temperatures in, and
even freezing of, the ground (Figure 5-3 and Figure 5-9 below), as records became
positive after soil temperature started to rise. More data at the Quebrada Negra wetland
is needed to validate these measurements and to see if this behavior is consistent in
time.
Figure 5-9. Soil heat flux (above) and soil temperature (below) time series at the Quebrada
Negra Wetland meteorological station. TC: temperature measured with the soil thermocouple
probe; WCR: temperature measured with the water content reflectometer.
5.2 Spatial and temporal distribution of vegetation cover
5.2.1 Spatial distribution of vegetation cover
The monthly average NDVI maps obtained using the Sentinel-2 images are presented in
Figure 5-10 and the total area covered by vegetation is presented in Table 5-1. The
NDVI is higher in the middle of all of the wetlands than at the edges, and we can see
10
9
8
7
6
5
;?° 4
E 3 "~"
" 1
0 -1 \{ vvv -2
·3
.4
-5
06/12 06/26 07/10 07/24 08/07 08/21 09/04 09/18 10/02 10/16 10/30 11/13 11/27
- TC - WCR
12
10
E 8
~ 6 .e. 0. 4 E
~
~
0
-2
06/12 06/26 07/10 07/24 08/07 08/21 09/04 09/18 10/02 10/16 10/30 11/13 11/27
140
Annex XIII
50
from the Quebrada Negra that this corresponds to the area where dense vegetation can
be observed, mostly composed of a green vegetation cover. Figure 5-11 shows a highresolution
Ortho mosaic taken with the UAV in the Quebrada Negra wetland. This
image was used to validate the distribution of NDVI in the Quebrada Negra wetland,
and as can be seen, NDVI is higher where more vegetation is observed in the Ortho
mosaic.
Additionally, the mean NDVI in each wetland is presented in Table 5-2. As shown in
Table 5-1, in general the total area covered by active vegetation increased with time
over the observational period, except for the Quebrada Negra wetland, in which it is
observed that the total area covered by active vegetation decreased in November, 2018,
although the mean NDVI increased (Table 5-2).
Annex XIII
141
51
Figure 5-10. Quebrada Negra, Cajones and Orientales wetlands average NDVI distribution
from July to November 2018.
Normalized Difference Vegetation Index NDVI
D < = 0.20 • 0.20 - 0.25 D 0.25 - 0.30 D 0.30 - 0.35 • > 0.35
142
Annex XIII
52
Figure 5-11. High-resolution ortho mosaic taken with the UAV.
Area covered by active vegetation (ha)
July August September October November
Quebrada Negra
wetland 2.13 2.31 2.58 4.12 3.43
Cajones wetland 0.81 1.12 1.31 2.20 2.41
Orientales wetland 2.23 2.70 2.86 6.09 7.50
Table 5-1. Area covered by active vegetation (NDVI > 0.2) in the Quebrada Negra, Cajones
and Orientales wetlands, from July to November 2018.
July August September October November
Quebrada Negra wetland 0.24 0.25 0.25 0.27 0.30
Cajones wetland 0.23 0.25 0.25 0.28 0.33
Orientales wetland 0.23 0.23 0.23 0.26 0.29
Table 5-2. Mean NDVI for the Quebrada Negra, Cajones and Orientales wetlands, from July to
November 2018.
I I I I
Annex XIII
143
53
Figure 5-12, Figure 5-13 and Figure 5-14 show how the vegetation cover is located
within the terrain of the Quebrada Negra, Cajones and Orientales wetlands, respectively.
Figure 5-12. Cross section of vegetation cover (NDVI>0.2) and topography of the Quebrada
Negra wetland. The Average (Green Line) and Maximum (Red Line) cross section of vegetation
cover have the same extent. For this reason, only the average green cover (green line) is visible.
4307
4302
4297
E 4292
C
.!2
io
~ 4287
;::;:;
4282
4277
4272
Cross Section Quebrada Negra
NDVIJul/18-Nov/18 =0.2
0 25 50 75
Cover vegetation estimation using
Sentinel-2 0
100 125
200
Average section covered by
vegetation (NDVl=0.2,
Maximum section covered by
vegetation (NDVl=0.2, Red line)
between Jul/18-Nov/18
- AW3DTM
- Max
- Average
150 175 200
Horizontal distance [m]
144
Annex XIII
54
Figure 5-13. Cross section of vegetation cover (NDVI>0.2) and topography of the Cajones
wetland.
Figure 5-14. Cross section of vegetation cover (NDVI>0.2) and topography of the Orientales
wetland.
4383
4378
0 4373
E"'
5 4368
'.;:;
">'
(I)
w 4363
4358
Cross Section Cajones
NDVIJul/18-Nov/18 =0.2
0 Cover vegetation
Average section covered by vegetation
(NDVl=0.2, Green line)
Maximum section covered by vegetation
(NDVl=0.2, Red line)
- AW3DTM
- Max
4353
-+---___________ _____. ___ .c,_ ___________ ~ - Average
0 25 50 75
Cross Section Orientales
NDVIJul/18-Nov/18 =0.2
4422
4420
4418
vi
14416
C
0
·..::; 4414
~
~
UJ
4412
4410
4408
0 25 so
100 125 150 175 200 225 250 275 300
Horizontal distance [m]
Cover vegetat ion estimation using
Sentinel-2
75 100 125
Horizontal distance [m]
200
Average section covered by
vegetation (NDVl=0.2, Green l'ne)
Maximum section covered by
vegetation (NDVl=0.2, Red line)
between Jul/18-Nov/18
- AW3DTM
- Max
,--------' --Average
150 175 200
Annex XIII
145
55
It can be observed for each of the three wetlands that the distribution of active
vegetation covers the flat area available and expands up the adjacent hillslopes where
slopes are less than approximately 15%. However, the resolution of the digital elevation
model prevents more accurate estimates of the relationship with slope.
In the case of the cross sections of Cajones and Orientales it is observed that between
the months of July-2018 and November-2018 the maximum coverage extent is greater
than the average extent (Figure 5-13 and Figure 5-14). In the case of the Quebrada
Negra wetland cross-section (Figure 5-12), the maximum and mean extent do not vary
significantly and cover the same transverse section, so although the NDVI value
increases (showing greater photosynthetic activity), it does not increase in spatial extent
at this location. However, an increase in vegetation cover in the Quebrada Negra
wetland was observed for stream cross sections located downstream and upstream of the
studied cross section, where the width of vegetation cover increased in the north-south
direction. It should be noted that the range of variation is limited to the Sentinel raster
resolution (10 m), so minor variations in this range are not captured.
5.2.2 Temporal evolution of vegetation cover
To determine a NDVI threshold value from the LANDSAT data we visually inspected
the vegetation cover over the areas of interest (Figure 5-15) and validated the chosen
value (0.2) by comparing the areas with high resolution drone pictures (Figure 5-16).
The results for each zone are presented in Figures 5-17 to 5-19. Between 2012 and 2017
one can observe larger areas than in previous years, probably due to the better quality of
information collected by the LANDSAT-8 satellite (higher spectral sensitivity). The
increase for this period can be associated with the change in the technology of the
acquisition of LANDSAT images. Roy et al. concluded for vegetated soil and
vegetation surfaces (0 ≤ NDVI ≤ 1), the OLI NDVI (Landsat -8) is greater than the
ETM+ NDVI (Landsat-7) (Roy et al., 2016).
146
Annex XIII
56
Figure 5-15. Vegetation cover over the Quebrada Negra, Orientales and Cajones wetlands for
NDVI thresholds 0.1, 0.15 and 0.2.
N
A
b)
1 25 25 5 Kilometers
a) Vegetation Cover over Silala Watershed for NDVI >= 0.10
b) Vegetation Cover over Silala Wat ershed for NDVI >= 0.15
c) Vegetation Cover over Silala Watershed for NDVI >= 0.20
Annex XIII
147
57
Figure 5-16. Validation of vegetation cover over the Quebrada Negra with an NVDI threshold
value of 0.2.
a) N A
12 Kilometers
c)
01 02 0-4 Kilometers
a) RGB satellite picture c) Vegetation Cover - zoomed
b) Vegetation Cover d) Picture of Quebrada Negra 2018/04/25
148
Annex XIII
58
Figure 5-17. Time series of active vegetation cover (NDVI>=0.2) over the Quebrada Negra (Q.N.) wetland (1986-2017).
Figure 5-18. Time series of active vegetation cover (NDVI>=0.2) over the Cajones wetland (1986-2017).
Figure 5-19. Time series of active vegetation cover (NDVI>=0.2) over the Orientales wetland (1986-2017).
Orientales [ ha I Cajones I ha I Q. N. I ha l
~ .. "' ., 0 :::
Q~ - ~N~W~ oe .... ~,-it:w~
Jan-86
Jan-86 Jan-86
Jul-86
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Jan-87
Jan-87 Jan-87
Jul-87
Jul-87 Jul-87
Jan-88
Jan-88 Jan-88
Jul-88
Jul-88 Jul-88
Jan-89
Jan-89 Jan-89
Jul-89
Jul-89 Jul-89
Jan-90
Jan-90 Jan-90
Jul-90
Jul-90 Jul-90
Jan-9 1
Jan-91 Jan-91
Jul-9 1
Jul-91 Jul-91
Jan-92
Jan-92 Jul-92 Jul-92 ·:;::~ ~
Jan-93 2
Jan-93 Jan-93 C
Jul-93 Jul-93 V,
Jul-93 ~ Jan-94 Jan-94 Jan-94 &,
Jul-94 Jul-94 Jul-94
Jan-95 Jan-95 Jan-9S
Jul-95 Jul-9S Jul-9S
Jan-96 Jan-96 Jan-96
Jul-96 Jul-96 Jul-96
Jan-97 Jan-97 Jan-97
Jul-97 Jul-97 Jul-97
Jan-98 Jan-98 Jan-98
Jul-98 Jul-98 Jul-98
Jan-99 Jan-99 Jan-99
Jul-99 Jul-99 Jul-99
Jan-00 Jan-00 Jan-00
Jul-00 Jul-00 Jul-00
Jan-01 Jan-01 ... ~~ I r-
Jul-01 Jul-01 Jul-01
)>
2
Jan-02 Jan-02 Jan-02 C
V,
Jul-02 Jul-02 Jul-02 )>
--t
Jan-03 Jan-03 Jan-03 .:...
Jul-03 Jul-03 Jul-03
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Jul-04 Jul-04 Jul-04
Jan-OS Jan-05 Jan-OS
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Jan-06 Jan-06 ""~t r-
)>
Jul-06 Jul-06 Jul-06 2
Jan-07
C
Jan-07 Jan-07 V,
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)>
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Jan-08 Jan-08 Jan-08 V,
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'"'"~
+ ~
Jan-11 Jan-11 Jan-11 I 2
Jul-II Jul-11
C
Jul-11 V,
Jan-12 Jan-12 Jan-12 ~
Jul-12 Jul-12 Jul-12 .:...
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Jul-14 Jul-14 "Ju"l-1"4 ~ ~
2
Jan-15 Jan-15 Jan-15 C
V,
Jul-lS Jul-IS Jul-IS ~ Jan-16 Jan-16 Jan-16 00
Jul-16 Jul-16 Jul-16
Jan-17 Jan-17 Jan-17
Jul-17 Jul-17 Jul-17
Annex XIII
149
59
Figure 5-20, Figure 5-21 and Figure 5-22 show box plots of the monthly active
vegetation cover over the period between 1986 and 2017. Each box consists of a lower
line representing the 25th percentile, and an upper line representing the 75th percentile;
the centre line is the median, the whiskers represent the maximum and minimum values,
while single dots are outliers. It can be observed that the vegetation cover peaks
between April and May and that there is strong variability for all the sites, especially in
the Cajones wetland, during the December-May period. Moreover, the average
vegetation cover during the Austral summer (i.e., December, January and February) is
1.7, 1.9 and 4.5 ha, for Quebrada Negra, Cajones and Orientales, respectively, whereas
during Austral winter (i.e., June, July and August) the values drop to 1.0, 0.8 and 1.1 ha.
Table 5-1 shows that vegetation coverage increased from July to December as obtained
from the Sentinel-2 images, which is consistent with the historical average variation
curves (1986-2017) obtained by LANDSAT images. Nevertheless, the values obtained
from Sentinel and LANDSAT products are not directly comparable, as the latter are less
accurate. However, LANDSAT presents a larger period over which imagery is offered
and therefore, allows for more years to be considered in the analysis of annual and
seasonal variability.
150
Annex XIII
60
Figure 5-20. Monthly time series of active vegetation cover (NDVI>=0.2) over the Quebrada
Negra wetland (1986-2017).
Figure 5-21. Monthly time series of active vegetation cover (NDVI>=0.2) over the Cajones
wetland (1986-2017).
Figure 5-22. Monthly time series of active vegetation cover (NDVI>=0.2) over the Orientales
wetland (1986-2017).
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Annex XIII
151
61
5.3 Evapotranspiration estimates
5.3.1 Potential evapotranspiration
ETo at the Quebrada Negra wetland was estimated with the FAO Penman-Monteith
equation using the data from the Quebrada Negra Wetland meteorological station
(Figure 5-23). The ETo for the study period varies between ~0 and 5.7 mm/day (on 14
June and 10 November, respectively). The minimum value was observed on a rainy day,
but the minimum value of days without rain events was 0.8 mm/day (24 July). As
expected, ETo increases as the summer approaches. Also, the FAO Penman-Monteith
method results in a clear reduction of the ETo when it rains.
Figure 5-23. Relationship between daily ETo (lower data, in blue) and daily precipitation
(upper data, in orange) at the Quebrada Negra Wetland meteorological station.
5.3.2 Spatial distribution of estimated actual evapotranspiration
After generating the NDVI maps, ETa,NDVI was calculated using equation (3). The
annual ETo from the UC meteorological station and the annual precipitation from the
Quebrada Negra station (DGA) data were used to calculate ETa,NDVI at the Quebrada
Negra, Cajones and Orientales wetlands. The annual ETo at the UC meteorological
station was 1284 mm and the annual precipitation at Quebrada Negra station (DGA)
was 173 mm. In this analysis, it was decided to use data from UC meteorological station
and Quebrada Negra station (DGA) because they have been collecting information for
more than one year. Despite the fact that the Quebrada Negra wetland station
measurements should represent better the conditions in the studied wetlands, the site
does not have an entire year of data.
The ETa,NDVI results obtained for each satellite image are presented in Table 5-3. It was
decided to estimate ETa,NDVI for each satellite image to analyze the sensitivity of the
Groeneveld et al. (2007) method to the selection of the mid-summer NDVI (peak season
NDVI) map. As shown in Table 5-3, since NDVI’ does not vary significantly between
: . I
1! ~ii~iW,11~i~~ Ir II ~ I~~ II 7
06/12 06/26 07/10 07/24 08/07 08/21 09/04 09/18 10/02 10/16 10/30 11/13 11/27
152
Annex XIII
62
different satellite images, hence all NDVI’ values should be appropriate to estimate
annual ETa,NDVI. Additionally, the mean ETa,NDVI values and its standard deviation for
each wetland are presented in Table 5-3. Figure 5-24 shows the time-averaged ETa,NDVI
map.
Taking into consideration the data presented in Table 5-3, when using the different
satellite images to calculate mid-summer NDVI’, the ETa,NDVI estimates for the
Quebrada Negra wetland vary between 596 and 654 mm/year, whereas the Cajones
ETa,NDVI varies between 670 and 729 mm/year. On the other hand, the Orientales
wetland ETa,NDVI varies between 659 and 734 mm/year. Furthermore, the ETa standard
deviation for all three wetlands is of the order of ~20 mm/year, giving the estimated
annual ETa,NDVI of 631 ± 21 mm/year for the Quebrada Negra wetland, 705 ± 17
mm/year for the Cajones wetland and 702 ± 23 mm/year for the Orientales wetland. It
can be noted that Groeneveld et al. showed that their method has residual errors that
decrease as measured ETa increases (Groeneveld et al., 2007), with error values of the
order of 3.5 – 16.9 % for ETa,NDVI estimates of the same magnitude as the ones obtained
in this study.
In summary, the largest time-averaged evapotranspiration values are estimated for the
Cajones wetland, while the lowest ones are observed in the Quebrada Negra wetland.
Additionally, the mean equivalent water flow due to this evapotranspiration (i.e.
considering the potential loss of river flow represented by this amount of evaporation)
was estimated to be 0.6 L/s for the Cajones wetland, 2.3 L/s for the Orientales wetland
(which has the largest area) and 0.7 L/s for the Quebrada Negra wetland.
Annex XIII
153
63
Studied wetland
Satellite image
date
Area covered by
vegetation [ha]
Average NDVI raw
[-]
NDVI'
[-]
ETa,NDVI
[mm/year]
Quebrada Negra 25-12-2017 4.48 0.31 0.38 596
wetland 30-12-2017 3.10 0.32 0.43 647
09-01-2018 2.64 0.32 0.43 654
14-01-2018 3.68 0.30 0.43 653
18-02-2018 3.51 0.32 0.40 620
23-02-2018 3.01 0.31 0.42 638
28-02-2018 3.76 0.31 0.39 609
Average 3.45 0.31 0.41 631
Standard deviation 0.56 0.01 0.02 21
Cajones wetland 25-12-2017 3.03 0.36 0.45 670
30-12-2017 2.67 0.36 0.48 701
09-01-2018 2.54 0.36 0.48 710
14-01-2018 2.96 0.34 0.48 707
18-02-2018 3.09 0.39 0.49 716
23-02-2018 2.82 0.37 0.50 729
28-02-2018 3.08 0.38 0.48 705
Average
2.88 0.37 0.48 705
Standard deviation
0.20 0.02 0.01 17
Orientales wetland 25-12-2017 10.34 0.35 0.44 659
30-12-2017 9.06 0.35 0.47 691
09-01-2018 8.72 0.34 0.47 692
14-01-2018 10.05 0.34 0.48 703
18-02-2018 11.14 0.39 0.50 724
23-02-2018 10.30 0.38 0.51 734
28-02-2018 11.09 0.39 0.48 710
Average 10.10 0.36 0.48 702
Standard deviation 0.86 0.02 0.02 23
Table 5-3. Average NDVI, NDVI’ and ETa,NDVI calculated from the seven Sentinel-2 products.
Figure 5-24. Annual ETa,NDVI map estimated using the time-averaged data from the seven
satellite images used.
Estimated actual evapotranspiration Ela.Novi (mm/year)
□ <a 624 □ 624 - 778 1!!!!!!1 778 - 932 • 932 - 1086 • , 1086
154
Annex XIII
64
5.4 Soil characterization
5.4.1 Peat depth determination
During the field work carried out in November 2018, a soil auger was used at the
Quebrada Negra wetland, more specifically at the soil auger location shown in Figure
4-7. The soil auger was driven until it was impossible to continue, due to the presence of
boulders, coarse gravel, consolidated rock or other hard material. A peat depth of 6.6 m
was obtained, the depth at which rock was found.
5.4.2 Soil particle distribution
Soil particle distribution tests were performed on the five samples from P1, the six
samples from P2 and the 14 samples extracted with the soil auger. The results from the
P1 samples are presented in Table 5-4 and Figure 5-25, the results from P2 are
presented in Table 5-5 and Figure 5-26, and the results from the 14 samples collected
from the material extracted with the soil auger are presented in Table 5-6, Table 5-7,
Table 5-8 and Figure 5-27. The soil particle size distribution was made following the
Unified Soil Classification System (USCS), and coarse-grained soils were also
classified for their particle size distribution curve. According to the USCS soil
classification, well-graded sand (SW), silty sand (SM) and clayey sand (SC) were
found. The USCS soil classification chart can be found in Appendix D. For some
samples, especially those collected at depths of less than 2 m at the middle of the
wetland, the test could not be performed due to the large proportion of organic material.
Sample number M1* M2* M3* M4* M5
Sample name P1_S1* P1_S2* P1_S3* P1_S4* P1_S5
Soil distribution ASTM (mm)
Gravel % (#4-3") (4.75-75mm) - - - - 0 %
Sand % (#200-#4) (0.075-
4.75mm) - - - - 30 %
Fines % (clay &
silt)
(< #200) (<0.075mm) - - - - 70 %
USCS soil classification - - - - Fines**
*Soil particle distribution test couldn’t be performed at the sample due to high organic material content
(grass and roots).
**There is not enough information to determine whether there is more clay or silt in the sample.
Table 5-4. Soil particle size distribution from P1 samples.
Annex XIII
155
65
Figure 5-25. P1 sample particle size distribution curve.
Sample number M6* M10 M8 M7 M9 M11
Sample name P2_S1* P2_S2 P2_S3 P2_S4 P2_S5 P2_S6
Soil distribution ASTM (mm)
Gravel % (#4-3") (4.75-75mm) - 0 % 2 % 7 % 5 % 0 %
Sand % (#200-#4) (0.075-4.75mm) - 67 % 90 % 89 % 68 % 69 %
Fines % (clay & silt) (< #200) (<0.075mm) - 33 % 8 % 4 % 27 % 31 %
USCS soil classification - SW SW-SM/SC** SM/SC** SW SW
*Soil particle size distribution test could not be performed for the sample due to high organic material
content (grass and roots).
**There is not enough information to determine whether there is more clay or silt in the sample.
Table 5-5. Soil particle size distribution from P2 samples.
Figure 5-26. P2 samples soil particle size distribution curve.
100%
90%
80%
g 70%
~ 60%
~
.". 50%
I 40%
~ CL 30%
20%
10%
0%
10 0.1 O.lll
Particle size (mm)
• Pl_Sl O Pl_S2 0 Pl_Sl P1_54 - Pl_SS
100%
90%
80%
i 70% .. -C~ 60%
~ .. 50%
I 40%
~ 30%
20%
10%
0%
10 0.1 0.01
Particle size (mm)
O P2_S1 --P2_S2 - P2_S3 - P2_S4 -+-P2_SS - P2_S6
156
Annex XIII
66
Sample number M12* M13* M14* M15 M16
Sample name SA_
30-50
SA_
100-120
SA_
170-190
SA_
204-234
SA_
234-260
Soil distribution ASTM (mm)
Gravel % (#4-3") (4.75-75mm) - - - 0 % 0 %
Sand % (#200-#4) (0.075-
4.75mm) - - - 75 % 77 %
Fines % (clay &
silt)
(< #200) (<0.075mm) - - - 25 % 23 %
USCS soil classification - - - SW SW
*Soil particle size distribution test could not be performed for the sample due to high organic material
content (grass and roots)
Table 5-6. Soil particle size distribution from the soil auger hole samples (30-260 cm depth).
Sample number M17 M18 M19 M20 M21
Sample name SA_
315-
325
SA_
325-345
SA_
345-
375
SA_
375-
405
SA_
405-
440
Soil distribution ASTM (mm)
Gravel % (#4-3") (4.75-75mm) 0 % 6 % 0 % 0 % 1 %
Sand % (#200-
#4)
(0.075-
4.75mm) 84 % 84 % 82 % 61 % 85 %
Fines % (clay &
silt)
(< #200) (<0.075mm)
16 % 10 % 18 % 39 % 14 %
USCS soil classification SW
SWSM/
SC*
SW SW SW
Table 5-7. Soil particle size distribution from the soil auger hole samples (260- 440 cm depth).
Sample number M22 M23 M24 M25
Sample name SA_
440-510
SA_
510-565
SA_
565-610
SA_
610-660
Soil distribution ASTM (mm)
Gravel % (#4-3") (4.75-75mm) 1 % 0 % 7 % 14 %
Sand % (#200-#4) (0.075-4.75mm) 86 % 91 % 83 % 69 %
Fines % (clay &
silt)
(< #200) (<0.075mm)
13 % 9 % 10 % 17 %
USCS soil classification SP SPSM/
SC*
SPSM/
SC* SW
Table 5-8. Soil particle size distribution from the soil auger hole samples (440-660 cm depth).
Annex XIII
157
67
Figure 5-27. Soil auger hole samples particle size distribution curve.
Taking into consideration the particle size distribution curves (Figure 5-27), it is
observed that the soil is getting coarser with depth.
High content of organic material was found for the P1 samples, located at the middle of
the Quebrada Negra wetland. For this reason, particle distribution tests could not be
performed for most of the samples taken at P1. The only P1 sample on which the test
was applied was P1_S5, which was at approximately 2 m depth.
High content of organic material was found for the P2 samples, located at the
downstream end of the Quebrada Negra wetland. Mostly sand particles were found,
with varying percentages of fines. The only P2 sample on which the test could not be
applied was P2_S1, which was near the surface.
The samples taken above 2 m depth at the soil auger hole showed mostly roots, sands
and fine soils. At the samples collected at 2 m or deeper, a smaller amount of roots was
found. A bigger percentage of gravels was found at 6 m depth. This is consistent with
the results obtained from P1, which were taken near to the soil auger hole.
5.4.3 Falling-head Permeability Test results
The Ks results for falling-head permeability tests carried out to the thin walled tube soil
samples from P1 and P2 pits are presented in Table 5-9 and Table 5-10. The values
presented in the tables below are the mean from three tests performed at each sample.
100%
90%
80%
l. . 70% C 60% 1 ~ SO% ::
~ 40%
~ 30%
20%
10%
0%
0 SA_30-50
....-SA_345-37S
10
0 SA_ 100-120
-+-SA_375-405
0 SA_ 170-190
-+-SA_ 405-440
Particle size (mm)
-+-SA_ 204-234
-+-SA_440-510
SA_234-260
- SA_Sl0-565
0.1
......... SA_ 315-325
-+-SA_565-610
......... SA_325-345
SA_610-660
0 .01
158
Annex XIII
68
Sample Ks (m/s) Ks (m/day)
P1_S50_V 9.717E-07 8.395E-02
P1_S50_H 1.662E-07 1.436E-02
P1_S150_V 1.723E-07 1.489E-02
P1_S150_H 1.280E-07 1.106E-02
Table 5-9. Ks results for pit P1 soil samples.
Sample Ks (m/s) Ks (m/day)
P2_S50_V 9.163E-08 7.917E-03
P2_S50_H disturbed sample disturbed sample
P2_S150_V 9.440E-07 8.156E-02
P2_S150_H 4.640E-08 4.009E-03
Table 5-10. Ks results for pit P2 soil samples.
The soil hydraulic conductivity results obtained from the Shelby tubes samples at pit P1
and P2 are in general low, with values that are typical of semi-pervious soils. The values
obtained from P1 samples rank between 8.4×10-2 and 1.1×10-2 m/day. The values
obtained from P2 samples rank between 7.9×10-3 and 8.2×10-2 m/day.
5.4.4 Field saturated hydraulic conductivity
The results of the estimation of the hydraulic conductivity are presented in Table 5-11.
Experimental fits highlighted in red have substantial problems that compromise the
validity of the estimates. Also, 40% of the valid results present specific storage values
below 10-7 m-1, which may suggest implausibly low values of porosity and
compressibility, and according to Butler (Butler, 1997), it is recommended that other
models such as Kansas Geological Survey (KGS) slug test model (Hyder et al., 1994)
are used. This should be further explored, especially for future measurements. Figure
5-28 shows different examples of the fits. Both a) and b) show good fits but in the case
of b) a considerable amount of recovery was not achieved. c) and d) present two
different cases where the shape of the experimental data does not resemble the type
curves, despite achieving an acceptable level of recovery. Repetition of the experiment
should also be considered to produce more reliable and representative parameters.
Considering only the slug tests that did not show problems, starting upstream, a
hydraulic conductivity that is characteristic of the lower end of semi-pervious soils
(Table 5-12) was measured at wells 01 and 03, with values of the order of 10-2 and 10-1
m/day respectively. Continuing in the downstream direction, slug tests performed on
wells 12, 13 and 14, located around the middle of the main grassland (Figure 4-26),
Annex XIII
159
69
evidenced soils with, again, hydraulic conductivity values of the order of 10-2 to 10-1
m/day. Wells 17, 20 and 22 show that this situation appears to be maintained until the
last portion (downstream) of the main grassland. Finally, the last well in the
downstream direction (well 25) evidences a change in soil characteristics towards soils
with higher hydraulic conductivity, with a value in the order of 100 m/day.
These results are consistent with the hydraulic conductivities obtained in the laboratory
from the Shelby tubes samples taken at pit P1 and P2. The hydraulic conductivity
obtained from the Shelby tubes samples at pit P1 is of the order of 10-2 m/day, while at
well 12M, the nearest well where the slug test was performed, the measured hydraulic
conductivity is 3.5×10-2 m/day. The values obtained from wells 13 and 14 are also of
the same order of magnitude. The values obtained from P2 samples lie between 10-3 and
10-2 m/day. These are lower than the values obtained from the surrounding wells (17, 20
and 21), but they are still relatively similar.
As explained above, by looking only at the successful slug tests, it appears that the
wetland has soils that fall under a semi-pervious classification, with a notable increase
in hydraulic conductivity in the soils at the downstream tail of the wetland area.
However, as is evidenced in Figure 5-29, the perturbation in the groundwater level
arising from the slug test at well 8Z takes substantially more time to stabilize than the
one arising from the slug test at well 12M. Therefore, one would expect a much lower
hydraulic conductivity at soils near well 8Z than those near well 12M. Moreover, results
obtained from the slug tests performed at 8Z, despite the limited validity of the test,
support the observations from the continuous measurements of the well, as the hydraulic
conductivity obtained is of 5.2×10-4 m/day. Assuming this to be correct, there would be
evidence of a zone near well 8Z, in the first portion of the main grassland (upstream
direction), exhibiting hydraulic conductivities two orders of magnitude lower than those
measured at the rest of the wetland, with values that are characteristic of impervious
soils. Furthermore, it is also interesting to point out that, according to UAV
photogrammetry, such as that of Figure 4-26, and observation during field campaigns,
superficial ponds and ephemeral surface discharge appear to be characteristic of the first
portion of the main grassland. The spatial distribution of the slug test results is
presented in Figure 5-30.
160
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70
Location Kr (m/s) Kr (m/day) Ss (1/m) Observations
25-S 2.20E-05 1.90E+00 3.30E-03
08Z-D 6.00E-09 5.18E-04 3.30E-03 Bad fit, 74% of recovery missing
07S-D 2.00E-08 1.73E-03 3.30E-04 Bad fit, 68% of recovery missing
05-D 5.50E-08 4.75E-03 3.30E-05 Bad fit, 39% of recovery missing
07A-D 1.50E-07 1.30E-02 3.30E-10 Bad fit, 36% of recovery missing
01-D 1.60E-07 1.38E-02 3.30E-07
12Z-D 1.50E-06 1.30E-01 3.30E-07
14A-D 7.00E-07 6.05E-02 3.30E-05
12M-D 4.00E-07 3.46E-02 3.30E-07
22-D 3.50E-07 3.02E-02 3.30E-05
14M-D 2.80E-07 2.42E-02 3.30E-01 Double stage recovery
18A-S 2.80E-07 2.42E-02 3.30E-10 Erratic data and low initial displacement
13Z-D 3.30E-07 2.85E-02 3.30E-05
17M-D 2.00E-07 1.73E-02 3.30E-05
19Z-D 4.00E-08 3.46E-03 3.30E-10 Bad fit, 86% of recovery missing
06A-S 4.00E-07 3.46E-02 3.30E-10 Erratic data and low initial displacement
20M-D 4.70E-07 4.06E-02 3.30E-04
03-D 1.50E-06 1.30E-01 3.30E-07
04-D - - - Impossible fit, 96% of recovery missing
02-S 2.00E-07 1.73E-02 3.30E-07 Erratic data and low initial displacement
Table 5-11. Slug test results summary. Each location is represented using the following code:
XXY-Z, where the XX number corresponds to the number of the piezometer (which indicates
relative position in the wetland and increases in the downstream direction), the Y letter
corresponds to the position of the piezometer relative to the northern or southern limits of the
wetland (as shown in Figure 4-26), and the Z letter indicates deep (D) or shallow (S) level (as
shown in Figure 4-20).
Annex XIII
161
71
Figure 5-28. Examples of slug test fits.
Field saturated hydraulic conductivity values for the 14M-D and 06A-S wells (Figure
5-28 c) and d), respectively) were estimated using only the beginning of the slug test
curves, before any abrupt change is observed. It was decided to use only a part of the
data because the change in slope could be due to a change in the soil composition.
log10 K (m/s) 0 1 2 3 4 5 6 7 8 9 10 11 12 13
Permeability Pervious Semipervious Impervious
Table 5-12. Typical values of soil hydraulic conductivity. Modified from Bear (Bear, 1988).
o• ...
0.8 0.8
01 0.1 ... 0.6
{ o-> { o.s
o., OA
0.3 o.3
o, o.,
0 \ 0.1
0 0
0.001 0.01 0 1 10 100 0.001 0.01 0.1 10 100
a) 25-S b) 01-D
.. 0.9
o~ ·~
0.1 0.7
0.6 0 .6
f O.S { O.S
0.4 0.4 .., 0.J .., o.,
01 0.1
0 0
""'' 0.001 0.0,. 0.1 10 100
c) 14M-D d) 06A-S
162
Annex XIII
72
Figure 5-29. Groundwater level continuous measurements at wells 8Z and 12M. Discontinuities
occurring during September in both plots correspond to the slug tests performed at both wells.
Figure 5-30. Spatial distribution of field saturated hydraulic conductivity. In red are presented
the values measured in shallow piezometers and in black those measured in deep piezometers.
.,; 4273
.;
g ~· ~
.:;
1 4272.8
'"iii'
3:
"O 4272.6 C:
::, e
\!)
Jul 24
.,; 42703 .;
427025 g ~
.:;
>
~
~ 42702
~
"O 4270.15 ~ C:
::, e
\!) 4270.1
Jul 24
Aug07
Aug07
sz
Aug21
12M
Aug21
(=--oeep
5ep04 Sep 18 Oct02
Sep04 Sep18 Oct02
s~
Annex XIII
163
73
5.4.5 Thermal properties
Table 5-13 presents the results of the nine measurements performed at the site of the
soil sensors installation. Even though the measurements were taken at sites with
different water saturation conditions and orientation, the results are similar and do not
suggest any kind of pattern.
K
W/(m·K)
C
MJ/(m³·K)
D
mm²/s
Uncovered
wall
0.475 3.625 0.131
0.510 4.381 0.116
0.521 4.743 0.110
Underwater
wall
0.521 4.743 0.110
0.507 5.289 0.096
0.511 5.188 0.099
Underwater
bottom
0.603 5.494 0.110
0.549 3.433 0.160
0.550 3.431 0.160
Table 5-13. Measurements of thermal properties of the soil.
5.5 Groundwater level monitoring
5.5.1 Spatial interpolation
Figure 5-31 and Figure 5-32 show the main grassland area of the Quebrada Negra
wetland, in which the surface water features and the different vegetation covers (Table
5-14) were visually identified from UAV photogrammetry captured during August
2018. The zones where an appearance of surface water is identified coincide with the
presence of dense Tussock grasses. It seems likely that this surface water is fed by
lateral spring sources (marked with a dashed yellow arrow), which are not evident from
the photograph alone. These springs appear to emerge from the basal slopes of the
ravine.
164
Annex XIII
74
Cover type Description
C1 Dense tussock grasses (Calamagrostis cf. ampliflora)
C2 Oxychloe andina bog cushion plants with Patosia clandestina
C3 Oxychloe andina with sparse and dried tussock Calamagrostis grasses
C4 Sparse Tussock grasses
Table 5-14. Different vegetation cover types identified from UAV photogrammetry captured
during August 2018. The vegetation cover types were identified by C. Latorre (Personal
Communication).
Figure 5-31 and Figure 5-32 also show examples of the contour maps of water level
elevation constructed from the groundwater level measurements, and the direction of the
vertical gradient at the individual monitoring locations. It is observed that there is a
lateral gradient favoring flow in a direction from the Quebrada Negra towards the Silala
River, i.e. from East to West.
Figure 5-31. Contour lines of groundwater levels (m.a.s.l.), at shallow piezometers, measured
during September 2018 at the main grassland of the Quebrada Negra wetland. Red circles
represent points where positive gradient (downwelling) was observed, blue circles represent the
points where negative gradient (upwelling) was observed and yellow circles represent points
where zero-gradient was observed. Surface channels observed in the wetland are identified as
light blue lines. Apparent surface water sources are marked with dashed yellow lines.
Cover type
CJ Cl CJ C3
CJ (2 CJ (4
Vertical gradient direction
• Upwelling
o Zero gradient
• Downwelling
Surface water channels
10 20
Meters
Annex XIII
165
75
Figure 5-32. Contour lines of groundwater levels (m.a.s.l.), at deep piezometers, measured
during September 2018 at the main grassland of the Quebrada Negra wetland. Red circles
represent points where positive gradient (downwelling) was observed, blue circles represent the
points where negative gradient (upwelling) was observed and yellow circles represent points
where zero-gradient was observed. Surface channels observed in the wetland are identified as
light blue lines. Apparent surface water sources are marked with dashed yellow lines.
Figure 5-33 shows the interpolated contours of the vertical hydraulic gradient, which
was calculated from the difference in the levels of the shallow and deep piezometers at
each location. Positive values mean that the shallow wells present higher levels than the
deep ones, which implies downwelling conditions. Negative vertical hydraulic gradients
represent the opposite, i.e., upwelling conditions. The spatially heterogeneous nature of
the vertical gradients in the main wetland area can be seen more clearly when looking at
the monitoring points in Figure 5-31 to Figure 5-33, where red shows the piezometer
locations where downwelling was observed, blue the locations of upwelling and yellow
the locations with zero gradient. It can be seen that: a) in the upslope (eastern) segment
of the ravine leading into the main wetland, an area of upwelling occurs, which then
leads to an area of downwelling; b) in the main areas of wetland vegetation in general
the vertical gradient of groundwater levels is mostly dominated by zero or positive
gradients (downwelling), but with localized areas of upwelling; and c) in the ravine
below the main area of wetland, in general, upwelling conditions occur.
Cover type
□ Cl CJ C3
CJ C2 CJ C4
Vertical gradient direction
• Upwelling
o Zero gradient
• Downwelling
-- Surface water channels
10 20
Meters
• • ,::·w
200 • •• -:•·'If -~--
166
Annex XIII
76
Figure 5-33. Vertical hydraulic gradient, calculated from well measurements. Positive
hydraulic gradients correspond to downwelling conditions, whereas negative hydraulic
gradients correspond to upwelling conditions.
Monitoring points
• Upwelling
o Zero gradient
• Downwelling
Vertical hydraulic
gradient (m/m)
- -0.5
CJ -0.25
CJ D
CJ 0.25
• o.5
Monitoring points
• Upwelling
o Zero gradient
• Downwelling
Vertical hydraulic
gradient (m/m)
- -0.5
CJ -0.25
CJD
CJ 0.25
• o.5
Monitoring points
• Upwelling
o Zero gradient
• Downwelling
Vertical hydraulic
gradient (m/m)
- -0.5
CJ -0.25
CJ D
CJ 0.25
- 0.5
600200
600)00
0
0
0
so 100
Meters
1'1All56111'.M-1~
so
Meters
so 100
Meters
1'1Alll61111M-1~
Annex XIII
167
77
5.5.2 Groundwater profiles
Five groundwater level profiles are used to show variability in the main wetland area in
more detail, four of which are transverse to the principal wetland slope and one in the
longitudinal direction. Figure 5-34 shows the location and distribution of the five
profiles presented in Figure 5-35 and Figure 5-36.
Figure 5-34. Map of transverse and longitudinal profiles.
168
Annex XIII
78
Figure 5-35. Groundwater level profiles from four transverse cross-sections, P1-P4.
4273
4272
4271
4270
P l
09Z 095
Pl'
09M 09F 09A
x: 600241
y: 7563680
x: 600241
y: 7563686
x: 600242
y: 7563692
x: 600242
y: 7563698
x: 600243
y: 7563704
x: 600243
y: 7563710
4271
4270
4269
4268
4267
P2
132
x: 600222
y: 7563678
P3
x: 600222
y: 7563684
x: 600222
y: 7563690
x: 600223
y: 7563696
13F
x: 600223
y: 7563702
x: 600223
y: 7563708
P2'
13A 1
P3'
4269
16A
4268
162 165 16M ----- 4267 I 4266
4265
I I I I I I
x: 600207
y: 7563677
x: 600207
y: 7563683
x: 600207
y: 7563689
x: 600208
y: 7563695
x: 600208
y: 7563701
x: 600208
y: 7563707
x: 600209
y: 7563713
P4
4267 -
4266
4265
4264
-
182 185
18~ ------------ --
-
I I I
x: 600199
y: 7563682
x: 600198
y: 7563688
x: 600198
y: 7563694
x: 600198
y: 7563700
Water-table levels (m.a.s.l.}
(09/11/2018)
-- Shallow Piezometer -- Deep Piezometer
18F
I
x: 600198
y: 7563706
P4'
18A
I
x: 600198
y: 7563712
Vertical exaggeration: 2x
Om 6m
• I
Annex XIII
169
79
Figure 5-36. Groundwater level longitudinal profile L1.
Figure 5-35 and Figure 5-36 present the cross-sections of the topography and watertable
levels measured at the deep and shallow piezometers in the main Quebrada Negra
wetland, based on the manual measurements carried out on 11 September 2018. The
position of each piezometer and the ground elevation were obtained by Real-time
kinematic (RTK) positioning, with an error of 10-15 cm in the position and of 15-20 cm
in the ground elevation. The interpolation was done using the Arcgis® software, using
the Topo to Raster tool. In this case, the interpolation is used to estimate the water-table
elevation and topography between known data points using a modified spline technique.
The Topo to raster interpolation takes advantage of the types of input data commonly
available and the known characteristics of elevation surfaces. This method uses an
iterative finite difference interpolation technique. It is optimized to have the
computational efficiency of local interpolation methods, such as inverse distance
weighted (IDW) interpolation, without losing the surface continuity of global
interpolation methods, such as Kriging and Spline (Hutchinson et al., 2011).
The cross-sections generally confirm the observations above, namely that the main
wetland is characterized by zero gradients and downwelling, with localized upwelling as
seen for locations 13F and 16F, for example.
L1
4276
4273
4270
4267
4264
4261
x: 600266
y: 7563699
06A
x: 600246
y: 7563701
Water table levels (m.a.s.l.)
(09/11/2018}
-- Shallow Piezometer -- Deep Piezometer
x: 600226
y: 7563702
x: 600206
y: 7563704
L1'
x: 600186
y: 7563705
Vertiull exaggeration: 2x
21M
Om 20m
170
Annex XIII
80
5.5.3 Continuous monitoring records
Finally, Figure 5-37 presents the records of the continuous monitoring of groundwater
level and shows that there are no major changes between June and September, although
there is some variability at daily and longer time scales.
The step changes recorded in some wells (Figure 5-37) are related to the slug tests
performed in those wells (Figure 4-26). Additionally, there are short periods (~2 days)
with missing data because the sensors were used to perform slug tests in other wells.
During these periods, the sensors were installed at different locations, and after the tests,
they were replaced in their original locations. This accounts for the discrete changes.
Sensors that present daily oscillations greater than the rest may have been out of the
water, perhaps due to the presence of ice in the wells.
It can be seen for example that location 14A shows an upwelling gradient. As can be
seen from Figure 4-26, this location lies at the northern edge of the wetland, at the base
of the adjacent hillslope.
5.5.4 Discussion
The overall picture that emerges from the monitoring of groundwater levels and
gradients in the Quebrada Negra wetland is one of complexity of groundwater flow
paths and strong spatial heterogeneity. The wetland exists because it is fed by
groundwater, and it is interesting to note that over much of the wetland, hydraulic
gradients show conditions that promote downwelling, rather than upwelling. It can be
seen that the springs that feed the wetland emerge at the edges of the wetland (in
particular at the southern lateral boundary, as well as the upslope ravine), and that
within the main wetland there are isolated locations where spring emergence occurs.
Within the main wetland there are distinct channels and perennial flows, which then
return subsurface, to flow as groundwater down the ravine towards the main Silala
River.
Annex XIII
171
81
Figure 5-37. Continuous monitoring of groundwater levels at specific points.
Vl
~
..E....
QJ
> QJ
I..
QJ
+-' m
~
'"O
C
::::I
0
I..
~
7A
4274 ~-----~------~------------~------~------~
4273.S
4273 1-
4272.S ~-------~-----~------~------~----,---~------~
Jul 24 Aug07 Aug21
sz
Sep04 Sep 18 Oct02
4273 ~-----~-------------------~------~------~
4272.8
4272.6
Jul 24 Aug07 Aug21
12M
Sep04 Sep 18 Oct02
4:::::~ ~~~~ ~ "· ·~j 4270.2 .
4270.lS f ~_,,_..._____..........,___.......__,,,_,,_,_.._....___==- ~
4270.1 ~-----~------~-----~------~------~------~
Jul 24 Aug07 Aug21
14A
Sep04 Sepl8 Oct02
4269.3 ~-----~-------------------~------~------~
4269.1
4269 ~-----~--------------------------~------~
Jul24 Aug07
Jul 24 Aug07
Aug21
14Z
Sep04
Aug 21 Sep 04
J --Deep Shallow I
Sep 18 Oct02
Sep 18 Oct02
172
Annex XIII
82
6. CONCLUSIONS
In this study, the transition from winter to spring of the meteorological conditions, the
vegetation cover and the groundwater levels of the Quebrada Negra wetland was
captured and analyzed. Temperature records show that daily maximum temperatures
vary between -3 and 17 °C, while the daily minima vary between -11 and 1 °C for the
study period. The temperatures slowly rise as winter ends and summer approaches.
Also, seven precipitation events were identified during the study period, which,
according to satellite images, correspond to snowfall events. However, analysis of
individual satellite images showed that there was abundant snow at Quebrada Negra
while the pluviometer remained reporting zero precipitation. This phenomenon probably
occurs due to the inherent limitations of pluviometers designed to capture rainfall.
Additionally, negative values of soil heat flux were observed during winter, which could
be attributed to the presence of snow on the surface and low temperatures in, and even
freezing of, the ground.
The NDVI was used as an indicator of active vegetation coverage, where it was
considered that NDVI > 0.2 corresponded to area covered by active vegetation. This
threshold was determined by visual inspection of satellite images. The analysis of the
satellite images used to investigate the spatial distribution of vegetation cover in the
Quebrada Negra (Chile), Cajones and Orientales (Bolivia) wetlands showed that NDVI
is higher in the middle of all the wetlands than at the edges. In general, the total area
covered by vegetation increased with time over the observational period (July to
November 2018), except for the Quebrada Negra wetland, in which the total area
covered by vegetation decreased in November.
High-resolution NDVI images show, for each of the three wetlands, that the distribution
of vegetation cover covers the flat area available and expands up the adjacent hillslopes
where slopes are less than approximately 15%. In the case of the cross sections of
Cajones and Orientales, it was observed that the maximum spatial coverage between the
months of July-2018 and November-2018 is greater than the average extent. However,
in the case of the Quebrada Negra wetland cross-section, the maximum and mean extent
do not vary significantly and cover the same transverse section. However, an increase in
vegetation cover in the Quebrada Negra wetland during the studied period was observed
in river cross sections located downstream and upstream of the studied cross section,
where the width of vegetation cover increased in the north-south direction. It should be
noted that the range of variation is limited to the Sentinel raster resolution (10 m), so
variations smaller than 10 m are not captured.
Annex XIII
173
83
The temporal evolution of area covered by active vegetation (NDVI > 0.2) for each
wetland was analyzed using low resolution but longer record length LANDSAT images.
These showed that the peak vegetation cover occurs between April and May and that
there is strong variability for all the sites, especially in the Cajones wetland, during the
December-May period. The area covered by vegetation obtained with the Sentinel-2
images is consistent with the historical average variation curves (1986-2017) obtained
by LANDSAT images. Nevertheless, the values obtained from Sentinel and LANDSAT
products are not directly comparable because the latter are less accurate.
Potential evapotranspiration was estimated using the FAO Penman-Monteith method,
and for the study period varies between ~0 and 5.72 mm/day on 14 June and 10
November respectively. As expected, ETo increases as the summer approaches.
Additionally, actual evapotranspiration was estimated at an annual time scale using the
Groeneveld et al. (2007) method.
The highest annual ETa,NDVI values were observed in the Cajones wetland (705
mm/year), while the lowest ones were observed in the Quebrada Negra wetland (631
mm/year). The estimated ETa,NDVI in the Orientales wetland was estimated to be 702
mm/year. Additionally, the mean water flow due to evapotranspiration was estimated to
be 0.7 L/s in the Quebrada Negra wetland, 0.6 L/s in the Cajones wetland and 2.3 L/s in
the Orientales wetland. The highest water loss to the atmosphere observed in the
Orientales wetland is due to its greater area of active vegetation, which is approximately
three times the area of the Cajones and Quebrada Negra wetlands during summer.
The sensitivity of the Groeneveld et al. (2007) method to the selection of the midsummer
NDVI (peak season NDVI) was analyzed. Using seven satellite images as
potential mid-summer NDVI map, the ETa standard deviation for all three wetlands was
of the order of ~20 mm/year. Additionally, Groeneveld et al. (2007) showed that their
method has residual errors that decrease as measured ETa increases, with error values on
the order of 3.5 – 16.9 % for ETa,NDVI estimates of the same magnitude as the ones
obtained in this study.
High content of organic material was found in the two pits excavated in the Quebrada
Negra wetland. For this reason, particle distribution tests could not be performed for all
the obtained samples. A very dense root system, sands and fine soils were found above
a depth of two metres, compared to deeper samples. Also, it was observed that the soil
gets coarser with depth.
The soil hydraulic conductivity results obtained from the falling head permeameter are
in general low (between 4.0×10-3 and 8.4×10-2 m/day), with values that are typical of
semi-pervious soils. In general, these results agree with the soil saturated hydraulic
conductivity measured with the slug tests. Although there is a general agreement, some
174
Annex XIII
84
slug tests results show hydraulic conductivity values that are characteristic of
impermeable soils in the main grassland. Despite the fact that measured hydraulic
conductivities show that the soil is semi-pervious to impervious, during the excavation
of the pits, they needed to be constantly drained, because the water level kept rising as
the excavation proceeded.
In the wetland as a whole, there are areas of upwelling at the upslope and downslope
boundaries, and there is evidence of spring flow emergence from the adjacent (Northern
and Southern) hillslopes. However, for the main grassland, the vertical hydraulic
gradient is mostly close to zero and dominated by positive gradients (downwelling).
Also, there is a groundwater gradient in a longitudinal direction down the Quebrada
Negra ravine towards the Silala ravine. Therefore, the evidence suggests a subsurface
flow that mainly follows the topography, with a small downwards component.
Nevertheless, some locations with positive gradients (downwelling) coincide with the
zones where small ponds and surface flows are observed and where the highest
measured hydraulic conductivities were reported. Additionally, it was observed that the
zones where an appearance of surface water is identified coincide with the presence of
dense Tussock grasses.
The overall picture that emerges from observed groundwater levels in the Quebrada
Negra wetland is one of complexity of groundwater flow paths and strong spatial
heterogeneity. The wetland exists because it is fed by groundwater, but over much of
the wetland, hydraulic gradients show conditions that promote downwelling, rather than
upwelling. The springs that feed the wetland emerge at the edges of the wetland (in
particular at the southern lateral boundary, as well as the upslope ravine), and within the
main wetland there are isolated locations where spring emergence occurs. Within the
main wetland there are distinct channels and perennial flows, which then return
subsurface, to flow as groundwater down the ravine towards the main Silala River.
Annex XIII
175
85
7. REFERENCES
Alcayaga, H., 2017. Characterization of the Drainage Patterns and River Network of
the Silala River and Preliminary Assessment of Vegetation Dynamics Using Remote
Sensing. (Chile’s Memorial, Vol. 4, Annex I).
Allen, R.G., Pereira, L.S., Raes, D. and Smith, M., 1998. Crop Evapotranspiration-
Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage,
Paper 56.
ASTM, 2007. Standard Test Method for Particle-Size Analysis of Soils D422-63.
ASTM International, West Conshohocken, Pennsylvania.
ASTM, 2015. Standard Practice for Thin-Walled Tube Sampling of Fine-Grained Soils
for Geotecgnical Purposes D1587M-15. ASTM International,West Conshohocken,
Pennsylvania.
Bear, J., 1988. Dynamics of Fluids in Porous Media. Dover Civil and Mechanical
Engineering Series. Dover, New York, pp. 800.
Butler, J.J., 1997. The design, performance, and analysis of slug tests. Lewis Publishers,
Boca Raton, Florida, pp. 262.
Chavez, P., 1996. Image-Based Atmospheric Corrections - Revisited and Improved
Photogrammetric Engineering and Remote Sensing. American Society of
Photogrammetry, 62, 1025- 1036.
Congedo, L., 2018. Semi-Automatic Classification Plugin Documentation. Technical
Report. Release 6.0.1.1. Available at: http://dx.doi.org/10.13140/RG.2.2.29474.02242/1
Cooper, H.H., Bredehoeft, J.D. and Papadopulos, I.S., 1967. Response of a Finite-
Diameter Well to an Instantaneous Charge of Water. Water Resources Research, 3(1),
263-269, doi:10.1029/WR003i001p00263.
Fetter, C.W., 1994. Applied Hydrogeology, Third Edition, Macmillan College
Publishing Company, United States.
Garcia, M., Raes, D., Allen, R. and Herbas, C., 2004. Dynamics of reference
evapotranspiration in the Bolivian Highlands (Altiplano). Agricultural and Forest
Meteorology, 125(1), 67-82.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D. and Moore, R., 2017.
Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing
Environment, 202, 18-27.
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Groeneveld, D.P. and Baugh, W.M., 2007. Correcting satellite data to detect vegetation
signal for eco-hydrologic analyses. Journal of Hydrology, 344, 135-145
doi:10.1016/j.hydrol.2007.07.001.
Groeneveld, D.P., Baugh, W.M., Sanderson, J.S. and Cooper, D.J., 2007. Annual
groundwater evapotranspiration mapped from single satellite scenes. Journal of
Hydrology, 344, 146-156.
Hall, D.K., Riggs, G.A. and Salomonson, V.V., 2006. MODIS/Terra Snow Cover 5-Min
L2 Swath 500m. Version 5. NASA National Snow and Ice Data Center Distributed
Active Archive Center. Boulder, Colorado, USA.
Head, K. and Epps, R., 2011. Manual of Soil Laboratory Testing. Volume II:
Permeability, Shear Strength and Compressibility Tests. Third Edition. Whittles
Publishing. Scotland, UK.
Herrera, C. and Aravena, R., 2019(a). Chemical and isotopic characterization of surface
water and groundwater of the Silala River transboundary basin, Second Region, Chile.
(Chile’s Reply, Vol. 3, Annex XI).
Herrera, C. and Aravena, R., 2019(b). Chemical characterization of surface water and
groundwater of the Quebrada Negra, Second Region, Chile. ( Chile’s Reply, Vol. 3,
Annex XII).
Hutchinson, M., Xu, T. and Stein, J., 2011. Recent Progress in the ANUDEM Elevation
Gridding Procedure. In T. Hengel, I. Evans, J. Wilson, and M. Gould (Ed.).
Geomorphometry, 2011, 19-22. Available at:
http://geomorphometry.org/HutchinsonXu2011.
Hyder, Z., Butler Jr., J., McElwee, C. and Liu, W., 1994. Slug tests in partially
penetrating wells. Water Resources Research, 30 (11), 2945-2957.
NTT DATA, and RESTEC, 2014. AW3D Standard DTM. Available at
http://aw3d.jp/en/.
Roy, D., Kovalskyy, V., Zhang, H., Vermote, E., Yan, L., Kumar, S. and Egorov, A.,
2016. Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized
difference vegetation index continuity. Remote Sensing Environment, 185, 57-70.
Samtani, N.C. and Nowatzki, E.A., 2006. Soils and Foundations. Reference Manual –
Volume I. National Highway Institute, US Department of Transportation, Federal
Highway Administration. Publication No. FHWA NHI-06-088.
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Sellers, P.J., Berry, J.A., Collatz, G.J., Field, C.B. and Hall, F.G., 1992. Canopy
reflectance, photosynthesis and transpiration. III A reanalysis using improved leaf
models and new canopy integration scheme. International Journal of Remote Sensing,
42, 187-216.
Sproles, E., Crumley, R., Nolin, A., Mar, E. and Lopez Moreno, J., 2018.
SnowCloudHydro-A new framework for forecasting streamflow in snowy, data-scarce
regions. Remote Sensing, 10(8), 1276, doi:10.3390/rs10081276.
Summer, D.M. and Jacobs, J.M., 2005. Utility of Penman–Monteith, Priestley–Taylor,
reference evapotranspiration, and pan evaporation methods to estimate pasture
evapotranspiration. Journal of Hydrology, 308(1), 81-104.
Tucker, C.J. and Sellers, P.J., 1986. Satellite remote sensing of primary production.
International Journal of Remote Sensing, 7, 1395-1416.
WMO, 2014. Guide to Meteorological Instruments and Methods of Observation. World
Meteorological Organization, Geneva, Switzerland. Available at:
https://library.wmo.int/index.php?lvl=notice_display&id=12407.
Yoder, R.E., Odhiambo, L.O. and Wright, W.C., 2005. Evaluation of methods for
estimating daily references crop evapotranspiration at a site in the humid southeast
United States. Applied Engineering in Agriculture, 21, 197-202.
Zhu, Z., Wang, S. and Woodcock, C. E., 2015. Improvement and expansion of the
Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and
Sentinel 2 images. Remote Sensing Environment, 159, 269-277.
Annex XIII
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88
APPENDIX A
PICTURES OF THE PITS
A-1 P1 middle of the stream
Annex XIII Appendix A
179
89
Annex XIII Appendix A
180
90
A-2 P2 downstream
Annex XIII Appendix A
181
91
APPENDIX B
SOIL SAMPLES FOR PEAT DEPTH DETERMINATION
Soil samples taken at the Quebrada Negra wetland for later particle distribution analysis
in the laboratory are presented below. The first 30 to 190 cm deep are in the body of this
report (see Figure 4-11).
Figure B-1. Soil samples between 204 and 325 cm deep in the Quebrada Negra wetland for peat
characterization.
Annex XIII Appendix B
MlS) SA_204-234 M16) SA_234-260 M17) SA_260-325
a.
QJ a. QJ
QJ a. ""O
QJ QJ -0 (1J E
E -0 u
u E LI)
st u N
M 0 M
N u:, I
I N LI)
st I .-<
0 st M
N M
N
182
92
Figure B-2. Soil samples between 325 and 405 cm deep in the Quebrada Negra wetland for peat
characterization.
Figure B-3. Soil samples between 405 and 565 cm deep in the Quebrada Negra wetland for peat
characterization.
Annex XIII Appendix B
C.
a.,
a.,
-0
E u
l/')
'SI('(')
I
l/')
N
('(')
M18) SA_325-345 . :· . . ..
. '
. 4. :
.;;;;;;;;;;.,_.,.
~
C.
a.,
a.,
-0
E
u
l/') ,-...
('(')
I
l/')
'SI-
('(')
C. a.,
a.,
-0
E u
0
.-i
l/')
I
0
'SI-""
M19) SA_ 345-375 ==:-----~ QUEBRADA NEGRA
OT 70
MUESTRA - 19
N0\12018
M22) SA_ 44 0-510
C.
a.,
a.,
-0
E u
l/')
0 v
i
l/') ,-...
('(')
C.
QJ
QJ
-0
E u
l/')
<.D
l/')
I
0
.-i
l/')
M20} SA_375-405 - .
.
M23) SA_Sl0-565 -.
.
183
93
Figure B-4. Soil samples between 565 and 660 cm deep in the Quebrada Negra wetland for peat
characterization.
Some pictures of the material extracted with the soil auger are shown below (from 0 to
260 centimetres depth).
Figure B-5. Pictures of the material extracted with the soil auger (from 0 to 260 cm depth).
Annex XIII Appendix B
M24) SA_SGS-570 M25) SA_570-660 -
a. a.
Q) Q)
Q) Q)
-0 -0
E E u u
0 0 r-- \.0
LI) \.0
LI) 0
\.0 r--
LI) LI)
184
94
APPENDIX C
DESCRIPTION OF SOIL SAMPLES COLLECTION FOR KS ANALYSIS AT
PITS P1 AND P2
Tables C-1 and C-2 give more details about the performance of soil samples collection
with the Shelby tubes at pit P1 and pit P2, respectively.
Sample Date Tube insertion
(min:sec)
Waiting period
(min:sec)
P1_S50_V** 22/11/2018 1:00* 6:00
P1_S50_H*** 23/11/2018 0:30 6:00
P1_S150_V** 23/11/2018 0:10 5:30
P1_S150_H** 23/11/2018 1:52 5:10
* the use of a sledge hammer was required to insert the tube into the ground.
** sampling was repeated 2 times.
*** sampling was repeated 3 times.
Table C-1. Undisturbed soil sampling in pit P1 at the Quebrada Negra wetland.
Sample Date Tube insertion
(min:sec)
Waiting period
(min:sec)
P2_S50_V 22/11/2018 2:45* 5:36
P2_S50_H 22/11/2018 4:12* 8:15
P2_S150_V 22/11/2018 2:45* 5:15
P2_S150_H*** 22/11/2018 0:15 5:00
* the use of a sledge hammer was required to insert the tube into the ground.
*** sampling was repeated 3 times.
Table C-2. Undisturbed soil sampling in pit P2 at the Quebrada Negra wetland.
Annex XIII Appendix C
185
95
APPENDIX D
USCS SOIL CLASSIFICATION CHART
Table D-1. Soil classification chart (Samtani and Nowatzki, 2006).
Annex XIII Appendix D
Criteria for Assigning Group Symbols and Group Names Soil Classitication
Using Laboratory Tests"
COARSE-GRAINED SOILS (Sands and Gravels) - more than
Group Grnup
50% retained on No. 200 (0.075 nun) sieve
Symbol Name~
FINE-GRAINED (Silts and Clays) - 50% or more passes the
No. 200 (0.075 nun) sieve
GRAVELS CLEAN
e ll 2:. 4 and I :S Cc :S 3e GW
Well-graded
GRAVELS gravef
More than
Cll < 4 and/or l > Cc > 3• GP
Poorly-graded
50%of < 5% fines grave{
coarse
GRAVELS Fines classify as ML or MH GM Silty gravel'·!"·"
Fraction
retained on WITH FINES Clayey
No.4 Fines classify as CL or CH GC aravelf.i.h
> 12% of fines0 0
Sieve
SANDS CLEAN
e ll 2:. 6 and I :s Cc :s 3• SW
Well~graded
SANDS Sand'
50% or more
Cll < 6 and/or I > Cc > 3• SP
Poorly-graded
of coarse < 5% finesd sand'
fraction SANDS WITH Fines classify as ML or MH SM Silty sand!"·''·'
passes No. 4 FINES
Sieve Clayey Fines classify as CL or CH SC
> 12% finesd
sandg.,h.i
PI > 7 and plots on or above
CL Lean cla/·1.111
SILTS AND Inorganic "A" line'
CLAYS PI < 4 or plots below "A" line' ML Silt"·1
•
111
Organic
Liquid limit
Organic
Liquid limit - overdried < O.
75 OL
cla'?-'·m,u
less than 50 Liquid limit - not dried Oroanic
sil~.1.m.o
SILTS AND
Inorganic
PI plots on or above "A" line CH Fat clav"·1.m
CLAYS PI plots below "A" line MH Elastic silt"·1
•
111
Liquid limit - oven dried <
0
_
75
Organic
Liquid limit
Organic OH
cla?-'·111·P
50 or more Liquid limit - not dried
Organic
silf.l,m.q
Highly
Primary organic matter, dark in color, and
fibrous Pt Peat
on?:anic soils
organic odor
186
Annex XIII Appendix D
96
Table D-1 (continued). Soil classification chart (Samtani and Nowatzki, 2006).
NOTES:
a
b
C
cl
e
f
g
h
k
111
n
0
p
Based on the material passing the 3 in (75 nun) sieve.
If field sample contained cobbles and/or boulders, add "with cobbles and/or boulders"
to group name.
Gravels with 5 to 12% fines require dual symbols:
GW-GM, well-graded gravel with silt
GW-GC, well-graded gravel with clay
GP-GM, poorly graded gravel with silt
GP-GC, poorly graded gravel with clay
Sands with 5 to 12% fines require dual symbols:
SW-SM, well-graded sand with silt
SW-SC, well-graded sand with clay
SP-SM, poorly graded sand with silt
SP-SC, poorly graded sand with clay
C = D60 Cc = (D30/
" D10 (D10) (D60)
[Cu: Unifonnity Coefficient; Cc: Coefficient of Curvature]
If soil contains 2: 15% sand, add "with sand" to group name.
If fines classify as CL-ML, use dual symbol GC-GM, SC-SM.
If fines are organic, add "with organic fines" to group name.
If soil contains 2: 15% gravel, add " with gravel" to group name.
If the liquid limit and plasticity index plot in hatched area on plasticity chart, soil is a
CL-ML, silty clay.
If soil contains 15 to 29% plus No. 200 (0.075 111111), add "with sand" or "with gravel,"
whichever is predominant.
If soil contains 2: 30% plus No. 200 (0.075mm), predominantly sand, add "sandy" to
group name.
If soil contains 2: 30% plus No. 200 (0.075 mm), predominantly gravel, add "gravelly"
to group name.
PI 2: 4 and plots on or above "A" line.
PI < 4 or plots below "A" line.
Pl plots on or above "A" line.
PI lots below "A" line.
Annex XIV
SERNAGEOMIN (National Geology and Mining Service),
2019. Geology of the Silala River Basin: An Updated
Interpretation
187
188
Annex XIV
189
GEOLOGY OF THE SILALA RIVER BASIN: AN UPDATED
INTERPRETATION
Edmundo Polanco (DSc)
Project Geologist of the Regional Geology Unit of the Department of Basic
Geology
January 2019
190
Annex XIV
GLOSSARY
This glossary of geologic terms is based on the glossary in Earth: An Introduction to
Geologic Change, by S. Judson and S.M. Richardson (Englewood Cliffs, NJ, Prentice
Hall, 1995) and The Encyclopedia of Volcanoes, by H. Sigurdsson (editor) (Academic
Press, USA, 2015). Where possible, definitions conform generally, and in some cases
specifically, to definitions given in Robert L. Bates and Julia A. Jackson (editors),
Glossary of Geology, 3rd ed., American Geological Institute, Alexandria, Virginia,
1987.
39Ar/40Ar method: A different method that was invented to supersede K/Ar method, to
be more accurate.
40K/40Ar method: A method used for the dating of potassium-bearing rocks by using
the ratio of radioactive 40K to its daughter, 40Ar.
Absolute time: Geologic time expressed in years before the present.
Amphibole: Any of a large group of minerals composed of a silicate joined to various
metals, such as calcium, magnesium, iron, or sodium. Hornblende is a mineral of the
amphibole group.
Andesite: A fine-grained volcanic rock of intermediate composition, consisting largely
of plagioclase and one or more mafic minerals.
Aquifer: Geological formation capable of storing, transmitting and yielding exploitable
quantities of water.
Autobreccia: Clastic aggregate generated as a by-product of lava flowage.
Autoclastic facies: Clastic facies generated by nonexplosive fragmentation
accompanying lava effusion and flowage. Autobreccia and hyaloclastite are the two
most common kinds of autoclastic facies.
Annex XIV
191
Bedding: A collective term used to signify presence of beds, or layers, in sedimentary
rocks and deposits.
Bedding plane: Surface separating layers of sedimentary rocks and deposits. Each
bedding plane marks termination of one deposit and beginning of another of different
character, such as a surface separating a sandstone bed from an overlying mudstone bed.
Rock tends to breaks or separate readily along bedding planes.
Bedrock: Any solid rock exposed at the Earth’s surface or overlain by unconsolidated
material.
Breccia: A clastic rock in which the gravel-sized particles are angular in shape and
make up an appreciable volume of the rock.
Biotite: Dark mica, K(Mg,Fe)3AlSi3O10(F,OH)2, a common silicate mineral. It is brown
to black with shiny surfaces, and like all micas, it splits into very
thin flakes along its one perfect cleavage.
Clastic: Refers to rock or sediments made up primarily of broken fragments of preexisting
rocks or minerals.
Crater: 1. A steep-walled, usually conical depression at the summit or on the flanks of
a volcano, resulting from the explosive ejection of material from a vent. 2. A bowlshaped
depression with a raised, overturned rim produced by the impact of a meteorite
or other energetic projectile.
Crystal: The multi-sided form of a mineral, bounded by planar growth surfaces, that is
the outward expression of the ordered arrangement of atoms within it.
Dacite: An extrusive igneous rock type or magma of intermediate silica content
falling between that of andesite and rhyolite; typically contains
phenocrysts of potassium feldspar and plagioclase feldspar, and may contain
quartz, biotite, and hornblende.
Debris flow: Fast-moving, turbulent mass movement with a high content of both water
and rock debris. The more rapid debris flows rival the speed of rock slides.
192
Annex XIV
Dome: An uplift or anticlinal structure, roughly circular in its outcrop exposure, in
which beds dip gently away from the center in all directions.
Extrusive: Pertaining to igneous rocks or features formed from lava released on the
Earth’s surface.
Foot wall block: The body of rock that lies below an inclined fault plane.
Glassy: A texture of extrusive igneous rocks that develops as the result of rapid cooling,
so that crystallization is inhibited.
Hanging wall block: The body of rock that lies above an inclined fault plane.
Igneous rock: A rock that has crystallized from a molten state.
Ignimbrite: Pyroclastic density current deposit composed of variable proportions
of pumice, ash, and lithic clasts usually used for deposits formed during large
explosive eruptions.
Lava: Molten rock that flows at the Earth’s surface.
Lava dome: A steep-sided rounded extrusion of highly viscous lava squeezed out from
a volcano and forming a dome-shaped or bulbous mass above and around the volcanic
vent. The structure generally develops inside a volcanic crater.
Magma: Molten rock, containing dissolved gases and suspended solid particles. At the
Earth’s surface, magma is known as lava.
Mineral: A naturally occurring inorganic solid that has a well-defined chemical
composition and in which atoms are arranged in an ordered fashion.
Normal fault: A geological fault where the hanging wall block has moved downwards
relative to the foot wall block.
Pyroclastic: Pertaining to clastic material formed by volcanic explosion or aerial
expulsion from a volcanic vent.
Pyroclastic flow: A dense, hot (sometimes incandescent) cloud of volcanic ash and gas
produced in a Pelean eruption.
Annex XIV
193
Reverse fault: A dip-slip fault on which the hanging wall block is offset upward
relative to the foot wall block.
Rhyolite: A fine-grained silica-rich igneous rock, the extrusive equivalent of granite.
Rift (graben): A valley caused by extension of the Earth’s crust. Its floor forms as a
portion of the crust moves downward along normal faults.
Rock: An aggregate of one or more minerals in varying proportions.
Sedimentary rock: Rock formed from the accumulation of sediment, which may
consist of fragments and mineral grains of varying sizes from pre-existing rocks,
remains or products of animals and plants, the products of chemical action, or mixtures
of these.
Silica: Silicon dioxide (SiO2) as a pure crystalline substance makes up quartz and
related forms such as flint and chalcedony. More generally, silica is the basic chemical
constituent common to all silicate minerals and magmas.
Stratovolcano (composite volcano): A volcano that is composed of alternating layers
of lava and pyroclastic material, along with abundant dikes and sills. Viscous,
intermediate lava may flow from a central vent. Example: Mt. Fuji in Japan.
Terrace: A relatively flat surface along a valley, with a steep bank separating it either
from the floodplain, or from a lower terrace.
Texture: The general appearance of a rock as shown by the size, shape, and
arrangement of the materials composing it.
Tuff: A general term for all consolidated pyroclastic rock. Not to be confused with tufa.
Vesicle: A cavity in a lava, formed by the entrapment of a gas bubble during
solidification of the lava.
Vesicular: A textural term applied to an igneous rock containing abundant vesicles,
formed by the expansion of gases initially dissolved in the lava.
194
Annex XIV
Volcanic ash: The dust-sized, sharp-edged, glassy particles resulting from an explosive
volcanic eruption.
Volcanic breccia: Clastic aggregate composed predominantly of angular volcanic
clasts.
Volcano: A vent in the surface of the Earth, from which lava, ash, and gases erupt,
forming a structure that is roughly conical.
Welded tuff: A pyroclastic rock in which glassy clasts have been fused by the
combination of the heat retained by the clasts, the weight of overlying material, and hot
gases.
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195
TABLE OF CONTENTS
1. INTRODUCTION........................................................................................................1
1.1. Context............................................................................................................1
1.2. Location of the study area...............................................................................2
1.3. Regional geology............................................................................................4
2. STRATIGRAPHY IN CHILE .....................................................................................5
3. INTERPRETATION AND MAPPING OF THE GEOLOGY OF THE ESTIMATED
GROUNDWATER CATCHMENT IN BOLIVIA AND CHILE ....................................9
4. EROSION AND DEPOSITION IN THE SILALA PALAEO-VALLEY.................13
5. STRUCTURAL EVOLUTION..................................................................................14
6. INACALIRI-APAGADO VOLCANIC CHAIN .......................................................18
7. SUMMARY AND CONCLUSIONS.........................................................................19
8. REFERENCES...........................................................................................................20
APPENDIX A
APPENDIX B
APPENDIX C
APPENDIX D
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Annex XIV
1
1. INTRODUCTION
1.1. Context
In 2017 Servicio Nacional de Geología y Minería (SERNAGEOMIN) remapped the
Chilean area included in the topographic catchment of the Silala River (see Figure 1).
This work was requested by the Dirección Nacional de Fronteras y Límites (DIFROL)
of the Ministry of Foreign Affairs, Mrs. Ximena Fuentes, and involved the production
of a report on the geological evolution of the Silala River basin (SERNAGEOMIN,
2017).
Over the period 2017 to 2018 a significant number of further geological investigations
of the Silala topographic basin have been carried out, which have enabled a better
understanding of the geology of the area. Additional information has been gained from
re-examination of drill cuttings, new radiometric dates, re-interpretation of geophysical
data, and further fieldwork, together with examination of several reports recently made
available that were cited in support of the Bolivian Counter-Memorial (BCM) in the
dispute before the International Court of Justice over the status and the use of the waters
of the Silala (Chile v. Bolivia). These reports were unavailable before November 2018
and have enabled comparisons between information gained by Servicio Nacional de
Geología y Minería(SERGEOMIN) in Bolivia and that gained by SERNAGEOMIN in
Chile.
In the light of this evolution of knowledge, the DIFROL requested an updated report on
the geology of the transboundary basin of the Silala River, including the review of the
geology of an extended groundwater catchment area in Bolivia, which would be aimed
at deepening the hydrogeological knowledge of this basin.
This report was elaborated under the supervision and instruction of Professors Denis
Peach and Howard Wheater.
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197
2
Figure 1. Location of study area, showing the Silala River basin (outlined in black) and the
extended groundwater catchment (shown in green). The international border between Chile and
Bolivia is shown in red.
1.2. Location of the study area
The Silala River basin is located in the volcanic arc of the high Andean Mountain
Range in the Second Region of Chile (Antofagasta Region) and the Department of
Potosí of Bolivia, approximately 100 km NE from the city of Calama (Figure 1). In
particular, the Silala River basin crosses the border between Chile and Bolivia.
,, ✓ C
•
, ~-
Vo/can
S.a n Pablo l'o. 1-. ·
' Vol , ' ~,i,~ )"'.
San.Pe - '>, t-o<: ,,
, , • .. ,._~ C"-9.
San .P edro , ro Lai/a-i' r1-: ..... .'1..' -
; '(g San Peq: Cerro; de Co an
o • r ,
-·~ ;ro-lnaca l
., odelG
-anir
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, 1~· -
------ .__,μ---<-~ - ,. --~ • _....,..-~--, '.bo/Jo
- JO~ -•-, - 45( J.,
t 15
Kilometers
Mercato~ Mljection, WGS 84
,I.,
;-_
198
Annex XIV
3
Figure 2. Synthesis of geology for the region in which the Silala River basin is located. Solid black line
corresponds to the topographic catchment area of the Silala River and solid green line is the Silala River basin
groundwater catchment.
9.·_, ·.•;· o~ ~ ~ •.....
C.06 ' · 0 " .. ' .
00-\ ~ ~ ♦ -: ••
o ~ -n ~, \\:i ·---.-... -.
Q ••
\ ..
... SI LALA RIVER ..... .
·. 'TOPOGRAPHIC ·
. . ·. CATCHMENT
·.·.; ·
Miocene Volcanic Rocks
Pliocene-Pleistocene
Volcanic Rocks
Silala lgnimbrite
Cabana lgnimbrite
Non-consolidate deposits
SILALA RIVER BASIN
GROUNDWATER
. CATCHMENT ./
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199
4
1.3. Regional geology
The regional geology is shown in Figure 2. The oldest rocks that are exposed in the
region are sequences of ignimbrites whose volume is considerable. These are
chemically evolved rocks (dacites and rhyolites) that filled depressions and valleys in
the existing relief. The radiometric ages found for these rocks indicate that at least two
similar geological events took place in the region, their ages being 10.71 Ma (Lower
Río San Pedro Ignimbrite: Ar/Ar in biotite; Salisbury et al., 2011) and 8.33 Ma (Sifón
Ignimbrite: average Ar/Ar; Salisbury et al., 2011). These dated rocks represent part of a
series of voluminous and extensive volcanic events that affected this part of the
Highland region (Altiplano) (Salisbury et al., 2011). These ignimbrites form the oldest
geological rocks in the Silala River basin area (labelled undifferentiated basement in
Figure 4, SERNAGEOMIN, 2017). Ignimbrites are deposited from explosive volcanic
eruptions. These volcanoes extrude a mix of volcanic gases, molten rock and ash in a
highly fluid pyroclastic flow. They flow under gravity at speeds of at least 100 km/hour
and are very destructive (Wilson and Houghton, 2000).
From 6.2 Ma (Polanco, 2012) several stratovolcanoes formed on the ignimbrite bedrock
from underlying magma chambers. These have intermediate to more evolved
compositions (andesites and dacites) that have been identified in the north of the basin,
forming a volcanic chain spanning more than 30 km in a NW-SE direction (Cerro
Lailai, Cerros de Colana and Cerro Inacaliri o del Cajón (henceforth Cerro Inacaliri):
5.4-5.8 Ma; K-Ar in total rock; Rivera et al., 2015), as well as in the South as an
isolated volcano (Cerro Negro dated to 6.2 Ma; Polanco, 2012) (Figure 2). The volcanic
products associated with these eruptive centers are mainly lava flows and domes and are
referred to as Volcanic Sequences of the Upper Miocene/Pliocene.
Subsequently, at 4.12 Ma (U-Pb in zircon), the Cabana Ignimbrite was deposited in the
Altiplano. This was a voluminous and highly evolved deposit and filled much of the
pre-existing topography. Volcanic activity continued to develop several eruption centers
located SW of the Quebrada Negra (see Figure 4), giving rise to the Volcanic Sequences
of the Upper Pliocene (2.6 Ma) and the Inacaliri volcano (Cerro Inacaliri) (1.48 Ma),
including Volcanic Sequences of the lower Pleistocene, and, in the south, an intense and
episodic volcanism began along the volcanic chain called Paniri-Toconce, which is over
20 km long and also is aligned in a NW-SE (N130°E) direction (Polanco, 2012), the
most recent activity of which corresponds to a lava flow from the Paniri Volcano
(150 ka; Polanco, 2012) (Figure 2).
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Annex XIV
5
Lastly, the most recent volcanic activity in the area corresponds to pyroclastic fall
deposits (630 ka; Blanco and Polanco, 2018) that resulted from an eruption of the Chao
Dome (see Figure 2).
2. STRATIGRAPHY IN CHILE
The interpretation of the geology of the area of the Silala Rivermade in
SERNAGEOMIN 2017, with information then available, recognized four main volcanic
lithological units. Further mapping, field observation and radiometric dating of dacitic
lavas found outcropping in the Silala ravine downstream of the Quebrada Negra have
led to the inclusion of a fifth lithological unit (Volcanic Sequences of the Upper
Pliocene) in the stratigraphy of the Silala River basin in Chile. The radiometric age
determinations that have been used to help construct the stratigraphy are listed in Table
1.
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201
6
Sample UTM
N
UT
M E Method Material Age
(Ma) Unit Reference
RSP12t 7.563.
439
596.
708 Ar/Ar biotite 630±31
0 ka** Pyroclastic fall deposit Blanco and
Polanco, 2018
No inf. No inf. No
inf. K-Ar biotite 1.48
±0.02*
Volcanic sequences of
the Lower Pleistocene
Almendras et al.,
2002
AL-197 7.566.
976
594.
878 Ar/Ar groundm
ass
1.612
±0.018
Volcanic sequences of
the Lower Pleistocene
Sellés and
Gardeweg, 2017
RSP16d 7.563.
146
595.
801 Ar-Ar plagiocla
se
1.61
±0.08*
*
Silala Ignimbrite Blanco and
Polanco, 2018
No inf. No inf. No
inf. K-Ar biotite 1.74
±0.02*
Nlsg-Volcanic
sequences of the Lower
Pleistocene
SERGEOMIN,
2003
RSP13
D
7.563.
561
596.
648 K-Ar groundm
ass 2.6±0.4 Volcanic sequences of
the Upper Pliocene
SERNAGEOMIN,
2017
No inf. No inf. No
inf. K-Ar biotite 3.2±0.4
*
Ntpg-Ignimbritas Silala
(Bolivian)
SERGEOMIN,
2017
RSP14
D
7.563.
554
596.
534 U-Pb zircon 4.12
±0.08 Cabana Ignimbrite SERNAGEOMIN,
2017
No inf. No inf. No
inf. K-Ar biotite 5.84
±0.09*
MPv2-Volcanic
sequences of the Upper
Miocene
Almendras et al.,
2002
No inf. No inf. No
inf. K-Ar biotite 5.8±0.4
*
MPv2-Volcanic
sequences of the Upper
Miocene
Almendras et al.,
2002
No inf. No inf. No
inf. K-Ar biotite 6.04
±0.07*
Volcanic sequences of
the Upper Miocene
SERGEOMIN,
2003
RSP50d 7.563.
302
600.
110 U-Pb zircon
6.63
±0.06*
*
Volcanic sequences of
the Upper Miocene
Blanco and
Polanco, 2018
No inf. No inf. No
inf. K-Ar biotite 6.6±0.5
*
Nis-3-Silala
Ignimbrites (Bolivian)
SERGEOMIN,
2017
No inf. No inf. No
inf. K-Ar biotite 7.8±0.3
*
MPvl-Silala
Ignimbrites (Bolivian) Ríos et al.,1997
Table 1. Compilation of the radiometric ages available of the Silala River area. * Ages from
Ríos et al,. (1997); Almendras et al., (2002); SERGEOMIN, (2003 and 2017). ** The age
reports are in the Appendix B.
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Annex XIV
7
The lithological units are presented in Figure 3 in order of the age of deposition, the
youngest being at the top. The bedrock lithologies and stratigraphic relationships are
also described below.
Volcanic Sequences from the Upper Miocene-Pliocene (MsPvd) ca 6.6 – 5.8 Ma
At this time a series of volcanic rocks including domes, lava domes, lava flows and
autoclastic breccia were emplaced. Their composition is mostly dacitic (Sellés and
Gardeweg, 2017). An available age date, located in Bolivian territory on the southeast
side of the Cerro Inacaliri, was 5.84±0.09 Ma (K-Ar in biotite; Almendras et al., 2002).
This unit was correlated with the older part of the Inacaliri and Apagado volcanic
structures, which have been dated at 5.8 Ma.
Cabana Ignimbrite (Piic) ca 4.12 Ma
The Cabana Ignimbrite is a medium to poorly welded tuff of white and white-pinky
color with vesicular and dacitic pumice (biotite and amphibole) and subangular and
angular lithics dominated by an ash matrix. It is at least 70 m thick in Chile. The first
age for this unit was of <7.5 Ma (Layana and Aguilera, 2013). Before the 2017/18
investigations this was the oldest age determined in the area and for this reason the
Cabana Ignimbrite was thought to lie below the Volcanic Sequences of the Upper
Miocene-Pliocene. However a subsequent determination gave an age of 4.12 Ma, and so
in the SERNAGEOMIN report of 2017 the Cabana Ignimbrite was thought to form a
wedge in the Miocene-Pliocene Volcanic Sequence.
Figure 3. The updated integrated stratigraphic column of the Silala River area.
Glacial deposits
Pig ·ca.40 ·12 ky BP
Volcanicsequences ····· ·
of the Upper Pliocene
Psvd • ca. 2.6 Ma
Silo la riverravine
...... Alluvial Deposits from lhe Upper Pleistocene
Pis(,)
........ Terrace Ill: 11 · 8.5 ky BP
__ . _ ... . _ Vo lean ic Sequence~ from tlie Lowe, Pleistocene
Pliv·ca. l.6·1.1 Ma
•• T2 •••.•••.•.••. Terrace II: 8,430 cal yrs BP
(L,torre & Frugone, 2017)
• • n .......... Terrace I: 530-670 cal yrs BP
(Latorre & Frugone, 2017)
r-,- r- ........ . . Silala lgnimbrite
Pliis ·ca. 1.61 Ma
C.b,n, lgnimbrite ••···· •········· Allu,iol Deposits
co. 4.12 Ma h~--_,,-,.._~_,,,--,<1 from the Upper Pliocene• Lower Pleistocene
A A A A
....... Vol<anic S.quences
from the Upper Miocene· Pliocene
MsP\/d · "· 6.6 · 5.8 Ma
Annex XIV
203
8
Volcanic Sequences of the Upper Pliocene (Psvd) ca 2.6 Ma
These lavas lie above the Cabana Ignimbrite and are dacitic (biotite and amphibole) of
pale gray color and were dated at 2.6 Ma (SERNAGEOMIN, 2017). In
SERNAGEOMIN (2017) they were thought contiguous with earlier Miocene lavas, but
have since been observed directly underlying the Silala Ignimbrite (1.61 Ma in Blanco
and Polanco, 2018) in both a borehole (see Annex A) and in outcrop.
Silala Ignimbrite (Pliis) ca 1.61 Ma
The Silala Ignimbrite is a more or less horizontal welded tuff of pink color and andesitic
composition with distinct cooling units or flow levels that outcrops in the Silala River
ravine in Chile. The age interval of this unit had been estimated in SERNAGEOMIN
(2017) with reference to its stratigraphic relationships with the other deposits in the
sequence. It provides the ignimbrite cover to the dacitic lava flow of 2.6 Ma (see above)
and it is covered by an andesitic lava flow from the Inacaliri volcano dated at 1.48 Ma
(Almendras et al., 2002) in Bolivia. Thus the Silala Ignimbrite unit was thought to lie in
the age range 2.6-1.48 Ma. The new age date (see Table 1) of 1.61 Ma confirms its
stratigraphic position.
Pyroclastic Fall Deposits (PlH(pc)) ca 630-11 ka
These deposits comprise well-stratified fine to medium-grained ash found in the central
and southern parts of the Chilean study area. Recently an age of 630 ka has been
determined for the Pyroclastic Fall Deposits. These pyroclastic deposits outcropping in
the Silala basin are interpreted as being associated with an eruption of the Chao Dome.
In summary, the most important change to the stratigraphic interpretation in Chile is the
inclusion of a fifth lithological unit (Volcanic Sequences of the Upper Pliocene), which
is associated with volcanism with an age of 2.6 Ma, lying in between the Cabana
Ignimbrite, which has an age of 4.2 Ma, and the Silala Ignimbrite, recently dated at 1.61
Ma and found overlying Upper Pliocene lavas, confirming its position in the
stratigraphic column. The oldest rocks found in the basin in Chile are the Volcanic
Sequences of the Upper Miocene with an age of 6.6-5.8 Ma.
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Annex XIV
9
3. INTERPRETATION AND MAPPING OF THE GEOLOGY OF THE
ESTIMATED GROUNDWATER CATCHMENT IN BOLIVIA AND CHILE
It is important to understand the geology of the groundwater catchment in order to gain
a good understanding of both the regional and local hydrogeology. By utilizing the
geological maps of Ríos et al., (1997) and Almendras et al., (2002) by SERGEOMIN,
including all the radiometric ages available (see Table 1), and satellite images from
Google Earth, it has been possible to construct a geological map which includes this
extended catchment in Bolivia as shown in Figure 4, which is very similar to the version
of SERGEOMIN (2003). In developing the geological map presented in
SERNAGEOMIN (2017) neither the reports of SERGEOMIN nor their geological maps
were available to consult. They have been provided subsequent to the filing of the BCM
and were obtained after reading the DHI (2018) report, which referred to these reports
(SERGEOMIN, 2003 and 2017). Clearly, since access to Bolivia for field observation
and further petrographic study and radiometric dating was not possible, the compilation
map provided in Figure 4 has a greater uncertainty attached to it than would be the case
if this work, including fieldwork, had been possible.
A new geological section (NE-SW Profile), also shown in Figure 4, has been
constructed to visualize the geology with depth. The paucity of borehole information
limits the three-dimensional accuracy of geological knowledge and understanding.
Nevertheless, the compilation of Chilean and Bolivian data (radiometric dates; Table 1),
field observations available in Bolivian reports, and the Chilean mapping observations
would be expected to give the best understanding to date of the geology of the
groundwater catchment of the Silala River.
Annex XIV
205
10
Figure 4. (a) Map showing a compilation and interpretation of the geology of the Silala River
basin that includes the Bolivian territory and uses Bolivian maps and data (SERGEOMIN, 2003
and 2017). Blue line is the NE-SW profile (AB section) and green line is the NW-SE profile (CD
section). (b) NE-SW profile (AB section)*. For the CD section see Figure 11.
The major bedrock unit in the Bolivian part of the groundwater catchment was
previously interpreted by SERNAGEOMIN geologists as being the Cabana Ignimbrite,
as found in Chile (Piic) (Figure 5). However, new descriptions and radiometric age
dates available in the SERGEOMIN (2003 and 2017) reports have allowed the
recognition of several levels of tuffaceous deposit of a variety of ages (7.8, 6.02 and 3.4
Ma, see Table 1). These deposits have variable thicknesses and have variable amounts
of pumice lithics and ash, and different welding grades. They are lumped together on
* A fold-out version of this profile can be found in Peach and Wheater (2019).
SW
PIH(pc) -
□ Hf Fluvial deposits from the Holocene
D Ha Alluvial deposits from the Holocene
D PIH(pc) Pyroclastic fall deposits
D PIHa Alluvial deposits from the Upper Pleistocene-Holocene
D Pls(a) Alluvial deposits from the Upper Pleistocene
□ Pig Glacial deposits (Upper Pleistocene)
D PIiis Silala lgnimbrite (Pliocene-Pleistocene)
D Pliv(a) Volcanic Sequences from the lower Pleistocene (ca. 1.5 Ma)
D Pliv(b) Ryolithic lava dome (ca. 1.5 Ma)
□ Psvd
□ PIie
D Msvd
Volcanic Sequences from the Upper Pliocene (co. 2.6 Ma)
Cabana lgnimbrite (Lower Pliocene; co. 4.12 Ma)
Volcanic Sequences from the Upper Miocene (ca. 6.6-5.8 Ma)
SILALA RIVER BASIN
GROUNDWATER
/ CATCHMENT
Kilometers
MercatorPl'ojectlon,WGS84
= ,_
:~I!-l,~:~ __L _~:J~u_~=L... _:: .~..:1.....~... ~. ...,:-.._,.,.~~=-:-:-:--:-::=~-::-:--=-----~-"° ~1:~:,._:~/~-~-::_7-
~ r--i;-·'"--'• 7U.6Ma9'ffl)'les
NE
206
Annex XIV
11
the map in Figure 4 under the name of Cabana Ignimbrite (Piic) but may include
ignimbrites older than 4.12 Ma. Significantly, these reports identify three separate
ignimbrite deposits associated with two debris flows. A single debris flow has been
identified in Chile in a borehole close to the international border (see Appendix A) and
in outcrop near the Inacaliri Police Station (see Figure 5) and lying between the Silala
and Cabana Ignimbrites.
It would appear that the Silala basin was like a reservoir, which was successively filled
by pyroclastic flows, now recognized and mapped as ignimbrites from differing sources
and of differing ages, the oldest deposit being at least 7.8 Ma (Table 1).
Of these pyroclastic flows, from successive volcanic eruptions that filled or partially
filled the Silala basin in Bolivian territory over several million years, at least two
crossed the line of the Chile-Bolivia international border to the west. These flows
surmounted the topographic high that formed the volcanic chain of Inacaliri and
Apagado volcanoes (Figure 2), and can been seen in Chile (Figure 5). In both cases, the
source of these two pyroclastic flows is interpreted as being in the east within Bolivian
territory because their thicknesses tend to decrease to the west.
Figure 5. Two different pyroclastic deposits of ignimbrites exposed in Chilean territory, near
the Inacaliri Police Station. Silala Ignimbrite (Pliis) above, Cabana Ignimbrite (Piic) below,
separated by a thin debris flow (alluvial flow deposit) (see Figure 7).
The ages of the ignimbrites in Chile (4.12 and 1.61 Ma) are very well defined, as are
their stratigraphic positions and physical relationships with other units. The upper
Annex XIV
207
12
ignimbrite (in Chile called the Silala Ignimbrite) has an age of 1.61 Ma and overlies, in
places, a dacitic lava flow of 2.6 Ma (Volcanic Sequences of the Upper Pliocene)
(Figure 6), while the lower ignimbrite has an age of 4.12 Ma and is covered by the
Volcanic sequences of the Upper Pliocene in places. From the Bolivian reports
(SERGEOMIN, 2003 and 2017) it appears that in Bolivian territory there are three
separate ignimbrites with associated debris flows. In Chile there are two ignimbrite
flows that have been recognized, which are separated by a single debris flow (or alluvial
flow). It would seem logical that the Chilean ignimbrite flows can be correlated with the
upper two in Bolivia (Nis-2 and Nis-3; Nis is an abbreviation of Neogene Ignimbrites
Silala). It is not possible that the upper ignimbrite, which has an age 1.61 Ma in Chile
could also have an age of 7.8 Ma in Bolivia. So, this ignimbrite with this much older
age must have been deposited earlier and in Chile perhaps might be found at depth
beneath both Silala and Cabana Ignimbrites. Here there is a major difference in
geological interpretation between that discussed in SERGEOMIN (2003 and 2017) and
in this report.
Figure 6. Silala Ignimbrite (Pliis) (1.61 Ma) covers the dacitic lava flow of 2.6 Ma
(Volcanic Sequences of the Upper Pliocene, Psvd).
208
Annex XIV
13
In summary the interpretation of the solid geology of the Silala area in this report, which
is based on the most complete information to date, is that there are at least three
ignimbrite deposits to be found in the Silala extended groundwater catchment, only two
of which outcrop in Chile with an interbedded debris flow and in places separated by
Pliocene dacitic lavas. The radiometric dating and field observations for this provide
very good confirmation.
4. EROSION AND DEPOSITION IN THE SILALA PALAEO-VALLEY
In two localities along the Silala River in Chile it is possible to recognize the upper and
lower ignimbrites (Silala and Cabana, respectively) with a debris flow deposit (or
alluvial flow deposit) lying between them. One of the locations is near the Inacaliri
Police Station (Figure 7), where the debris flow thickness is 20 cm, while close to the
international border between Chile and Bolivia, in the borehole CW-BO (Arcadis, 2017;
SERNAGEOMIN, 2017, see Appendix A), the debris flow deposit (an alluvial deposit)
was found to have a thickness of 13 metres. The distance between both localities is
about 4.5 km and the difference in altitude about 300 metres, indicating a significant
change in a small distance. The thinning toward the lower end of the Silala ravine and
the associated fining of the sedimentary grain size suggests flow from what is now
Bolivian territory down the proto Silala River valley towards the southwest
(SERNAGEOMIN, 2017).
Figure 7. Outcrop showing the upper and lower ignimbrites (Silala and Cabana ignimbrite,
respectively) with a thin fluvial deposit between them, exposed in Chilean territory near the
Inacaliri Police Station.
Annex XIV
209
14
Over the time between the deposition of the two ignimbrites in Chilean territory (upper
and lower ignimbrites), a period of approximately 2.5 Million years, there is no
geological record (volcanic or sedimentary) in the Chilean part of the basin, except for
the small debris flow. This gap in deposition suggests that a dynamic environment with
intense processes of minor deposition (fluvial deposits and debris flows) and high
erosion occurred along the Silala palaeo-valley. This suggests that a fluvial system, of
higher energy than at present, functioned in this area at that time.
5. STRUCTURAL EVOLUTION
In Chilean territory to the south west of the Silala extended catchment, it is possible to
recognize an alignment of volcanic centres in a NW-SE direction (Paniri-Toconce
volcanic chain: 1.6 Ma to 150 ka, see Figure 2). This direction is coincident with the
graben system in the area (the Apacheta dome (1.43 Ma to 50 ka) to the NW of the
Silala basin). Both lineaments are consistent with extension in the NE-SW direction.
Although this structural configuration gave rise to the volcanism mentioned above, it is
likely to have provided the plane of weakness for much earlier volcanism because the
NW-SE Miocene volcanic chain (6.8-5.4 Ma) can also be seen along a similar line (see
Figures 1 and 2).
There is an alignment of volcanic centres, including Cerrito Silala (Figures 2 and 4), in
a N-S direction, which has an age of 6.6-6.0 Ma and represents a local crustal extension
in the W-E direction. This extension is likely to have provided a plane of weakness that
favored the later structural configuration.
Along the Silala River a vertical normal fault has been mapped in Chile (Figure 8),
trending N-S, which affects the front of the dacitic lava flow of 2.6 Ma (Table 1)
(Volcanic Sequences of the Upper Pliocene) but does not affect the overlying ignimbrite
(Chilean-named Silala Ignimbrite). This structural configuration (Figure 8) occurred as
a response to the compression in a W-E direction such that the N-S inverse fault
(Cabana Fault) lifted and rotated the NE block with respect to SW (Figure 8). This
tectonic event occurred between 2.6 to 1.6 Ma.
Finally, an important morphological feature along the ravine of the Silala River is that
the level of the Chilean-named Silala Ignimbrite found on both sides of the ravine is
practically the same, as can be seen in the terraces (see Figure 9).
210
Annex XIV
15
Figure 8. Schematic structural profile in the SW sector of the Silala River.
Figure 9. Photography of an excellent example of no slip (relative movement) on both sides of
the ravine of the Silala River.
SW
Cabana lgnimbrite
MsPvd
Schematic structural model for reverse
fault contemporary with normal fault
N-S normal fault system (2.6-1.6 Ma),
morphologically is a "soft" flexure
Dacitic lava flow
(2.6 Ma)
NE
MsPvd
Annex XIV
211
16
The modelling (DHI, 2018) that was carried out in support of the BCM has employed
very high hydraulic conductivities along a fault which is mapped (SERGEOMIN, 2017)
as running from the Orientales wetland to the Cajones wetland and bending around to
follow the line of the Silala River to cross the international border into Chile (see Figure
10).
Figure 10. Amended map from DHI (2018) (BCM, Vol. 4, p.76, Figure 29) showing in red
(HGU 7) the postulated fault system.
No evidence, including displacements, fault gouge deposits or rock shattering has been
found in Chile to support the presence of such a fault (see Figure 9). No evidence of
displacement is provided by SERGEOMIN in their 2003 or 2017 reports, although they
do provide evidence of fractures and their directions. This fault has been assumed to be
-- Main canals
- HGU7
CJ HGU8
CJ HGUl
CJ HGU2
CJ HGU3
C]HGU4
- HGUS
C]HGU6
BOLIVIA
Area
Enlarged
212
Annex XIV
17
vertical by DHI (2018) yet such a fault system showing such outcrop sinuosity could
only occur in the manner assumed by DHI (2018) if it had a very low angle. There
appears no evidence for this.
A NW-SE profile through the Cajones ravine and Orientales areas (Figure 11) shows
the distribution of the Chilean-named Silala Ignimbrite, the debris flow and the Chileannamed
Cabana Ignimbrite as well as the line of the alignment of at least three centres of
Volcanic Sequence of Upper Miocene (Cerrito Silala to Cerro Silaguala) (see Figure 2).
Figure 11. NW-SE profile showing the Cajones and Orientales areas (CD green line in
Figure 4). The vertical black dashed line represents the axis of alignment of at least three
volcanic centres of Volcanic Sequences of Upper Miocene (Msvd). The Debris flow
(solid green color) that is showing to the SE of Cerrito Silala is interpreted. The legend
for the abbreviations can be found in Figure 4.
A simple explanation for the locations of the springs in Cajones and Orientales is that
they might be related to the intersection of the N-S alignment with projection of
regional NW-SE structure in Chilean territory (Miocene chain, graben, Pliocene-
Pleistocene volcanism).
Annex XIV
213
18
6. INACALIRI-APAGADO VOLCANIC CHAIN
The activity of the Inacaliri-Apagado volcanic chain was episodic but over a long
period. The high topography of these mountains formed a natural barrier that limited the
transport of the various pyroclastic flows that originated from the east in different
periods as demonstrated by at least three different ages as found for the ignimbrite
lithologies in Bolivian territory. One of the main differences in the geological
interpretation from that of the DHI (2018) report is the position of ignimbrite
recognized along the Silala River. The contact relationships as discussed in sections 2, 3
and 4 and the ages obtained (Table 1) are consistent with the schematic section shown
in Figure 12.
Figure 12. Schematic profile of Inacaliri-Apagado volcanic chain at the border of Chile and
Bolivia, including Cerrito Silala. The solid green color corresponds to the debris flow deposit
(or alluvial deposit).
Cerro loacaliri
~ D.tl("ili( tuff O>t • t'lb~ CGbotio Js,iimt:mte
c:=J D.K·nc: and aridcs1r.c lavas
~ Ande.itit LUH (bl • p,<): Si.law fs,mi,, re
- And...u.site .-00 b..1s..-.:tic andesilt- ta,...J'.
VolC8n Apagado
1111 Moruines / &h~~11 {Wl:po,;,t,;
Gi.K"1'
w.ner
214
Annex XIV
19
7. SUMMARY AND CONCLUSIONS
A variety of further investigations have been carried out to improve the knowledge of
the geology of the groundwater catchment area of the Silala River. These have included
new radiometric dates for rock deposits found in Chile, new field observations in Chile,
re-interpretation of drill cuttings from boreholes drilled in Chile, and examination of
Bolivian reports and map data. From this work a revised map of the groundwater basin,
a revised stratigraphy for the area and a three-dimensional conceptual understanding of
the geology of the Silala groundwater catchment have been developed.
The major conclusions are that the Ignimbrite succession is comprised of at least three
deposits that are associated or interbedded with debris flow deposits. These rocks were
deposited over a period from 7.8 Ma to 1.61 Ma but included long periods between the
deposition of the ignimbrites during which high energy fluvial erosional processes took
place. It is proposed that the pyroclastic flows that formed the ignimbrites were
restricted in their south-westward flow into what is now Chile by the Inacaliri-Apagado
volcanic chain and this topographic high held back much of the pyroclastic flow until it
overtopped this ridge.
New radiometric dates have shown that two separate sequences of dacitic volcanism
outcrop and in places the younger deposits (Pliocene dacitic lavas) are found between
the Cabana and Silala Ignimbrites in Chile.
There appears no evidence in Chile for the major fault system invoked by DHI (2018)
and used in their integrated model, and the sinuosity of this system appears highly
implausible.
Annex XIV
215
20
8. REFERENCES
ARCADIS, 2017. Detailed hydrogeological study of the Silala River. (Chile’s
Memorial, Vol. 4, Annex II).
Almendras, A.O., Balderrama Z.B., Menacho L.M. and Quezada C.G., 2002. Mapa
Geológico Hoja Volcán Ollagüe, escala 1:250.000. Mapas Temáticos de Recursos
Minerales de Bolivia. SERGEOMIN, Bolivia.
Blanco, N., and Polanco E., 2018. Geology of the Silala River Basin, Northern Chile.
Servicio Nacional de Geología y Minería (SERNAGEOMIN). (Appendix C).
Danish Hydraulic Institute (DHI), 2018. Study of the Flows in the Silala Wetlands and
Springs System. (Bolivia’s Counter-Memorial, Vol. 4, Annex 17).
Latorre, C. and Frugone, M., 2017. Holocene sedimentary history of the Río Silala
(Antofagasta Region, Chile). (Chile’s Memorial, Vol. 5, Annex IV).
Layana, S. and Aguilera, F., 2013. Stratigraphy of three new ignimbrites from Altiplano
Puna Volcanic Complex, northern Chile. In Actas GEOSUR 2013, 171-172, Viña del
Mar, Chile.
Polanco, E., 2012. Geología a escala 1:50.000 del área de la Cadena Volcánica Paniri-
Toconce, Provincia del Loa, Región de Antofagasta. (Chile’s Memorial, Vol. 5,
Annex VIII, Appendix D).
Ríos, H., Baldellón, E., Mobarec, R. and Aparicio, H., 1997. Mapa Geológico Hojas
Volcán Inacaliri y Cerro Zapaleri, escala 1:250.000. Mapas Temáticos de Recursos
Minerales de Bolivia, SGM Serie II-MTB-15B. SERGEOMIN.
Rivera, G., Morata, D.and Ramírez, C., 2015. Evolución Vulcanológica y Tectónica del
Área del Cordón Volcánico Cerro del Azufre – Cerro de Inacaliri y su Relación con el
Sistema Geotérmico de Pampa Apacheta, II Región de Antofagasta, Chile, XIV
Congreso Geológico de Chile, La Serena.
Salisbury, M.J., Jicha, B., de Silva, S., Singer, B., Jiménez, N. and Ort, M., 2011.
44Ar/39Ar chronostratigraphy of Altiplano-Puna volcanic complex ignimbrites reveals
the development of a major magmatic province. Geological Society of America Bulletin,
123, 821–840.
Sellés, D. and Gardeweg, M., 2017. Geología del área Ascotán-Cerro Inacaliri, Región
de Antofagasta. Servicio Nacional de Geología y Minería, Carta Geológica de Chile,
Serie Geología Básica 190, 1 mapa, escala 1:100.000. Santiago. (Chile’s Memorial,
Vol. 6, Appendix G)
SERGEOMIN, 2003. Estudio de cuencas hidrográficas, Cuenca manantiales del Silala,
Cuenca 20. Proyecto de Integración Regional, Departamento de Geología y Recursos
216
Annex XIV
21
Minerales, Servicio Nacional de Geología y Minería (SERGEOMIN), Bolivia. (Chile’s
Reply, Vol. 2, Annex 94).
SERGEOMIN, 2017. Proyecto Mapeo Geológico-Estructural del área circundante al
manantial del Silala, Departamento de Potosí. Convenio Interinstitucional, Servicio
Geológico Minero (SERGEOMIN)-DIREMAR. La Paz, Bolivia. (Appendix D).
SERNAGEOMIN, 2017. Geology of the Silala River Basin.. (Chile’s Memorial, Vol.
5, Annex VIII).
Wilson, C. and Houghton, B., 2000. Pyroclast Transport and Deposition. In: Sigurson,
H., Houghton, B., Mc Nutt, S., Ryme,r H., Stix, J. (eds.), Encyclopedia of Volcanoes,
San Diego CA, Academic Press, pp. 545-554.
217
22
APPENDIX A
STRATIGRAPHIC COLUMN OF BOREHOLES MW-DQN, PW-UQN AND
CW-BO
Annex XIV Appendix A
A BOREHOLE CODE
N
CW-BO
t
, ...,. :···(,... MW~OON
o.s 1km
(m) MW-DQN (m) PW-UQN
0 .,
. . . . . .. . ~
20 . . . . . . . . . . 20 ~ .: ~S~d-:.: Pliis l ... . .. . .
40 . .
LEGEND
GJ
.. . . .. .
Fluvial deposits (Holocene)
Gravels, sands and silts.
Alluvial deposits (Holocene)
Gravels, sands and silts.
40
PPla
60 j Piic
80
Sllala lgnlmbrite (Pliocene-Pleistocene) (ca. 1.61 Ma)
Pyroxene andes~ic tuff, moderately welded, with large pumice and abundant
young angular lithic fragments.
Alluvial deposits of Upper Pliocene • Lower Pleistocene
Volcanic Sequences of Upper Pliocene (ca. 2.6 Ma)
Domes, lava domes. Dacites with biotite and amphibole, ooarse porphyritic
texture, reddish grey in colour, locally having now banding.
Cabana lgnimbrite (Lower Pliocene) (ca. 4.12 Ma)
Crystal luff poorly to moderately welded, biotite and phenocrysts amphibole, with
abundant pumice towards its roof.
(m) CW-BO
0
20
Pliis
40
PPla
60
80
Piic
100
117
218
Annex XIV
219
23
APPENDIX B
AR/AR AND U-PB AGE REPORTS OF RADIOMETRIC DATING
Annex XIV Appendix B
220
Servicio Nacional de Geología y Minería
Subdirección Nacional de Geología
Departamento de Laboratorios
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
SDNG
UNIDAD DE GEOLOGIA ISOTOPICA
INFORME 40Ar/39Ar Nº 019/2017 ARGUS VI
Sr. Edmundo Polanco
Annex XIV Appendix B
SERNAGEOMIN
Ministerio de Mineria
Gobierno de Chile
221
Annex XIV Appendix B
National Geology and Mining Service
National Sub-directorate of Geology
Department of Laboratories
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
SDNG
ISOTOPIC GEOLOGY UNIT
40Ar/39Ar REPORT Nº 019/2017 ARGUS VI
Mr. Edmundo Polanco
SERNAGEOMIN
Ministerto de Mineria
Gobierno de Chile
222
Muestra Nº Análisis Material Edad Integrada ± 2σ
Edad Plateau ±
2σ
Edad Isoc. Inversa ±
2σ
RSP-12d 13983-01 Biotita 830 ± 350 ka 630 ± 310 ka 2000 ± 1700 ka
GEOCRONOLOGIA ARGUS VI
En el presente informe se encuentran contenidos los resultados y análasis realizados a las muestras
que se detallan en la precedente tabla resumen:
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Annex XIV Appendix B
z .!!
~ a 2 ~
"C "' 0 "z ' ~
ffi :g
"' "' •
223
Annex XIV Appendix B
Sample Nº Analysis Material Integrated Age ± 2σ Plateau Age ± 2σ Inverse Isochron
Age ± 2σ
RSP-12d 13983-01 Biotite 830 ± 350 ka 630 ± 310 ka 2000 ± 1700 ka
This report contains the results and analyses conducted on the samples that are detailed in the
preceding summary table:
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
ARGUS VI GEOCHRONOLOGY
2 ~
~ :E u
0 ~ "' ..,
I.!) 0 c,: 2 ~ "' :g ""'' ..., •
224
Muestra : RSP-12d
Material : Biotita
Nº interno : 13983-01
Análisis de Step Heating
Edad integrada: 830 ± 350 ka
Edad Plateau: 630 ± 310 ka
Pasos en el Plateau: 5/8 (85.2% de 39Ar)
MSWD Plateau: 0.69
Análisis de Isócrona Inversa
Edad Isócrona: 2000 ± 1700 ka
Pasos: 5/8 (63 % de los pasos)
Intercepto 40/36: 292.4 ± 3.9
MSWD Isócrona: 0.074
Comentarios:
GEOCRONOLOGIA ARGUS VI
Todas las edades son concordantes. No se aprecia la presencia de argón heredado. Se recomienda usar la
edad obtenida con el plateau.
*********************************************
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Annex XIV Appendix B
aw,IJ ap ou1a1qo~
---
eJJaU!WaP0!Jal5!U!W
NIL'\103!llfNH3S -
225
Annex XIV Appendix B
Sample : RSP-12d
Material : Biotite
Internal Nº : 13983-01
Step Heating Analysis
Integrated Age: 830 ± 350 ka
Plateau Age: 630 ± 310 ka
Steps at the Plateau: 5/8 (85,2% of 39Ar)
Plateau MSWD: 0,69
Inverse Isochron Analysis
Isochron Age: 2000 ± 1700 ka
Steps: 5/8 (63 % of the steps)
40/36 Intercept: 292 ± 3.9
Isochron MSWD: 0.074
Comments:
ARGUS VI GEOCHRONOLOGY
All ages are concordant. The presence of inherited argon has not been observed. It is recommended to use
the age obtained with the plateau.
*********************************************
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box: 10465 and 1347, Post 21- SANTIAGO – CHILE
226
Departamento de Laboratorios Servicio Nacional de Geología y Minería GEOCRONOLOGIA ARGUS VI
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
40Ar/39Ar Step-Heating Spectrum for Run 13983-01 (RSP-12d)
-4
-2
0
2
4
6
8
% 40Ar*
-0.4
-0.2
0
0.2
0.4
0.6 Cl/K
-20
-10
0
10
20
30
Ca/K
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
-6,000
-4,000
-2,000
0
2,000
4,000
6,000
8,000
10,000
Apparent Age (ka)
A
0.40 B
0.60 C
0.80 D
1.00
E
1.20
F
1.40 G
1.70
H
2.00
Integrated Age = 830 ± 350 ka
630 ± 310 ka (49.2%, MSWD = 0.69, p = 0.60, n = 5)
Data at 2-sigma, results at 2-sigma
Cumulative %39Ar Released
Annex XIV Appendix B
... ...
- _[_ ~
-
~
-
-
... ...
227
Annex XIV Appendix B
ARGUS VI GEOCHRONOLOGY
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
¥
0
ca
~
<1>
Cl
<(
"E
~
"a'.
a.
<(
0.6
0.4
0.2
-0.2
-0.4
10,000
8.000
6,000
4,000
2,000
-2,000
-4,000
-6,000
I
0.40
A
0 10 15 20
'°Arf'Ar Step-Heating Spectrum for Run 13983-01 (RSP-12d)
630 ± 310 ka (49.2%, MSWO = 0.69, p = 0.60, n = 5)
I I I
0.80 1.00
0.60 C D
B
Integrated Age = 830 ± 350 ka
25 30 35 40 45 50 55 60 65 70 75
Cumulative %"Ar Released
I I
Data at 2-sigma, results at 2-sigma
I
It 1.70 I 1.40 G
F
1.20
E
2.00
H
80 85 90 95 100
-2
-4
30
20
~0
~
7.
10 0
~
-10
-20
228
76 s Total
Material: Biotita 36 s Rise
A 0.4 7.19E-14 1915.24 0.13 24.75 0.03 1.61 0.02 0.08 0.03 6.482 0.017 0.02 0.0 0.2 32 506 0.43 0.14 0.010 0.003
B 0.6 5.16E-14 1373.70 0.11 24.01 0.03 1.24 0.02 0.04 0.03 4.637 0.012 0.27 0.15 0.14 379 357 0.21 0.14 0.010 0.003
C 0.8 4.90E-14 1305.05 0.11 26.67 0.03 1.23 0.02 0.01 0.03 4.393 0.012 0.54 0.27 0.13 661 323 0.05 0.13 0.009 0.002
D 1.0 3.92E-14 1044.76 0.10 22.68 0.03 1.02 0.02 0.02 0.03 3.509 0.009 0.76 0.35 0.12 872 309 0.10 0.15 0.010 0.003
E 1.2 2.74E-14 730.88 0.08 16.05 0.03 0.69 0.02 0.01 0.03 2.456 0.007 0.69 0.31 0.13 784 324 0.1 0.2 0.006 0.004
F 1.4 1.33E-14 355.60 0.06 8.01 0.03 0.33 0.02 0.03 0.03 1.179 0.004 2.07 0.92 0.15 2285 375 0.5 0.4 0.002 0.008
G 1.7 1.48E-14 395.61 0.06 11.42 0.03 0.42 0.02 0.00 0.03 1.294 0.004 3.31 1.15 0.11 2852 276 0.0 0.3 0.009 0.006
H 2.0 4.91E-16 13.08 0.05 0.36 0.03 0.02 0.02 0.02 0.03 0.0439 0.0008 1.61 0.6 0.8 1457 2005 6 10 0.05 0.18
630 155
Interpolation 77 s Total
37 s Rise
1 3.4 4.71E-14 1255.68 0.13 109.90 0.05 1.44 0.02 0.01 0.03 0.0158 0.0007 99.63 11.366 0.006 28.201 0.014 0.01 0.03 0.0024 0.0006
GEOCRONOLOGIA ARGUS VI
40Ar/39Ar Step-Heating Data for Run 13983-01; RSP-12d
Cl/K ± σ
Cl/K ± σ
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
N Power
(W)
40Ar
(moles)
40Ar
(fA)
39Ar
(fA)
± σ
(ka)
± σ39 (fA)
38Ar
(fA)
± σ38 (fA)
37Ar
(fA)
± σ37 (fA)
36Ar
(fA) Ca/K ± σ
N Power
(W)
40Ar
(moles)
40Ar
(fA)
± σ40 (fA)
39Ar
(fA)
± σ39 (fA)
38Ar
(fA)
± σ
(Ma) ± σ38 Ca/K ± σ (fA)
37Ar
(fA)
± σ37 (fA)
36Ar
(fA)
± σ36 (fA) %40Ar*
Sample: RSP-12d J: 0.0013809 ± 0.0000003 D: 0.99969 ± 0.00003 Heating:
40Ar*/39Ark ± σ Age
(Ma)
± σ36 (fA) %40Ar* 40Ar*/39Ark
Hole: 4/21
Standart: FC D: 0.99900 ± 0.00003 Heating:
Hole: 4/21
Age: 28.201 Ma
Plateau Age (steps A-E ):
± σ Age
(ka)
± σ40 (fA)
Annex XIV Appendix B
229
Annex XIV Appendix B
76 s Total
Material: Biotite 36 s Rise
A 0.4 7.19E-14 1915.24 0.13 24.75 0.03 1.61 0.02 0.08 0.03 6.482 0.017 0.02 0.0 0.2 32 506 0.43 0.14 0.010 0.003
B 0.6 5.16E-14 1373.70 0.11 24.01 0.03 1.24 0.02 0.04 0.03 4.637 0.012 0.27 0.15 0.14 379 357 0.21 0.14 0.010 0.003
C 0.8 4.90E-14 1305.05 0.11 26.67 0.03 1.23 0.02 0.01 0.03 4.393 0.012 0.54 0.27 0.13 661 323 0.05 0.13 0.009 0.002
D 1.0 3.92E-14 1044.76 0.10 22.68 0.03 1.02 0.02 0.02 0.03 3.509 0.009 0.76 0.35 0.12 872 309 0.10 0.15 0.010 0.003
E 1.2 2.74E-14 730.88 0.08 16.05 0.03 0.69 0.02 0.01 0.03 2.456 0.007 0.69 0.31 0.13 784 324 0.1 0.2 0.006 0.004
F 1.4 1.33E-14 355.60 0.06 8.01 0.03 0.33 0.02 0.03 0.03 1.179 0.004 2.07 0.92 0.15 2285 375 0.5 0.4 0.002 0.008
G 1.7 1.48E-14 395.61 0.06 11.42 0.03 0.42 0.02 0.00 0.03 1.294 0.004 3.31 1.15 0.11 2852 276 0.0 0.3 0.009 0.006
H 2.0 4.91E-16 13.08 0.05 0.36 0.03 0.02 0.02 0.02 0.03 0.0439 0.0008 1.61 0.6 0.8 1457 2005 6 10 0.05 0.18
630 155
Interpolation 77 s Total
37 s Rise
1 3.4 4.71E-14 1255.68 0.13 109.90 0.05 1.44 0.02 0.01 0.03 0.0158 0.0007 99.63 11.366 0.006 28.201 0.014 0.01 0.03 0.0024 0.0006
GEOCRONOLOGIA ARGUS VI
40Ar/39Ar Step-Heating Data for Run 13983-01; RSP-12d
Cl/K ± σ
Cl/K ± σ
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
N Power
(W)
40Ar
(moles)
40Ar
(fA)
39Ar
(fA)
± σ
(ka)
± σ39 (fA)
38Ar
(fA)
± σ38 (fA)
37Ar
(fA)
± σ37 (fA)
36Ar
(fA) Ca/K ± σ
N Power
(W)
40Ar
(moles)
40Ar
(fA)
± σ40 (fA)
39Ar
(fA)
± σ39 (fA)
38Ar
(fA)
± σ
(Ma) ± σ38 Ca/K ± σ (fA)
37Ar
(fA)
± σ37 (fA)
36Ar
(fA)
± σ36 (fA) %40Ar*
Sample: RSP-12d J: 0.0013809 ± 0.0000003 D: 0.99969 ± 0.00003 Heating:
40Ar*/39Ark ± σ Age
(Ma)
± σ36 (fA) %40Ar* 40Ar*/39Ark
Hole: 4/21
Standard: FC D: 0.99900 ± 0.00003 Heating:
Hole: 4/21
Age: 28.201 Ma
Plateau Age (steps A-E ):
± σ Age
(ka)
± σ40 (fA)
ARGUS VI GEOCHRONOLOGY
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
230
Departamento de Laboratorios Servicio Nacional de Geología y Minería GEOCRONOLOGIA ARGUS VI
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Isochron for Run 13983-01 (RSP-12d)
0 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 0.020 0.022 0.024 0.026 0.028 0.030 0.032 0.034 0.036 0.038 0.040 0.042 0.044 0.046 0.048
0.00324
0.00325
0.00326
0.00327
0.00328
0.00329
0.00330
0.00331
0.00332
0.00333
0.00334
0.00335
0.00336
0.00337
0.00338
0.00339
0.00340
0.00341
0.00342
0.00343
0.00344
0.00345
0.00346
A
B
C
DE
F
G
H
Age = 2000 ± 1700 ka (84.6%)
40Ar/36Ar Int. = 292.4 ± 3.9
MSWD = 0.074, n = 5
Data at 1-sigma, results at 2-sigma
39Ar/40Ar
36Ar/40Ar
Annex XIV Appendix B
231
Annex XIV Appendix B
Departamento de Laboratorios Servicio Nacional de Geología y Minería GEOCRONOLOGIA ARGUS VI
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Isochron for Run 13983-01 (RSP-12d)
0 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 0.020 0.022 0.024 0.026 0.028 0.030 0.032 0.034 0.036 0.038 0.040 0.042 0.044 0.046 0.048
0.00324
0.00325
0.00326
0.00327
0.00328
0.00329
0.00330
0.00331
0.00332
0.00333
0.00334
0.00335
0.00336
0.00337
0.00338
0.00339
0.00340
0.00341
0.00342
0.00343
0.00344
0.00345
0.00346
A
B
C
DE
F
G
H
Age = 2000 ± 1700 ka (84.6%)
40Ar/36Ar Int. = 292.4 ± 3.9
MSWD = 0.074, n = 5
Data at 1-sigma, results at 2-sigma
39Ar/40Ar
36Ar/40Ar
ARGUS VI GEOCHRONOLOGY
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
232
Isochron Data for 13983-01A to 13983-01H
Run ID Status 40Ar*/39Ar (36/40) isoch %± (39/40) isoch %± Correl 36/39 Group
13983-01A OK 0.01279 0.003384 0.30 0.01294 0.13 0.007 1
13983-01B OK 0.15209 0.003375 0.30 0.01751 0.14 0.007 1
13983-01C OK 0.26512 0.003366 0.30 0.02047 0.12 0.008 1
13983-01D OK 0.35005 0.003358 0.30 0.02174 0.14 0.007 1
13983-01E OK 0.31455 0.003361 0.30 0.02199 0.21 0.005 1
13983-01F User omitted 0.91742 0.003314 0.30 0.02255 0.40 0.004 1
13983-01G User omitted 1.14540 0.003272 0.30 0.02891 0.27 0.005 1
13983-01H User omitted 0.58467 0.003330 2.20 0.02754 8.48 0.007 1
Sample ID Age [ka] M.S.E. (40/36) tr M.S.E. MSWD Prob n
RSP-12d 13983-01 2000 1700 292.4 3.9 0.074 9.74E-01 5
Departamento de Laboratorios Servicio Nacional de Geología y Minería GEOCRONOLOGIA ARGUS VI
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Isochron Data for 13983-01A to 13983-01H
Run ID Status 40Ar*/39Ar (36/40) isoch %± (39/40) isoch %± Correl 36/39 Group
13983-01A OK 0.01279 0.003384 0.30 0.01294 0.13 0.007 1
13983-01B OK 0.15209 0.003375 0.30 0.01751 0.14 0.007 1
13983-01C OK 0.26512 0.003366 0.30 0.02047 0.12 0.008 1
13983-01D OK 0.35005 0.003358 0.30 0.02174 0.14 0.007 1
13983-01E OK 0.31455 0.003361 0.30 0.02199 0.21 0.005 1
13983-01F User omitted 0.91742 0.003314 0.30 0.02255 0.40 0.004 1
13983-01G User omitted 1.14540 0.003272 0.30 0.02891 0.27 0.005 1
13983-01H User omitted 0.58467 0.003330 2.20 0.02754 8.48 0.007 1
Sample ID Age [ka] M.S.E. (40/36) tr M.S.E. MSWD Prob n
RSP-12d 13983-01 2000 1700 292.4 3.9 0.074 9.74E-01 5
Annex XIV Appendix B
233
Annex XIV Appendix B
Isochron Data for 13983-01A to 13983-01H
Run ID Status 40Ar*/39Ar (36/40) isoch %± (39/40) isoch %± Correl 36/39 Group
13983-01A OK 0.01279 0.003384 0.30 0.01294 0.13 0.007 1
13983-01B OK 0.15209 0.003375 0.30 0.01751 0.14 0.007 1
13983-01C OK 0.26512 0.003366 0.30 0.02047 0.12 0.008 1
13983-01D OK 0.35005 0.003358 0.30 0.02174 0.14 0.007 1
13983-01E OK 0.31455 0.003361 0.30 0.02199 0.21 0.005 1
13983-01F User omitted 0.91742 0.003314 0.30 0.02255 0.40 0.004 1
13983-01G User omitted 1.14540 0.003272 0.30 0.02891 0.27 0.005 1
13983-01H User omitted 0.58467 0.003330 2.20 0.02754 8.48 0.007 1
Sample ID Age [ka] M.S.E. (40/36) tr M.S.E. MSWD Prob n
RSP-12d 13983-01 2000 1700 292.4 3.9 0.074 9.74E-01 5
ARGUS VI GEOCHRONOLOGY
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
234
Equipamiento principal:
Condiciones de medición:
Criterios de análisis:
Un MSWD < 3 se considera aceptable
GEOCRONOLOGIA ARGUS VI
La definición de un plateau se determina por: ≥ 3 pasos de fusión consecutivos; ≥ 50% de 39Ar liberado en
el análisis; Error overlap a 2σ.
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
A continuación se detallan las particularidades de los análisis realizados a las muestras contenidas en el
informe:
Espectrómetro Argus VI (multicolector, CDD en 36Ar); Thermo Scientific
Láser de CO2 (10,6 μ); Photon Machines.
Cada dos o tres pasos se realizó una medición del background, el cuál fue descontado directamente en
las mediciones subsecuentes.
La irradiación de neutrones fue realizada en el reactor nuclear de la CCHEN por un periodo de 23 hrs,
existiendo un escudo de cadmio para las muestras.
Para determinar J de cada lugar de irradiación, se realizó un regresión polinomial de 21 standars
presentes en el disco de irradiación.
Annex XIV Appendix B
235
Annex XIV Appendix B
Main Equipment:
Measurement Conditions:
Analysis Criteria:
A MSWD < 3 is considered to be acceptable.
ARGUS VI GEOCHRONOLOGY
The definition of a plateau is determined by: ≥ 3 consecutive fusion steps; ≥ 50% of 39Ar released in the
analysis; Error overlap at 2σ.
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box: 10465 and 1347, Post 21- SANTIAGO – CHILE
The details of the analyses conducted to the samples contained in the report are given below:
Argus VI Spectrometer (multicollector, CDD in 36Ar); Thermo Scientific CO2 Laser (10,6 μ); Photon
Machines.
Every two or three steps, the background was measured, which was discounted directly in the
subsequent measurement.
The neutron irradiation was carried out at the CCHEN nuclear reactor during a 23-hour period: there was
a cadmium shield for the samples.
To determine J of each irradiation site, a polynomial regression was done of 21 standards present in the
radiation disk.
2 ~
~ :E u
0 {; "cC,>': 0C
2 t c,: :E "' 0 "' .., •
236
Presentación de los datos:
Parametros utilizados:
Atmospheric argon ratios Source Decay constants Source
(40Ar/36Ar)A 295.5 ± 0.5 Steiger and Jäger (1977) 40K λε (5.81 ± 0.17)E-11 y-1 Steiger and Jäger (1977)
(40Ar/38Ar)A 1575 ± 2 Nier (1950) 40K λβ (4.96 ± 0.09)E-10 y-1 Steiger and Jäger (1977)
39Ar (7.05 ± 0.08)E-06 d-1 Stoenner et al. (1965)
Interfering isotope production ratios Source 37Ar (19.83 ± 0.06)E-03 d-1 Renne and Norman (2001)
(40Ar/39Ar)K 0.0017 ± 0.0002 In house 36Cl λβ (6.31 ± 0.04)E-09 d-1 Endt (1998)
(38Ar/39Ar)K 0.01220 ± 0.00003 Renne et al. (2005)
(39Ar/37Ar)Ca 0.00077 ± 0.00003 In house
(38Ar/37Ar)Ca 0.0000196 ± 0.0000008 Renne et al. (2005)
(36Ar/37Ar)Ca 0.0003308 ± 0.0000012 In house
(36Ar/38Ar)Cl 262.8 ± 1.7 Renne et al. (2008)
Informe 019; Argus 2017
Edmundo Polanco
SDNG
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
La información presentada en el informe, se ajusta a las normas de información de datos para
geocronología de 40Ar/39Ar, publicadas en "Data reporting norms for 40Ar/39Ar geochronology",
Quaternary Geochronology 4 (2009) 346-352.
Adán Ramírez
Analista
Marco Suarez
Jefe Geología Isotópica (S)
Annex XIV Appendix B
237
Annex XIV Appendix B
Data Presentation:
Parameters used:
Atmospheric argon ratios Source Decay constants Source
(40Ar/36Ar)A 295.5 ± 0.5 Steiger and Jäger (1977) 40K λε (5.81 ± 0.17)E-11 y-1 Steiger and Jäger (1977)
(40Ar/38Ar)A 1575 ± 2 Nier (1950) 40K λβ (4.96 ± 0.09)E-10 y-1 Steiger and Jäger (1977)
39Ar (7.05 ± 0.08)E-06 d-1 Stoenner et al. (1965)
Interfering isotope production ratios Source 37Ar (19.83 ± 0.06)E-03 d-1 Renne and Norman (2001)
(40Ar/39Ar)K 0.0017 ± 0.0002 In house 36Cl λβ (6.31 ± 0.04)E-09 d-1 Endt (1998)
(38Ar/39Ar)K 0.01220 ± 0.00003 Renne et al. (2005)
(39Ar/37Ar)Ca 0.00077 ± 0.00003 In house
(38Ar/37Ar)Ca 0.0000196 ± 0.0000008 Renne et al. (2005)
(36Ar/37Ar)Ca 0.0003308 ± 0.0000012 In house
(36Ar/38Ar)Cl 262.8 ± 1.7 Renne et al. (2008)
019 Report; Argus 2017
Edmundo Polanco
SDNG
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 y 1347, Post 21- SANTIAGO – CHILE
The information presented in the report conforms to the data reporting rules for 40Ar/39Ar
geochronology, published in "Data reporting norms for 40Ar/39Ar geochronology",
Quaternary Geochronology 4 (2009) 346-352.
Adán Ramírez
Analyst
Marco Suarez
Head of Isotopic Geology (Dep.)
238
Servicio Nacional de Geología y Minería
Subdirección Nacional de Geología
Departamento de Laboratorios
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Depto. Geologia Regional
UNIDAD DE GEOLOGIA ISOTOPICA
INFORME 40Ar/39Ar Nº 023/2017 ARGUS VI
Sr. Edmundo Polanco
Annex XIV Appendix B
SERNAGEOMIN
Ministerio de Mineria
Gobierno de Chile
239
Annex XIV Appendix B
National Geology and Mining Service
National Sub-directorate of Geology
Department of Laboratories
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
Regional Department of Geology
ISOTOPIC GEOLOGY UNIT
40Ar/39Ar REPORT Nº 023/2017 ARGUS VI
Mr. Edmundo Polanco
SERNAGEOMIN
Ministerio de Mineria
Gobierno de Chile
240
Muestra Nº Análisis Material Edad Integrada ± 2σ
Edad Plateau ±
2σ
Edad Isoc. Inversa ±
2σ
RSP-16d 14031-01 Plagioclasa 1.56 ± 0.08 Ma 1.61 ± 0.08 Ma 1.6 ± 0.2 Ma
GEOCRONOLOGIA ARGUS VI
En el presente informe se encuentran contenidos los resultados y análasis realizados a las muestras
que se detallan en la precedente tabla resumen:
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Annex XIV Appendix B
241
Annex XIV Appendix B
Sample Nº Analysis Material Integrated Age ± 2σ Plateau Age ± 2σ Inverse Isochron
Age ± 2σ
RSP-16d 14031-01 Plagioclase 1.56 ± 0.08 Ma 1.61 ± 0.08 Ma 1.61 ± 0.02 Ma
This report contains the results and analyses conducted on the samples that are detailed in the
preceding summary table:
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
ARGUS VI GEOCHRONOLOGY
242
Muestra : RSP-16d
Material : Plagioclasa
Nº interno : 14031-01
Análisis de Step Heating
Edad integrada: 1.56 ± 0.08 Ma
Edad Plateau: 1.61 ± 0.08 Ma
Pasos en el Plateau: 4/8 (71.8% de 39Ar)
MSWD Plateau: 0.99
Análisis de Isócrona Inversa
Edad Isócrona: 1.6 ± 0.2 Ma
Pasos: 4/8 (50 % de los pasos)
Intercepto 40/36: 295 ± 4
MSWD Isócrona: 1.4
Comentarios:
GEOCRONOLOGIA ARGUS VI
Todas las edades son concordantes. No se aprecia la presencia de argón heredado. Se recomienda usar la
edad obtenida con el plateau.
*********************************************
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Annex XIV Appendix B
243
Annex XIV Appendix B
Sample : RSP-16d
Material : Plagioclase
Internal Nº : 14031-01
Step Heating Analysis
Integrated Age: 1.56 ± 0.08 Ma
Plateau Age: 1.61 ± 0.08 Ma
Steps at the Plateau: 4/8 (71.8% de 39AR)
Plateau MSWD: 0,99
Inverse Isochron Analysis
Isochron Age: 1.6 ± 0.2 Ma
Steps: 4/8 (50% steps)
40/36 Intercept: 295 ± 4
Isochron MSWD: 1.4
Comments:
ARGUS VI GEOCHRONOLOGY
All ages are concordant. The presence of inherited argon has not been observed. It is recommended to use the
age obtained with the plateau.
*********************************************
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box: 10465 and 1347, Post 21- SANTIAGO – CHILE
244
Departamento de Laboratorios Servicio Nacional de Geología y Minería GEOCRONOLOGIA ARGUS VI
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
40Ar/39Ar Step-Heating Spectrum for Run 14031-01 (RSP-16d)
-20
0
20
40
60
80
100
% 40Ar*
-0.1
0
0.1
0.2
0.3
Cl/K
10
20
30
40
Ca/K
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
-2
-1
0
1
2
3
4
5
6
Apparent Age (Ma)
A
0.40
B
0.60
C
0.90 D
1.20 E
1.50 F
1.80 G
2.20
H
2.60
Integrated Age = 1.56 ± 0.08 Ma
1.61 ± 0.08 Ma (5.0%, MSWD = 0.99, p = 0.40, n = 4)
Data at 2-sigma, results at 2-sigma
Cumulative %39Ar Released
Annex XIV Appendix B
I I I 17_ I I
- L_
- ---
~
- ~ ~
245
Annex XIV Appendix B
Departamento de Laboratorios Servicio Nacional de Geología y Minería GEOCRONOLOGIA ARGUS VI
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
40Ar/39Ar Step-Heating Spectrum for Run 14031-01 (RSP-16d)
-20
0
20
40
60
80
100
% 40Ar*
-0.1
0
0.1
0.2
0.3 Cl/K
10
20
30
40
Ca/K
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
-2
-1
0
1
2
3
4
5
6
Apparent Age (Ma)
A
0.40
B
0.60
C
0.90 D
1.20 E
1.50 F
1.80 G
2.20
H
2.60
Integrated Age = 1.56 ± 0.08 Ma
1.61 ± 0.08 Ma (5.0%, MSWD = 0.99, p = 0.40, n = 4)
Data at 2-sigma, results at 2-sigma
Cumulative %39Ar Released
ARGUS VI GEOCHRONOLOGY
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
246
76 s Total
Material: Plagioclasa 36 s Rise
A 0.4 1.68E-15 44.76 0.05 6.59 0.03 0.13 0.02 1.97 0.03 0.1658 0.0008 -0.85 -0.06 0.04 -0.14 0.09 11.79 0.17 0.007 0.010
B 0.6 1.14E-15 30.38 0.05 7.64 0.03 0.12 0.02 3.27 0.03 0.1070 0.0007 16.99 0.68 0.03 1.64 0.07 16.95 0.15 0.002 0.009
C 0.9 2.94E-15 78.27 0.05 10.92 0.02 0.19 0.02 4.81 0.03 0.2742 0.0015 8.51 0.61 0.04 1.48 0.10 17.45 0.10 0.002 0.006
D 1.2 6.08E-15 162.02 0.05 14.21 0.03 0.28 0.02 5.42 0.03 0.5529 0.0016 5.71 0.65 0.03 1.58 0.08 15.09 0.08 0.001 0.004
E 1.5 3.55E-15 94.58 0.05 11.81 0.03 0.22 0.02 5.43 0.03 0.3280 0.0016 8.79 0.71 0.04 1.71 0.10 18.24 0.10 0.004 0.006
F 1.8 1.01E-15 26.87 0.05 6.03 0.03 0.09 0.02 3.99 0.03 0.0989 0.0010 20.82 0.94 0.05 2.26 0.12 26.7 0.2 0.001 0.011
G 2.2 1.00E-15 26.66 0.05 3.93 0.03 0.06 0.02 3.11 0.03 0.0962 0.0007 16.63 1.14 0.06 2.75 0.13 31.9 0.4 0.001 0.017
H 2.6 6.81E-17 1.82 0.05 0.92 0.03 0.03 0.02 0.79 0.02 0.0078 0.0005 59.42 1.18 0.19 2.9 0.5 34.4 1.6 0.06 0.07
1.61 0.04
Interpolation 77 s Total
37 s Rise
1 3.4 5.40E-14 1438.32 0.13 121.44 0.04 1.56 0.02 0.07 0.03 0.0243 0.0008 99.51 11.772 0.005 28.201 0.012 0.019 0.008 0.0018 0.0006
GEOCRONOLOGIA ARGUS VI
40Ar/39Ar Step-Heating Data for Run 14031-01; RSP-16d
Cl/K ± σ
Cl/K ± σ
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
N Power
(W)
40Ar
(moles)
40Ar
(fA)
39Ar
(fA)
± σ
(Ma)
± σ39 (fA)
38Ar
(fA)
± σ38 (fA)
37Ar
(fA)
± σ37 (fA)
36Ar
(fA) Ca/K ± σ
N Power
(W)
40Ar
(moles)
40Ar
(fA)
± σ40 (fA)
39Ar
(fA)
± σ39 (fA)
38Ar
(fA)
± σ
(Ma) ± σ38 Ca/K ± σ (fA)
37Ar
(fA)
± σ37 (fA)
36Ar
(fA)
± σ36 (fA) %40Ar*
Sample: RSP-16d J: 0.0013369 ± 0.0000002 D: 1.00010 ± 0.00003 Heating:
40Ar*/39Ark ± σ Age
(Ma)
± σ36 (fA) %40Ar* 40Ar*/39Ark
Hole: 16/21
Standart: FC D: 1.00027 ± 0.00003 Heating:
Hole: 16/21
Age: 28.201 Ma
Plateau Age (steps B-E ):
± σ Age
(Ma)
± σ40 (fA)
Annex XIV Appendix B
247
Annex XIV Appendix B
76 s Total
Material: Plagioclas 36 s Rise
A 0.4 1.68E-15 44.76 0.05 6.59 0.03 0.13 0.02 1.97 0.03 0.1658 0.0008 -0.85 -0.06 0.04 -0.14 0.09 11.79 0.17 0.007 0.010
B 0.6 1.14E-15 30.38 0.05 7.64 0.03 0.12 0.02 3.27 0.03 0.1070 0.0007 16.99 0.68 0.03 1.64 0.07 16.95 0.15 0.002 0.009
C 0.9 2.94E-15 78.27 0.05 10.92 0.02 0.19 0.02 4.81 0.03 0.2742 0.0015 8.51 0.61 0.04 1.48 0.10 17.45 0.10 0.002 0.006
D 1.2 6.08E-15 162.02 0.05 14.21 0.03 0.28 0.02 5.42 0.03 0.5529 0.0016 5.71 0.65 0.03 1.58 0.08 15.09 0.08 0.001 0.004
E 1.5 3.55E-15 94.58 0.05 11.81 0.03 0.22 0.02 5.43 0.03 0.3280 0.0016 8.79 0.71 0.04 1.71 0.10 18.24 0.10 0.004 0.006
F 1.8 1.01E-15 26.87 0.05 6.03 0.03 0.09 0.02 3.99 0.03 0.0989 0.0010 20.82 0.94 0.05 2.26 0.12 26.7 0.2 0.001 0.011
G 2.2 1.00E-15 26.66 0.05 3.93 0.03 0.06 0.02 3.11 0.03 0.0962 0.0007 16.63 1.14 0.06 2.75 0.13 31.9 0.4 0.001 0.017
H 2.6 6.81E-17 1.82 0.05 0.92 0.03 0.03 0.02 0.79 0.02 0.0078 0.0005 59.42 1.18 0.19 2.9 0.5 34.4 1.6 0.06 0.07
1.61 0.04
Interpolation 77 s Total
37 s Rise
1 3.4 5.40E-14 1438.32 0.13 121.44 0.04 1.56 0.02 0.07 0.03 0.0243 0.0008 99.51 11.772 0.005 28.201 0.012 0.019 0.008 0.0018 0.0006
GEOCRONOLOGIA ARGUS VI
40Ar/39Ar Step-Heating Data for Run 14031-01; RSP-16d
Cl/K ± σ
Cl/K ± σ
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
N Power
(W)
40Ar
(moles)
40Ar
(fA)
39Ar
(fA)
± σ
(Ma)
± σ39 (fA)
38Ar
(fA)
± σ38 (fA)
37Ar
(fA)
± σ37 (fA)
36Ar
(fA) Ca/K ± σ
N Power
(W)
40Ar
(moles)
40Ar
(fA)
± σ40 (fA)
39Ar
(fA)
± σ39 (fA)
38Ar
(fA)
± σ
(Ma) ± σ38 Ca/K ± σ (fA)
37Ar
(fA)
± σ37 (fA)
36Ar
(fA)
± σ36 (fA) %40Ar*
Sample: RSP-16d J: 0.0013369 ± 0.0000002 D: 1.00010 ± 0.00003 Heating:
40Ar*/39Ark ± σ Age
(Ma)
± σ36 (fA) %40Ar* 40Ar*/39Ark
Hole: 16/21
Standard: FC D: 1.00027 ± 0.00003 Heating:
Hole: 16/21
Age: 28.201 Ma
Plateau Age (steps B-E ):
± σ Age
(Ma)
± σ40 (fA)
e
ARGUS VI GEOCHRONOLOGY
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
248
Departamento de Laboratorios Servicio Nacional de Geología y Minería GEOCRONOLOGIA ARGUS VI
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Isochron for Run 14031-01 (RSP-16d)
0 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70
0.0010
0.0012
0.0014
0.0016
0.0018
0.0020
0.0022
0.0024
0.0026
0.0028
0.0030
0.0032
0.0034 A
B
C
D
E
F
G
H
Age = 1.6 ± 0.2 Ma (12.2%)
40Ar/36Ar Int. = 295 ± 4
MSWD = 1.4, n = 4
Data at 1-sigma, results at 2-sigma
39Ar/40Ar
36Ar/40Ar
Annex XIV Appendix B
249
Annex XIV Appendix B
Departamento de Laboratorios Servicio Nacional de Geología y Minería GEOCRONOLOGIA ARGUS VI
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Isochron for Run 14031-01 (RSP-16d)
0 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70
0.0010
0.0012
0.0014
0.0016
0.0018
0.0020
0.0022
0.0024
0.0026
0.0028
0.0030
0.0032
0.0034 A
B
C
D
E
F
G
H
Age = 1.6 ± 0.2 Ma (12.2%)
40Ar/36Ar Int. = 295 ± 4
MSWD = 1.4, n = 4
Data at 1-sigma, results at 2-sigma
39Ar/40Ar
36Ar/40Ar
ARGUS VI GEOCHRONOLOGY
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
250
Isochron Data for 14031-01A to 14031-01H
Run ID Status 40Ar*/39Ar (36/40) isoch %± (39/40) isoch %± Correl 36/39 Group
14031-01A User omitted -0.05763 0.003413 0.60 0.14673 0.50 0.048 1
14031-01B OK 0.67894 0.002809 0.80 0.25023 0.43 0.075 1
14031-01C OK 0.61351 0.003096 0.60 0.13877 0.25 0.026 1
14031-01D OK 0.65435 0.003191 0.30 0.08728 0.23 0.018 1
14031-01E OK 0.70843 0.003087 0.50 0.12414 0.27 0.022 1
14031-01F User omitted 0.93619 0.002680 1.40 0.22235 0.58 0.043 1
14031-01G User omitted 1.13930 0.002821 0.90 0.14597 0.83 0.044 1
14031-01H User omitted 1.18224 0.001373 22.50 0.50260 4.32 0.071 1
Sample ID Age [Ma] M.S.E. (40/36) tr M.S.E. MSWD Prob n
RSP-16d 14031-01 1.6 0.2 295 4 1.4 2.47E-01 4
Departamento de Laboratorios Servicio Nacional de Geología y Minería GEOCRONOLOGIA ARGUS VI
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
Isochron Data for 14031-01A to 14031-01H
Run ID Status 40Ar*/39Ar (36/40) isoch %± (39/40) isoch %± Correl 36/39 Group
14031-01A User omitted -0.05763 0.003413 0.60 0.14673 0.50 0.048 1
14031-01B OK 0.67894 0.002809 0.80 0.25023 0.43 0.075 1
14031-01C OK 0.61351 0.003096 0.60 0.13877 0.25 0.026 1
14031-01D OK 0.65435 0.003191 0.30 0.08728 0.23 0.018 1
14031-01E OK 0.70843 0.003087 0.50 0.12414 0.27 0.022 1
14031-01F User omitted 0.93619 0.002680 1.40 0.22235 0.58 0.043 1
14031-01G User omitted 1.13930 0.002821 0.90 0.14597 0.83 0.044 1
14031-01H User omitted 1.18224 0.001373 22.50 0.50260 4.32 0.071 1
Sample ID Age [Ma] M.S.E. (40/36) tr M.S.E. MSWD Prob n
RSP-16d 14031-01 1.6 0.2 295 4 1.4 2.47E-01 4
Annex XIV Appendix B
251
Annex XIV Appendix B
Isochron Data for 14031-01A to 14031-01H
Run ID Status 40Ar*/39Ar (36/40) isoch %± (39/40) isoch %± Correl 36/39 Group
14031-01A User omitted -0.05763 0.003413 0.60 0.14673 0.50 0.048 1
14031-01B OK 0.67894 0.002809 0.80 0.25023 0.43 0.075 1
14031-01C OK 0.61351 0.003096 0.60 0.13877 0.25 0.026 1
14031-01D OK 0.65435 0.003191 0.30 0.08728 0.23 0.018 1
14031-01E OK 0.70843 0.003087 0.50 0.12414 0.27 0.022 1
14031-01F User omitted 0.93619 0.002680 1.40 0.22235 0.58 0.043 1
14031-01G User omitted 1.13930 0.002821 0.90 0.14597 0.83 0.044 1
14031-01H User omitted 1.18224 0.001373 22.50 0.50260 4.32 0.071 1
Sample ID Age [Ma] M.S.E. (40/36) tr M.S.E. MSWD Prob n
RSP-16d 14031-01 1.6 0.2 295 4 1.4 2.47E-01 4
ARGUS VI GEOCHRONOLOGY
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 and 1347, Post 21- SANTIAGO – CHILE
252
Equipamiento principal:
Condiciones de medición:
Criterios de análisis:
Un MSWD < 3 se considera aceptable
GEOCRONOLOGIA ARGUS VI
La definición de un plateau se determina por: ≥ 3 pasos de fusión consecutivos; ≥ 50% de 39Ar liberado en
el análisis; Error overlap a 2σ.
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
A continuación se detallan las particularidades de los análisis realizados a las muestras contenidas en el
informe:
Espectrómetro Argus VI (multicolector, CDD en 36Ar); Thermo Scientific
Láser de CO2 (10,6 μ); Photon Machines.
Cada dos o tres pasos se realizó una medición del background, el cuál fue descontado directamente en
las mediciones subsecuentes.
La irradiación de neutrones fue realizada en el reactor nuclear de la CCHEN por un periodo de 23 hrs,
existiendo un escudo de cadmio para las muestras.
Para determinar J de cada lugar de irradiación, se realizó un regresión polinomial de 21 standars
presentes en el disco de irradiación.
Annex XIV Appendix B
253
Annex XIV Appendix B
Main Equipment:
Measurement Conditions:
Analysis Criteria:
A MSWD < 3 is considered to be acceptable.
ARGUS VI GEOCHRONOLOGY
The definition of a plateau is determined by: ≥ 3 consecutive fusion steps; ≥ 50% of 39Ar released in the
analysis; Error overlap at 2σ.
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box: 10465 and 1347, Post 21- SANTIAGO – CHILE
The details of the analyses conducted to the samples contained in the report are given below:
Argus VI Spectrometer (multicollector, CDD in 36Ar); Thermo Scientific CO2 Laser (10,6 μ); Photon
Machines.
Every two or three steps, the background was measured, which was discounted directly in the
subsequent measurement.
The neutron irradiation was carried out at the CCHEN nuclear reactor during a 23-hour period: there was
a cadmium shield for the samples.
To determine J of each irradiation site, a polynomial regression was done of 21 standards present in the
radiation disk.
;;e .!!!
~ :E u
0 UJ {; "' 0
~ C
ii;
"' :E UJ 0
V'I "' •
254
Presentación de los datos:
Parametros utilizados:
Atmospheric argon ratios Source Decay constants Source
(40Ar/36Ar)A 295.5 ± 0.5 Steiger and Jäger (1977) 40K λε (5.81 ± 0.17)E-11 y-1 Steiger and Jäger (1977)
(40Ar/38Ar)A 1575 ± 2 Nier (1950) 40K λβ (4.96 ± 0.09)E-10 y-1 Steiger and Jäger (1977)
39Ar (7.05 ± 0.08)E-06 d-1 Stoenner et al. (1965)
Interfering isotope production ratios Source 37Ar (19.83 ± 0.06)E-03 d-1 Renne and Norman (2001)
(40Ar/39Ar)K 0.0017 ± 0.0002 In house 36Cl λβ (6.31 ± 0.04)E-09 d-1 Endt (1998)
(38Ar/39Ar)K 0.01220 ± 0.00003 Renne et al. (2005)
(39Ar/37Ar)Ca 0.00077 ± 0.00003 In house
(38Ar/37Ar)Ca 0.0000196 ± 0.0000008 Renne et al. (2005)
(36Ar/37Ar)Ca 0.0003308 ± 0.0000012 In house
(36Ar/38Ar)Cl 262.8 ± 1.7 Renne et al. (2008)
Informe 023; Argus 2017
Edmundo Polanco
Depto. Geologia Regional
Departamento de Laboratorios Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - FONO: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Casilla: 10465 y 1347, correo 21- SANTIAGO – CHILE
La información presentada en el informe, se ajusta a las normas de información de datos para
geocronología de 40Ar/39Ar, publicadas en "Data reporting norms for 40Ar/39Ar geochronology",
Quaternary Geochronology 4 (2009) 346-352.
Adán Ramírez
Analista
Marco Suarez
Jefe Geología Isotópica (S)
Annex XIV Appendix B
255
Annex XIV Appendix B
Data Presentation:
Parameters used:
Atmospheric argon ratios Source Decay constants Source
(40Ar/36Ar)A 295.5 ± 0.5 Steiger and Jäger (1977) 40K λε (5.81 ± 0.17)E-11 y-1 Steiger and Jäger (1977)
(40Ar/38Ar)A 1575 ± 2 Nier (1950) 40K λβ (4.96 ± 0.09)E-10 y-1 Steiger and Jäger (1977)
39Ar (7.05 ± 0.08)E-06 d-1 Stoenner et al. (1965)
Interfering isotope production ratios Source 37Ar (19.83 ± 0.06)E-03 d-1 Renne and Norman (2001)
(40Ar/39Ar)K 0.0017 ± 0.0002 In house 36Cl λβ (6.31 ± 0.04)E-09 d-1 Endt (1998)
(38Ar/39Ar)K 0.01220 ± 0.00003 Renne et al. (2005)
(39Ar/37Ar)Ca 0.00077 ± 0.00003 In house
(38Ar/37Ar)Ca 0.0000196 ± 0.0000008 Renne et al. (2005)
(36Ar/37Ar)Ca 0.0003308 ± 0.0000012 In house
(36Ar/38Ar)Cl 262.8 ± 1.7 Renne et al. (2008)
023 Report; Argus 2017
Edmundo Polanco
Dept. Regional Geology
Department of Laboratories Servicio Nacional de Geología y Minería
Til Til 1993, Ñuñoa - Santiago - PHONE: (56-2) 2385292 FAX: (56-2) 2385332 - www.sernageomin.cl
E-mail: [email protected] – Postal Box 10465 y 1347, Post 21- SANTIAGO – CHILE
The information presented in the report conforms to the data reporting rules for 40Ar/39Ar
geochronology, published in "Data reporting norms for 40Ar/39Ar geochronology",
Quaternary Geochronology 4 (2009) 346-352.
Adán Ramírez
Analyst
Marco Suarez
Head of Isotopic Geology (Dep.)
256
Unidad de Geología Isotópica
Laboratorio U-Pb
INFORME : UPb-011-18
SOLICITANTE : Edmundo Polanco
AFILIACIÓN : Departamento de Geología General
SERNAGEOMIN
PROYECTO : --
CORRELATIVO INTERNO : C170725
FECHA INFORME : 25-04-2018
MUESTRAS : RSP-50d
Marco Suárez Felipe Llona
Jefe Unidad Geología Isotópica (S) Análisis LA-ICP-MS
Annex XIV Appendix B
Servicio Nacional
de Geologia y
Mineria
257
Annex XIV Appendix B
Isotopic Geology Unit
U-Pb Laboratory
REPORT : UPb-011-18
APPLICANT : Edmundo Polanco
AFFILIATION : Department of General Geology
SERNAGEOMIN
PROJECT : --
IN-HOUSE CORRELATIVE : C170725
DATE OF REPORT : 25-04-2018
SAMPLES : RSP-50d
Marco Suárez Felipe Llona
Head of Isotopic Geology Unit (Dep.) LA-ICP-MS Analysis
Servicio Nacional
de Geologia y
Mineria
258
Muestra RSP-50d
Número de puntos analizados : 30 puntos, 3 puntos excluidos de los resultados.
Edades 206Pb/238U corregidas por plomo común.
Edad:
Número de puntos utilizados en edad: 27
Edad propuesta para 15 valores coherentes (algoritmo Zircon age extractor / Isoplot):
6.63 ± 0.06 Ma
Annex XIV Appendix B
Servicio Nacional
de Geologia y
Mineria
259
Annex XIV Appendix B
RSP-50d Sample
Number of points analysed : 30 points, 3 points excluded from results
206Pb/238U ages corrected with common lead
Age:
Number of points used in dating : 27
Age proposed for 15 coherent values (Zircon age extractor algorithm / Isoplot):
6.63 ± 0.06 Ma
Servicio Nacional
de Geologia y
Mineria
260
Muestra: RSP-50
RAZONES EDADES [Ma]
N° spot Observ. U [ppm]a Pb [ppm]a Th [ppm]a 207Pb/235Ub 2 sd 206Pb/238Ub 2 sd rhoc 207Pb/206Pbb 2 sd 207Pb/235U
RSP-50_1 992 14 929 0,00883 0,00032 0,001002 0,000024 0,30393 0,0647 0,0018 8,9
RSP-50_2 387 13 301 0,02662 0,00120 0,001275 0,000035 0,57587 0,154 0,0045 26,7
RSP-50_4 658 7 390 0,01086 0,00057 0,001071 0,000026 0,48118 0,077 0,0043 11,0
RSP-50_5 1147 15 226 0,01740 0,00170 0,001243 0,000030 0,4776 0,102 0,0095 17,5
RSP-50_6 276 4 168 0,01581 0,00089 0,001104 0,000027 0,12066 0,1069 0,0059 15,9
RSP-50_7 577 9 414 0,01428 0,00066 0,001076 0,000027 0,59602 0,0982 0,0036 14,4
RSP-50_8 556 8 344 0,01298 0,00075 0,001249 0,000031 0,13534 0,078 0,0043 13,1
RSP-50_9 572 11 467 0,01554 0,00110 0,001113 0,000027 0,5937 0,1023 0,0064 15,7
RSP-50_11 1020 7 412 0,00913 0,00030 0,001113 0,000026 0,5092 0,0612 0,0014 9,2
RSP-50_12 936 11 548 0,01063 0,00058 0,001046 0,000024 0,55198 0,0755 0,0034 10,7
RSP-50_13 569 7 387 0,01067 0,00045 0,001101 0,000026 0,0079291 0,0706 0,0028 10,8
RSP-50_14 494 7 391 0,01197 0,00073 0,001085 0,000029 0,4785 0,0824 0,0042 12,1
RSP-50_15 748 9 554 0,01033 0,00038 0,001134 0,000026 0,14535 0,0665 0,0021 10,4
RSP-50_16 1254 37 2706 0,00852 0,00030 0,001045 0,000027 0,49509 0,0615 0,0016 8,6
RSP-50_17 485 8 245 0,01690 0,00095 0,001215 0,000030 0,31944 0,103 0,0051 17,0
RSP-50_18 876 10 639 0,00986 0,00095 0,001052 0,000025 0,14693 0,0688 0,0069 10,0
RSP-50_19 624 5 265 0,00984 0,00043 0,001053 0,000025 0,36526 0,0691 0,0024 9,9
RSP-50_20 567 7 351 0,01285 0,00100 0,001069 0,000025 0,54615 0,0875 0,0064 13,0
RSP-50_21 699 8 532 0,01047 0,00039 0,001077 0,000025 0,13359 0,0712 0,0021 10,6
RSP-50_23 438 13 445 0,02279 0,00130 0,001223 0,000029 0,54897 0,1349 0,0072 22,9
RSP-50_24 837 21 708 0,01834 0,00120 0,001177 0,000030 0,7032 0,1138 0,0065 18,4
RSP-50_25 826 13 648 0,01243 0,00170 0,001109 0,000028 0,16291 0,082 0,011 12,5
RSP-50_26 1687 21 1361 0,00853 0,00042 0,001007 0,000024 0,21051 0,0625 0,0027 8,6
RSP-50_27 531 5 212 0,01228 0,00050 0,001308 0,000030 0,09453 0,069 0,0024 12,4
RSP-50_28 610 7 399 0,01083 0,00043 0,001120 0,000026 0,16694 0,0718 0,0025 10,9
RSP-50_29 430 7 258 0,01637 0,00130 0,001122 0,000029 0,63274 0,1077 0,0073 16,5
RSP-50_30 369 5 293 0,01284 0,00063 0,001089 0,000028 0,22473 0,0866 0,0038 12,9
RSP-50_3 (1) 352 10 443 0,01709 0,00170 0,001203 0,000032 0,67874 0,106 0,01 17,2
RSP-50_10 (1) 450 51 109 0,06444 0,00860 0,007341 0,001000 0,99474 0,0669 0,002 63,4
RSP-50_22 (1) 447 10 262 0,02041 0,00310 0,001165 0,000042 0,97132 0,121 0,01 20,5
(1) Valores no considerados en los cálculos debido a patrón incorrecto en curvas de razones isotópicas (inhomogeneidad en el contenido isotópico)
a Concentraciones de U, Pb y Th son calculadas en relación al circón de referencia GJ-1 (Jackson et al. 2004 Chem. Geol, 211 47-69)
b Corregido por background, por fraccionamiento y normalizado al circón de referencia GJ-1
207Pb/235U es calculado usando (207Pb/206Pb) / (238U/206Pb * 1/137.88)
c Rho es la correlación del error definido como el cuociente de los errores propagados de las razones 206Pb/238U y 207Pb/235U
d Dos veces el valor de la propagación de los errores estándar.
e Williams, I.S., 1998. U–Th–Pb geochronology by ion microprobe. In: McKibben, M.A., Shanks, III W.C., Ridley, W.I. (Eds.),
Applications of Microanalytical Techniques to Understanding Mineralizing Processes. Reviews in Economic Geology 7(1):1–35.
Annex XIV Appendix B
I I I
I I I
111
111
111
111
111
I I I
I I I
I I I
261
Annex XIV Appendix B
Sample: RSP-50
RATIOS AGES [Ma]
N° spot Observ. U [ppm]a Pb [ppm]a Th [ppm]a 207Pb/235Ub 2 sd 206Pb/238Ub 2 sd rhoc 207Pb/206Pbb 2 sd 207Pb/235U
RSP-50_1 992 14 929 0,00883 0,00032 0,001002 0,000024 0,30393 0,0647 0,0018 8,9
RSP-50_2 387 13 301 0,02662 0,00120 0,001275 0,000035 0,57587 0,154 0,0045 26,7
RSP-50_4 658 7 390 0,01086 0,00057 0,001071 0,000026 0,48118 0,077 0,0043 11,0
RSP-50_5 1147 15 226 0,01740 0,00170 0,001243 0,000030 0,4776 0,102 0,0095 17,5
RSP-50_6 276 4 168 0,01581 0,00089 0,001104 0,000027 0,12066 0,1069 0,0059 15,9
RSP-50_7 577 9 414 0,01428 0,00066 0,001076 0,000027 0,59602 0,0982 0,0036 14,4
RSP-50_8 556 8 344 0,01298 0,00075 0,001249 0,000031 0,13534 0,078 0,0043 13,1
RSP-50_9 572 11 467 0,01554 0,00110 0,001113 0,000027 0,5937 0,1023 0,0064 15,7
RSP-50_11 1020 7 412 0,00913 0,00030 0,001113 0,000026 0,5092 0,0612 0,0014 9,2
RSP-50_12 936 11 548 0,01063 0,00058 0,001046 0,000024 0,55198 0,0755 0,0034 10,7
RSP-50_13 569 7 387 0,01067 0,00045 0,001101 0,000026 0,0079291 0,0706 0,0028 10,8
RSP-50_14 494 7 391 0,01197 0,00073 0,001085 0,000029 0,4785 0,0824 0,0042 12,1
RSP-50_15 748 9 554 0,01033 0,00038 0,001134 0,000026 0,14535 0,0665 0,0021 10,4
RSP-50_16 1254 37 2706 0,00852 0,00030 0,001045 0,000027 0,49509 0,0615 0,0016 8,6
RSP-50_17 485 8 245 0,01690 0,00095 0,001215 0,000030 0,31944 0,103 0,0051 17,0
RSP-50_18 876 10 639 0,00986 0,00095 0,001052 0,000025 0,14693 0,0688 0,0069 10,0
RSP-50_19 624 5 265 0,00984 0,00043 0,001053 0,000025 0,36526 0,0691 0,0024 9,9
RSP-50_20 567 7 351 0,01285 0,00100 0,001069 0,000025 0,54615 0,0875 0,0064 13,0
RSP-50_21 699 8 532 0,01047 0,00039 0,001077 0,000025 0,13359 0,0712 0,0021 10,6
RSP-50_23 438 13 445 0,02279 0,00130 0,001223 0,000029 0,54897 0,1349 0,0072 22,9
RSP-50_24 837 21 708 0,01834 0,00120 0,001177 0,000030 0,7032 0,1138 0,0065 18,4
RSP-50_25 826 13 648 0,01243 0,00170 0,001109 0,000028 0,16291 0,082 0,011 12,5
RSP-50_26 1687 21 1361 0,00853 0,00042 0,001007 0,000024 0,21051 0,0625 0,0027 8,6
RSP-50_27 531 5 212 0,01228 0,00050 0,001308 0,000030 0,09453 0,069 0,0024 12,4
RSP-50_28 610 7 399 0,01083 0,00043 0,001120 0,000026 0,16694 0,0718 0,0025 10,9
RSP-50_29 430 7 258 0,01637 0,00130 0,001122 0,000029 0,63274 0,1077 0,0073 16,5
RSP-50_30 369 5 293 0,01284 0,00063 0,001089 0,000028 0,22473 0,0866 0,0038 12,9
RSP-50_3 (1) 352 10 443 0,01709 0,00170 0,001203 0,000032 0,67874 0,106 0,01 17,2
RSP-50_10 (1) 450 51 109 0,06444 0,00860 0,007341 0,001000 0,99474 0,0669 0,002 63,4
RSP-50_22 (1) 447 10 262 0,02041 0,00310 0,001165 0,000042 0,97132 0,121 0,01 20,5
(1) Values not considered in the calculations due to incorrect pattern in isotopic ratios (inhomogeneity in the isotopic content).
a Concentrations of U, Pb, and Th are calculated in connection with the reference zircon GJ-1 (Jackson et al. 2004 Chem. Geol, 211 47-69)
b Corrected by background, by fractioning, and standardized to the reference zircon GJ-1
207Pb/235U is calculated using (207Pb/206Pb) / (238U/206Pb * 1/137.88).
c Rho is the correlation of the error defined as the quotient of errors propagation of the ratios 206Pb/238U y 207Pb/235U.
d Twice the value of the standard error propagation.
e Williams, I.S., 1998. U–Th–Pb geochronology by ion microprobe. In: McKibben, M.A., Shanks, III W.C., Ridley, W.I. (Eds.),
Applications of Microanalytical Techniques to Understanding Mineralizing Processes. Reviews in Economic Geology 7(1):1–35.
I I I
I I I
111
111
111
111
111
I I I
I I I
I I I
262
Edad corregida por Pb común (e)
2 s 206Pb/238U 2 s 207Pb/206Pb 2 s 206Pb/238U 2 s 207Pb/206Pb común
0,3 6,5 0,2 753 58 6,3 0,2 0,83603
1,1 8,2 0,2 2387 50 7,1 0,2 0,83614
0,6 6,9 0,2 1110 100 6,6 0,2 0,83606
1,7 8,0 0,2 1490 190 7,4 0,2 0,83613
0,9 7,1 0,2 1724 98 6,6 0,2 0,83607
0,7 6,9 0,2 1588 72 6,5 0,2 0,83606
0,8 8,0 0,2 1140 110 7,7 0,2 0,83613
1,1 7,2 0,2 1620 120 6,7 0,2 0,83608
0,3 7,2 0,2 637 49 7,0 0,2 0,83608
0,6 6,7 0,2 1044 90 6,5 0,2 0,83605
0,5 7,1 0,2 933 78 6,9 0,2 0,83607
0,7 7,0 0,2 1238 97 6,7 0,2 0,83607
0,4 7,3 0,2 831 68 7,1 0,2 0,83609
0,3 6,7 0,2 646 56 6,6 0,2 0,83605
1,0 7,8 0,2 1649 93 7,3 0,2 0,83612
1,0 6,8 0,2 761 87 6,6 0,2 0,83605
0,4 6,8 0,2 905 67 6,6 0,2 0,83605
1,0 6,9 0,2 1320 130 6,5 0,2 0,83606
0,4 6,9 0,2 967 63 6,7 0,2 0,83606
1,3 7,9 0,2 2149 95 7,0 0,2 0,83612
1,2 7,6 0,2 1830 110 6,9 0,2 0,83610
1,7 7,1 0,2 1110 240 6,8 0,2 0,83608
0,4 6,5 0,2 658 86 6,4 0,2 0,83603
0,5 8,4 0,2 908 73 8,2 0,2 0,83616
0,4 7,2 0,2 970 75 7,0 0,2 0,83608
1,3 7,2 0,2 1700 130 6,7 0,2 0,83608
0,6 7,0 0,2 1335 80 6,7 0,2 0,83607
1,7 7,7 0,2 1690 180
8,3 47,2 6,6 829 63
3,0 7,5 0,3 1890 130
EDADES [Ma]
2 sd 207Pb/235U
0,0018 8,9
0,0045 26,7
0,0043 11,0
0,0095 17,5
0,0059 15,9
0,0036 14,4
0,0043 13,1
0,0064 15,7
0,0014 9,2
0,0034 10,7
0,0028 10,8
0,0042 12,1
0,0021 10,4
0,0016 8,6
0,0051 17,0
0,0069 10,0
0,0024 9,9
0,0064 13,0
0,0021 10,6
0,0072 22,9
0,0065 18,4
0,011 12,5
0,0027 8,6
0,0024 12,4
0,0025 10,9
0,0073 16,5
0,0038 12,9
0,01 17,2
0,002 63,4
0,01 20,5
Annex XIV Appendix B
I I I
I I I
I I I
I I I
I I I
I I I
263
Annex XIV Appendix B
AGES [Ma]
207Pb/235U 2 s 206Pb/238U 2 s 207Pb/206Pb 2 s comm 207Pb/206Pb
8,9 0,3 6,5 0,2 753 58 0,2 0,83603
26,7 1,1 8,2 0,2 2387 50 0,2 0,83614
11,0 0,6 6,9 0,2 1110 100 0,2 0,83606
17,5 1,7 8,0 0,2 1490 190 0,2 0,83613
15,9 0,9 7,1 0,2 1724 98 0,2 0,83607
14,4 0,7 6,9 0,2 1588 72 0,2 0,83606
13,1 0,8 8,0 0,2 1140 0,2 0,83613
15,7 1,1 7,2 0,2 1620 0,2 0,83608
9,2 0,3 7,2 0,2 637 0,2 0,83608
10,7 0,6 6,7 0,2 1044 0,2 0,83605
10,8 0,5 7,1 0,2 933 0,2 0,83607
12,1 0,7 7,0 0,2 1238 0,2 0,83607
10,4 0,4 7,3 0,2 831 0,2 0,83609
8,6 0,3 6,7 0,2 646 0,2 0,83605
17,0 1,0 7,8 0,2 1649 0,2 0,83612
10,0 1,0 6,8 0,2 761 0,2 0,83605
9,9 0,4 6,8 0,2 905 0,2 0,83605
13,0 1,0 6,9 0,2 1320 0,2 0,83606
10,6 0,4 6,9 0,2 967 0,2 0,83606
22,9 1,3 7,9 0,2 2149 0,2 0,83612
18,4 1,2 7,6 0,2 1830 0,2 0,83610
12,5 1,7 7,1 0,2 1110 0,2 0,83608
8,6 0,4 6,5 0,2 658 0,2 0,83603
12,4 0,5 8,4 0,2 908 0,2 0,83616
10,9 0,4 7,2 0,2 970 0,2 0,83608
16,5 1,3 7,2 0,2 1700 0,2 0,83608
12,9 0,6 7,0 0,2 1335 0,2 0,83607
17,2 1,7 7,7 0,2 1690 63,4 8,3 47,2 6,6 829 20,5 3,0 7,5 0,3 1890 EDADES [Ma] Age corrected by common Pb(e)
2 s 206Pb/238U 2 s 2 s 206Pb/238U 2 s 207Pb/206Pb común
0,3 6,5 0,2 753 58 6,3 0,2 0,83603
1,1 8,2 0,2 2387 50 7,1 0,2 0,83614
0,6 6,9 0,2 1110 100 6,6 0,2 0,83606
1,7 8,0 0,2 1490 190 7,4 0,2 0,83613
0,9 7,1 0,2 1724 98 6,6 0,2 0,83607
0,7 6,9 0,2 72 6,5 0,2 0,83606
0,8 8,0 0,2 110 7,7 0,2 0,83613
1,1 7,2 0,2 120 6,7 0,2 0,83608
0,3 7,2 0,2 49 7,0 0,2 0,83608
0,6 6,7 0,2 90 6,5 0,2 0,83605
0,5 7,1 0,2 78 6,9 0,2 0,83607
0,7 7,0 0,2 97 6,7 0,2 0,83607
0,4 7,3 0,2 68 7,1 0,2 0,83609
0,3 6,7 0,2 56 6,6 0,2 0,83605
1,0 7,8 0,2 93 7,3 0,2 0,83612
1,0 6,8 0,2 87 6,6 0,2 0,83605
0,4 6,8 0,2 67 6,6 0,2 0,83605
1,0 6,9 0,2 130 6,5 0,2 0,83606
0,4 6,9 0,2 63 6,7 0,2 0,83606
1,3 7,9 0,2 95 7,0 0,2 0,83612
1,2 7,6 0,2 110 6,9 0,2 0,83610
1,7 7,1 0,2 240 6,8 0,2 0,83608
0,4 6,5 0,2 86 6,4 0,2 0,83603
0,5 8,4 0,2 73 8,2 0,2 0,83616
0,4 7,2 0,2 75 7,0 0,2 0,83608
1,3 7,2 0,2 130 6,7 0,2 0,83608
0,6 7,0 0,2 80 6,7 0,2 0,83607
1,7 7,7 0,2 180
8,3 47,2 6,6 63
3,0 7,5 0,3 130
I I I
I I I
I I I
I I I
I I I
I I I
264
5.0
5.4
5.8
6.2
6.6
7.0
7.4
7.8
8.2
8.6
box heights are 2s
Age
TuffZirc Age = 6.63 +0.04 -0.06 Ma
(96.5% conf, from coherent group of 15)
Annex XIV Appendix B
265
Annex XIV Appendix B
0,04
0,06
0,08
0,10
0,12
0,14
0,16
0,18
650 750 850 950 1050
238U/206Pb
207Pb/206Pb
data-point error ellipses are 2s
Razones no corregidas por plomo común
0,04
0,06
0,08
0,10
0,12
0,14
0,16
0,18
650 750 850 950 1050
238U/206Pb
207Pb/206Pb
data-point error ellipses are 2s
Ratios not corrected by common lead
~ ~ °~' ~-------'--- =1i-..; :==::::::'._:::==~ (O
266
0,0009
0,0010
0,0011
0,0012
0,0013
0,0014
0,004 0,008 0,012 0,016 0,020 0,024 0,028 0,032
207Pb/235U
206Pb/238U
7.6 7.2 8.4 8.0 9.2 8.8
data-point error ellipses are 2s
Razones no corregidas por plomo común
0,04
0,06
0,08
0,10
0,12
0,14
0,16
0,18
650 750 850 950 1050
238U/206Pb
207Pb/206Pb
data-point error ellipses are 2s
Ratios not corrected by common lead
Annex XIV Appendix B
(_!!!!!!!!!!!!!!!~)
267
Annex XIV Appendix B
0
1
2
3
4
5
6
7
8
9
6,0 6,5 7,0 7,5 8,0 8,5
Number
Age (Ma)
. . 1 I I . I . . . . I ... , .
268
269
Annex XIV Appendix C
24
APPENDIX C
GEOLOGY OF THE SILALA RIVER BASIN, NORTHERN CHILE
67°45'W
68°30'W 68°15'W 68°0'W
Plsa
Pliva
Ha PlHa PlHpc
Psvd
Msvd
Piic
Msvd
Pliis
Msvd
Plg
PlHpc
Plsa
PlHpc
Msvd
Plg
Pliva
A
A'
4354
4850
4551
4553 4589
CHILE
CHILE BOLIVIA
HITO
S/N
HITO
S/N
o del Cajón
Port. Silala
Cerro
Silaguala
POLICE
STATION
Cerro de Inacaliri
HITO
S/N LXXIII
Cerrito
de
Silala
HITO S/N
LXXV Port. de Silala
HITO 16
LXXIV Cto. de Silala
Azufrera Cabana
REPRESA SILALA
INACALIRI
PAMPA AVESTRUZ
Quebrada Cabana
Quebrada Negra
Embalse Inacaliri
Quebrada Queñuagual
RÍO
SILALA
RÍO
INACALIRI
Planta Cabana
B'
B
5212
5426
5446
5373
5373
5360
5330
5420
4020
4519
4586
4470
4845
4222
"
"
"
"
"
"
"
"
" "
"
"
" "
"
" "
"
"
"
"
"
"
"
"
"
"
¯
¯
¯
¯
( ( (
(
( ( (
E
E
E E E
( (
(
(
/
/
¢
¢¢ ¢ ¢
¢
"
"
"
" "
"
1.612±0.018 2
2.6±0.4 1
4.12±0.08 1
1.61±0.08 1
0.63±0.31 1 6.63±0.06 1
@
; J
-
J
H
SERVICIO NACIONAL DE GEOLOGÍA Y MINERÍA
GEOLOGY OF THE SILALA RIVER AREA, NORTHERN CHILE
68°05' 595 km 600 km 68°00'
7.570
km
7.560
km
22°00'
7.570
km
22°00'
68°05' 600 Km 68°00' 605 km
SCALE 1:75.000
Bibliographical Reference
Blanco, N.; Polanco, E. 2018. Geology of the Silala River Area, Northern Chile. Servicio Nacional de Geología y
Minería, Informe Registrado IR-18-70, 1 map at scale 1:75.000. Santiago.
Registration No.
© Servicio Nacional de Geología y Minería. Avenida Santa María 0104, P.O. Box 10465, Santiago, Chile.
National Director (S): Alfonso Domeyko L.
National Deputy Director of Geology (S): Felipe Espinoza G.
All rights reserved.
Edition
This report has not been edited in accordance with the standards and / or nomenclature of the Subdirección Nacional
de Geología of Servicio Nacional de Geología y Minería.
Idiomatic and graphic control: Soraya Amar, Aníbal Gajardo, Renate Wall
Standards used
Geological Time Scale: Gradstein, F.M.; Ogg, J.G.; Schmitz, M.D.; Ogg, G.M. (editors) 2012.
Topographic base
Map scale 1:50.000, Cerro Inacaliri o del Cajón, Inacaliri and Linzor from the Instituto Geográ fico Militar (IGM), modified.
Geodesic reference
Universal Transversal de Mercator Projection (UTM), 19S zone, SIRGAS.
Scientific and technical assistance
Petrographic and radiometric dating feasibility studies: Edmundo Polanco V., Eugenia Fonseca P.
K-Ar radiometric determinations: Adrián Valeria X.; 40Ar/39Ar: Adán Ramírez B., Luis Yáñez B. Isotope geology unit of
Servicio Nacional de Geología y Minería.
U-Pb LA-ICP-MS radiometric determinatios: Marcos Suárez F., Felipe Llona R. Isotope geology unit of Servicio Nacional
de Geología y Minería. Dr. Luigi Solari from Centro de Geociencias de la Universidad Nacional Autónoma de
México (UNAM), Querétaro, México.
Geophysical studies: Jorge Vivallos C., Cecilia Donoso B., David Cáceres A.
Digital production: Cecilia Araya M., Cristian Faunes Q., y Marcos Lienlaf L., from Servicio Nacional de Geología y
Minería.
Financial support
Servicio Nacional de Geología y Minería
“Circulation hereof authorised by Resolution N° 18 of January 25 of 2019 of Dirección Nacional de Fronteras y Límites
del Estado. The publishing and circulation of maps, geographic maps or other printed material and documents referring
to or related with the borders and boundaries of Chile, in no way commit the Chilean Government, in accordance with
Article 2, letter g) of Statutory Decree N° 83 of 1979 from the Ministry o f Foreign Affairs”.
L E G E N D
CENOZOIC
PLEISTOCENE HOLOCENE
NEOGENE QUATERNARY
MIOCENE PLIOCENE
605 km
7.575
km
7.565
km
595 Km
7575
km
7.565
km
7.560
km
PALEOGENE
OLIGOCENE
S C H E M A T I C G E O L O G I C S E C T I O N S
##
Msvd
Plsa
Pliv
Pliv
Plg
Plsa 5.000
4.000
3.000
5.000
4.000
3.000
m asl
Plg
Plg PW-UQN
MW-DQN
SPW-DQN
B B'
PPla Pliis
Silala Ríver
Msvd
SCALE 1:75.000
Equidistance of contour lines: 50 m
1 0 1 2 3 4 km
±
LOCATION MAP
*
*
PACIFIC OCEAN
"ACUERDO DE 1998"
P E R Ú
BOLIVIA
ARGENTINA
CHILE
Santiago
76° 72° 68°
24°
35°
46°
57°
CHILEAN ANTARTIC
TERRITORY
90° 53°
SOUTH POLE
/(5
/(5
!
!
!
!
!
TARAPACÁ
REGION
ANTOFAGASTA
REGION
Salar
de Atacama
Salar
de Pintados
Río Loa
Calama
Tocopilla
IQUIQUE Pozo Almonte
ANTOFAGASTA
B O L I V I A
A R G E N T I N A
72°0'W 71°0'W 70°0'W 69°0'W 68°0'W 67°0'W
20°0'S
21°0'S
22°0'S
23°0'S
24°0'S
0 50 100 200 km
0 500 km
PACIFIC OCEAN
Fluvial deposits (Holocene)
Gravels, sands and silts.
Alluvial deposits (Holocene)
Gravels, sands and silts.
Alluvial deposits of the Upper Pleistocene-Holocene
Unconsolidated deposits formed by gravels with well rounded clasts, sands and silts.
Pyroclastic fall deposits (Pleistocene-Holocene)
Unconsolidated deposits, well stratified with alternating layers of dark scoria and light pumice.
Alluvial deposits of the Upper Pleistocene
Unconsolidated deposits formed by gravels, sands and silts.
Lateral meshing with glacial deposits (moraines).
Glacial deposits (Upper Pleistocene)
Unconsolidated deposits, formed by poorly sorted blocks and gravels.
Volcanic Sequences of the Lower Pleistocene (ca. 1.61-1.48 Ma)
Andesitic and dacitic volcanic rocks, reddish and black, formed by andesitic lavas and agglomerates.
Silala Ignimbrite (Pleistocene) (ca. 1.61 Ma)
Andesitic tuff, moderately welded with large pyroxene andesitic pumice and abundant young angular lithic fragments.
Alluvial deposits of the Upper Pliocene – Lower Pleistocene
Gravels, sands and silts (not represented in the map due to map scale; represented in the schematic geological sections).
Volcanic Sequences of the Upper Pliocene (ca. 2.6 Ma)
Domes, lava domes. Dacites with biotite and amphibole, coarse porphyritic texture, reddish grey in colour, locally having flow
banding.
Cabana Ignimbrite (Lower Pliocene) (ca. 4.12 Ma)
Ash tuff poorly to moderately welded and crystal rich (biotite and amphibole) with abundant pumice towards its roof.
Volcanic Sequences of the Upper Miocene (ca. 6.6 – 5.8 Ma)
Eroded remnants of volcanic edifices corresponding to domes, lava domes and autoclastic breccias composed of biotite -
hornblende dacite having coarse porphyritic texture, reddish grey color and, locally with flow banding.
MAGNETIC DECLINATION
DECEMBER-2018
MAGNETIC NORTH
TRUE NORTH
6° 27' W
CERRO DE
TOCORPURI
INACALIRI LINZOR
ASCOTAN
AIQUINA TOCONCE
CERRO
ARARAL
CUPO
VOLCANES
SAN PEDRO Y
SAN PABLO
CERRO
INACALIRI
O DEL CAJÓN
LOCATION IN OLLAGÜE
AND CALAMA PARTIAL SHEETS
Ollagüe Sheet, scale 1:250.000
Calama Sheet, scale 1:250.000
Study area
Geology of the Silala River Area, scale 1:75.000
Instituto Geográfico Militar (IGM) Sheets Catalog,
scale 1:50.000
Ha
PlHpc
PlHa
Plsa
Plg
Pliis
PPla
Psvd
Piic
Msvd
¢
¢
¢ ¢ ¢
¢
"
"
MW-BO
PW-BO
CW-BO
MWL-UQN
PW-UQN
MWS-UQN
Río Silala
1:50.000
PW-UQI
EW-PS
PW-DQN
MW-DQN
SPW-DQN
BOREHOLE CODE
Río Silala
Queb.Negra
¹
¹
4300
4200
4100
S I M B O L O G Y
SERVICIO NACIONAL DE GEOLOGÍA Y MINERÍA - CHILE
Nicolás Blanco
Edmundo Polanco
INFORME REGISTRADO IR-18-70
1 MAP
S U B D I R E C C I Ó N N A C I O N A L D E G E O L O G Í A
2018
Scale 1:75.000
!
ANTOFAGASTA
68°0'W
22°30'S
25°0'S
GE OL OG Y O F T H E S I L A L A A R E A
NO R T H E R N C H I L E
SOURCE OF INFORMATION
68°0'W
22°0'S
N. Blanco and E. Polanco (1:75.000)
21°45'S
22°0'S
22°15'S
22°30'S
1
2
RADIOMETRIC DATING (Ma ± 2σ)
K-Ar groundmass
40Ar/39Ar plagioclase
40Ar/39Ar biotite
U-Pb Zircón
Dating location
RADIOMETRIC DATING SOURCE
This work
Sellés and Gardeweg (2017)
@
J
"
;
-
Pliv
# # ## ###
Psvd
Hf
Plsa 5.000
4.000
3.000
5.000
4.000
3.000
m asl
PlHa
Hf PlHpc
PlHpc
Piic
PlHpc
Pliis
SPW-DQN
PW-DQN
MW-DQN
MWL-UQN
PW-UQN
MWS-UQN
Silala
River
A A'
Silala
Silala River
River
PW-BO
MW-BO
CW-BO
Inacaliri
River
PPla
Msvd
Msvd
Erosion escarpment
"
3672
Alignment of volcanic sources
Hydrographic basin limit
Unpaved road
Contour lines
Altitude (meters asl)
¹
Flow direction
Inclined bedding plane
Covered reverse fault
Covered normal fault
Inferred fault
Fault
( (
E E
Borehole location in map
Trace of geologic section
¢ PW-UQN
A A' ¯ ¯
/
Borehole
location #
Dacitic dome,
lava dome and
autoclastic breccia
Dacitic
ignimbrite
Andesitic
ignimbrite
Lava, andesitic and dacitic
agglomerate
PREVIOUS WORKS
68°0'W
22°0'S
D. Sellés and M. Gardeweg, 2017
(1:100.000)
N. Marinovic and A. Lahsen, 1984
(1:250.000)
A. Hauser, 1999; 2000 (without scale)
Hf
SCHEMATIC STRUCTURAL MODEL FOR REVERSE
FAULT CONTEMPORARY WITH NORMAL FAULT
Bibliographical Reference
Blanco, N. and Polanco, E., 2018. Geology of the Silala River Area, Northern Chile. Servicio Nacional de Geología y
Minería, Informe Registrado IR-18-70, 1 map at scale 1:75.000. Santiago.
Registration No.
© Servicio Nacional de Geología y Minería. Avenida Santa María 0104, P.O. Box 10465, Santiago, Chile.
National Director (S): Alfonso Domeyko L.
National Deputy Director of Geology (S): Felipe Espinoza G.
All rights reserved.
Edition
This report has been edited in accordance with the standards and / or nomenclature of the Subdirección Nacional
de Geología of Servicio Nacional de Geología y Minería.
Idiomatic and graphic control: Soraya Amar, Aníbal Gajardo, Renate Wall
Standards used
Geological Time Scale: Gradstein, F.M.; Ogg, J.G.; Schmitz, M.D.; Ogg, G.M. (editors), 2012.
Topographic base
Map scale 1:50.000, Cerro Inacaliri o del Cajón, Inacaliri and Linzor from the Instituto Geográfico Militar (IGM),
modified.
Geodesic reference
Universal Transversal de Mercator Projection (UTM), 19S zone, SIRGAS.
Scientific and technical assistance
Petrographic and radiometric dating feasibility studies: Edmundo Polanco V., Eugenia Fonseca P.
K-Ar radiometric determinations: Adrián Valeria X.; 40Ar/39Ar: Adán Ramírez B., Luis Yáñez B. Isotope geology unit of
Servicio Nacional de Geología y Minería.
U-Pb LA-ICP-MS radiometric determinatios: Marcos Suárez F., Felipe Llona R. Isotope geology unit of Servicio Nacional
de Geología y Minería. Dr. Luigi Solari from Centro de Geociencias de la Universidad Nacional Autónoma de
México (UNAM), Querétaro, México.
Geophysical studies: Jorge Vivallos C., Cecilia Donoso B., David Cáceres A.
Digital production: Cecilia Araya M., Cristian Faunes Q., y Marcos Lienlaf L., from Servicio Nacional de Geología y
Minería.
Financial support
Servicio Nacional de Geología y Minería
“Circulation hereof authorised by Resolution N° 18 of January 25 of 2019 of Dirección Nacional de Fronteras y Límites
del Estado. The publishing and circulation of maps, geographic maps or other printed material and documents referring
to or related with the borders and boundaries of Chile, in no way commit the Chilean Government, in accordance with
Article 2, letter g) of Statutory Decree N° 83 of 1979 from the Ministry o f Foreign Affairs”.
S Y M B O L O G Y
SOURCE OF INFORMATION
68°0'W
22°0'S
N. Blanco and E. Polanco, 2018
(1:75.000)
PREVIOUS WORKS
68°0'W
22°0'S
D. Sellés and M. Gardeweg, 2017
(1:100.000)
N. Marinovic and A. Lahsen, 1984
(1:250.000)
A. Hauser, 1999; 2000 (without scale)
Alcayaga, H., 2017. Characterization of the Drainage Patterns and River Network of the Silala River and Preliminary
Assessment of Vegetation Dynamics Using Remote Sensing.
Bibliographical Reference
Blanco, N. and Polanco, E., 2018. Geology of the Silala River Area, Northern Chile. Servicio Nacional de Geología y
Minería, Informe Registrado IR-18-70, 1 map at scale 1:75.000. Santiago.
Registration No.
© Servicio Nacional de Geología y Minería. Avenida Santa María 0104, P.O. Box 10465, Santiago, Chile.
National Director (S): Alfonso Domeyko L.
National Deputy Director of Geology (S): Felipe Espinoza G.
All rights reserved.
Edition
This report has been edited in accordance with the standards and / or nomenclature of the Subdirección Nacional
de Geología of Servicio Nacional de Geología y Minería.
Idiomatic and graphic control: Soraya Amar, Aníbal Gajardo, Renate Wall
Standards used
Geological Time Scale: Gradstein, F.M.; Ogg, J.G.; Schmitz, M.D.; Ogg, G.M. (editors), 2012.
Topographic base
Map scale 1:50.000, Cerro Inacaliri o del Cajón, Inacaliri and Linzor from the Instituto Geográfico Militar (IGM),
modified.
Geodesic reference
Universal Transversal de Mercator Projection (UTM), 19S zone, SIRGAS.
Scientific and technical assistance
Petrographic and radiometric dating feasibility studies: Edmundo Polanco V., Eugenia Fonseca P.
K-Ar radiometric determinations: Adrián Valeria X.; 40Ar/39Ar: Adán Ramírez B., Luis Yáñez B. Isotope geology unit of
Servicio Nacional de Geología y Minería.
U-Pb LA-ICP-MS radiometric determinatios: Marcos Suárez F., Felipe Llona R. Isotope geology unit of Servicio Nacional
de Geología y Minería. Dr. Luigi Solari from Centro de Geociencias de la Universidad Nacional Autónoma de
México (UNAM), Querétaro, México.
Geophysical studies: Jorge Vivallos C., Cecilia Donoso B., David Cáceres A.
Digital production: Cecilia Araya M., Cristian Faunes Q., y Marcos Lienlaf L., from Servicio Nacional de Geología y
Minería.
Financial support
Servicio Nacional de Geología y Minería
“Circulation hereof authorised by Resolution N° 18 of January 25 of 2019 of Dirección Nacional de Fronteras y Límites
del Estado. The publishing and circulation of maps, geographic maps or other printed material and documents referring
to or related with the borders and boundaries of Chile, in no way commit the Chilean Government, in accordance with
Article 2, letter g) of Statutory Decree N° 83 of 1979 from the Ministry o f Foreign Affairs”.
S Y M B O L O G Y
SOURCE OF INFORMATION
68°0'W
22°0'S
N. Blanco and E. Polanco, 2018
(1:75.000)
PREVIOUS WORKS
68°0'W
22°0'S
D. Sellés and M. Gardeweg, 2017
(1:100.000)
N. Marinovic and A. Lahsen, 1984
(1:250.000)
A. Hauser, 1999; 2000 (without scale)
Alcayaga, H., 2017. Characterization of the Drainage Patterns and River Network of the Silala River and Preliminary
Assessment of Vegetation Dynamics Using Remote Sensing.
REGISTERED REPORT
Larger size map in pocket on the back cover of this volume.
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270
APPENDIX D
PROYECTO MAPEO GEOLÓGICO-ESTRUCTURAL DEL ÁREA
CIRCUNDANTE AL MANANTIAL DEL SILALA, DEPARTAMENTO DE
POTOSÍ
Annex XIV Appendix D
COLUMNA ESTRATIGRAflCA
CARACTERISTlCAS DE LAS UNIDADES GEOL001CAS
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DIREMAR
CONVENIO DE COO~ERACION INTERINITITUCIONAL Y CONTRATO
DE CONSULTDRIASERGEDMIN-OIREMAR
PROYECTO MAPEO GEOLOGICD ESTRUCTURAL
.I.REASCIRCUNDANTESOELOSMANANTIALESOELSILALA
MAPA GEOLOGICO
AREA 1
C H I L E
B O L I V I A
C H I L E
B O L I V I A
Nlsg
Nis-3
Qfg
Nis-2
Nfd2
Nis-1
Nis-2
Qcf
Nfd2
Nfd2
Nlin1
Qfg
HITO-LXXV
HITO-LXXIV SILALA CHICO
HITO.LXXIII SILALA
Qa
Qc
Qc
Qc
Qcf
Qfg
Nlsg
Qc
Qm
Nlsc
Qlin2
Nlsc
Qm
Qlin2
Qc
Qlin2
Qc
Qc
Qc
Silala chico
7801
7802
7803
7809
7810
7813
7814
7816
7702
7706
7712
7713
7717
7720
4800
4500
4800
4600
4700
4500
4600
4700
4700
4600
4400
4300
4500
4600
4400
4400
4600
4500
598000
598000
599000
599000
600000
600000
601000
601000
602000
602000
603000
603000
604000
604000
605000
605000
606000
606000
607000
607000
608000
608000
609000
609000
7563000
7563000
7564000
7564000
7565000
7565000
7566000
7566000
7567000
7567000
7568000
7568000
7569000
7569000
0 1 2 km
±
GEOLOGICAL STRUCTURAL MAPPING PROJECT OF
SURROUNDING AREAS OF SILALA SPRINGS
GEOLOGICAL MAP AREA 1
REFERENCE SYSTEM: WGS84 - SIST EMA DE PROYECCIÓN UTM ZONA 19 SUR
La Paz, September 2017 Scale. 1: 30.000 Map No. 1
C O N V E N I O D E C O O P E R A C I Ó N I N T E R I N S T I T U C I O N A L Y C O N T R A T O
D E C O N S U LT O R I A S E R G E O M I N - D I R E M A R
Sedimentary units
Volcanic units
VOLCANIC CHAIN
AGUA DE PERDÍZ
1.48
1.74
5.84
6,06
(No scale ratio)
STRATIGRAPHIC COLUMN
CHARACTERISTICS OF GEOLOGICAL UNITS
Nlcn Lavas Cerro Negro
Lavas Silala Grande ª ª ª Nlsg
References
bt
px
hb
olg
qz
cpx
p
ads
biotite
pyroxene
hornblende
oligocene
quartz
clinopyroxene
pumice
andesine
GEOLOGICAL SYMBOLS
Inferred contact
Center of volcanic emission
Flow direction
Limit area 1
International border
Petrographic samples
Radiometric age
Contour lines (per 20 m)
TOPOGRAPHIC SYMBOLS
Trail, pathwalk
Wetland
Geological contact
Bt 1,48±0,02 Ma
International milestone
Loose surface, two-way
L L L L Lavas Silala Chico
L L L L
Nlsc
Nfd2 Deposit flow 2 pumicestone, sands.
Nis-2 Ignimbrite Silala 2
Nis-1 Ignimbrite Silala 1
Dacitic ignimbrite brown porphyritic, in blocks, with
andesitic monomictic clastic rocks, qz-olg-cpx-p
Dacitic ignimbrite brown porphyritic, light pink,
in blocks, with intermediate welding, qz-olg-cpx-p
Gray brown deposit. Pebbles, gravel,
Nfd1 Deposit Flow 1 volcanic glass, pumicestone, sands.
Bt 7,8 Ma
L NLlin1L L Lavas Inacaliri 1
7,8
Bt
Bt 1,48±0,02 Ma
6,04±0,07 Ma
Lavas Inacaliri 2 Porphyritic dark violet, laminated or in blocks, flow
banding. Andesites of px, px.
Porphyritic dark gray, laminated or in blocks, flow
banding. Andesites of hb, olg-bt-hb
Porphyritic dark gray, laminated or in blocks, flow
banding. Andesites of px, olg-bt-cpx
88
8Qlin2
Ignimbrite Silala 3
Porphyritic dark gray, laminated or in blocks, flow
banding. Andesites of hb, ads-bt-hb
Porphyritic gray, laminated or in blocks,
flow banding. Andesite of bt, ads-bt-hb-cpx
Dacitic ignimbrite brown porphyritic, in slabs, with
developed crystals, qz-olg-cpx-p
Brown gray deposits of pebbles, gravel,
Nis-3
Qc Colluvial deposit Pebbles and blocks
Qa Alluvial Deposit Silt, sand and clays
Qcf Colluvial-fluvial deposit Gravel, sand, silt and clays
Qm Moraine deposits Blocks, pebbles, gravel and clays
Qfg Fluvio-glacial deposit Gravel, sand and clays
8
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3,3
4
5
5.3
7
1
1.6
2
3
6
271
Annex XIV Appendix D
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272
273
Data CD
CD-ROM containing supporting data to
Annexes XI – XIV
Appendix C to Annex XIV
Blanco, N. and Polanco, E., 2018. Geology of
the Silala River Basin, Northern Chile
Volume 3 - Annexes XI-XIV to the Expert Reports