CHEMICAL WEATHERING AND ORGANIC CARBON TRANSPORT IN AN
ACTIVE MOUNTAIN BELT:
SIERRA DE LAS MINAS, GUATEMALA
THESIS
Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in
the Graduate School of The Ohio State University
By
Brandon Collins McAdams
Graduate Program in Earth Sciences
The Ohio State University
2012
Master's Examination Committee:
Dr. Anne E. Carey, Advisor
Dr. Carla Restrepo
Dr. W. Berry Lyons
Dr. Michael Barton
Copyright by
Brandon Collins McAdams
2012
Abstract
Rivers and streams draining active mountain terrains are known to transport an
amount of sediment and chemical weathering products that is disproportionately large
compared to the amount of land area occupied by active mountain terrains on the earth’s
surface. SuchThese high rates of material transport are attributed to the high rates of
physical erosion that accompany active mountain building events. Physical erosion
mobilizes particulate material, including organic carbon, and can expose un-weathered
bedrock to atmospheric weathering. Chemical weathering in active mountain terrains
plays a significant role in the global carbon cycle and thus plays a role in global climate
change over geologic time scales by removing CO2 from the atmosphere. The
relationship between CO2 and climate has been illustrated, as has the theory that current
atmospheric CO2 concentrations will result in global climate change. It is critical that
carbon fluxes from the atmosphere be quantified in order to better understand the
mechanisms controlling atmospheric CO2 concentrations.
Natural mechanisms controlling atmospheric CO2 concentrations vary regionally,
and so it is important that CO2 yields from watersheds in previously unstudied actively
uplifting regions be quantified and controls on these yields elucidated. Here, CO2 yields
from watersheds draining the Sierra de las Minas in Guatemala are quantified. These
yields are similar to the high yields observed in other active mountain regions worldwide
and underscore the importance of these areas in the global carbon cycle and global
ii
climate forcing. In addition, this study also supports the positive relationship between
annual precipitation and chemical yields that has been observed elsewhere. This
relationship may be influenced by mountain uplift causing local orographic increases in
precipitation.
Extreme storm events such as typhoons and hurricanes have been shown to
transport a large percentage of annual particulate organic carbon yields. This transport of
particulate organic carbon can be a sink of atmospheric CO2 if it can be buried and
removed from the atmosphere before it is consumed and oxidized. In 1998, Hurricane
Mitch triggered widespread landslide activity throughout the Sierra de las Minas that
mobilized material, including particulate organic carbon. Here, relationships among
carbon and nitrogen concentrations and δ13C in streambed sediments and shale were used
to speculate on the fate of material mobilized by landslides during Hurricane Mitch.
These speculations are supported by satellite observations made immediately following
Hurricane Mitch that map the extent of landslide scours. It is speculated herein that much
of the landslide transported organic carbon was efficiently removed from the fluvialhillslope interface and buried. These speculations are supported by the noted importance
of event controlled carbon export in regional organic carbon yields.
iii
Dedication
This document is dedicated to my family, friends, and professors, who have supported,
distracted, and inspired me when I needed it most.
iv
Acknowledgments
I am most grateful to my advisor, Dr. Anne E. Carey, who took a chance on a
meandering creative writing student and channeled my energies to produce this work. I
am also grateful to Drs. W. Berry Lyons, Michael Barton, and Carla Restrepo, who have
challenged me and provided meaningful insight into this project. I want to extend a
special thanks to Dr. Restrepo for her patience and guidance during my first field season.
I am also grateful to Andi Portier for her patience and assistance in the field that made
sampling not just possible, but efficient.
I would not have been able to conduct any sampling without the help of the
Defensores de la Naturaleza, and, more specifically, Ariel, Jorge, Ervin, Belizario, and
Marcello, who forged relationships and trust between us and the communities whose
streams we sampled. A special thanks to Marcello should be extended for watching over
our truck, providing a place to sleep, a warm meal, and even a dry pair of pants when I
was caught unprepared for rain. I also want to thank the women of Marcello’s family who
were kind and generous in letting a man cook in their kitchen. Thanks should also be paid
to Hans, Luisa, Claus, Katarina, and Alberto Droege for providing a home and family
when I had never felt more distance between my own home and family. I must also
acknowledge the culinary acumen of Patti and Aura, without which I might not have been
able to keep my sanity.
v
I want to thank Dr. Sue and Ms. Kathy Welch for their willingness to assist and
teach me many of the analytical techniques used in this study. Sue deserves a special
thanks for letting me be the first to play with her new instruments to obtain the dissolved
and particulate organic carbon, nitrogen, and carbon isotope data presented in this study. I
also extend thanks to the support staff at PANalytical, Kelly Duerling, and Dr. Steve
Goldsmith for collectively training me to perform X-ray fluorescence analysis.
I cannot conclude without acknowledging the support of my family and friends.
My fiancée, Becky Ascher, has kept me centered and focused, was always available to
Skype during my ten weeks in the field, and made me laugh at times when I needed to
smile. She was also the person I first talked to when I walked into the Ohio State
University admissions office looking to add a Bachelor’s in Earth Sciences to my creative
writing degree. Without her help, I would have never talked to Dr. Carey and might not
be writing this document today. I would not have had the confidence to pursue this
degree without my parents’ love and faith in their only child and son. I must also thank
Allison Kreinberg, Maya Wei-Haas, Jeff Pigott, Steve Levas, and Joe Voyles for the
many conversations we shared about research, fantasy football, grilled cheese, and other
topics that broke up the work day.
vi
Vita
June 2005 .......................................................The Pendleton School, Bradenton, Florida
May 2009 .......................................................B.A. English-Creative Writing, Denison
University, Granville, Ohio
August 2010 to present ..................................Graduate Research Associate, School of
Earth Sciences, The Ohio State University
Fields of Study
Major Field: Earth Sciences
vii
Table of Contents
Abstract ............................................................................................................................... ii
Dedication ........................................................................................................................ ivv
Acknowledgments............................................................................................................... v
Vita.................................................................................................................................. vvii
List of Tables ................................................................................................................... xxi
List of Figures ................................................................................................................. xxii
Chapter 1: Introduction ...................................................................................................... 1
Chapter 2: Geology, Geomorphology, Climate, and Sample Site Description .................. 6
2.1. Geologic Setting ....................................................................................................... 6
2.2. Geomorphic Setting and Climate ............................................................................. 7
2.3. Sample Site Description ........................................................................................... 8
Chapter 3: Methods ........................................................................................................... 21
3.1. Bottle Cleaning....................................................................................................... 21
3.2. Sample Collection .................................................................................................. 21
3.3. Sample Storage and Filtering ................................................................................. 22
3.4. Analytical Methods ................................................................................................ 23
viii
3.4.1. Field Analyses ................................................................................................. 23
3.4.2. Laboratory Analyses ........................................................................................ 24
3.4.3. Geochemical Modeling.................................................................................... 27
3.5. Incubation Experiments.......................................................................................... 28
Chapter 4: Results ............................................................................................................. 30
4.1. Stream Discharge and Watershed Area .................................................................. 30
4.2. Stream Temperature, pH, and Conductivity........................................................... 31
4.3. Geochemistry of Stream Waters ............................................................................ 32
4.3.1. Major Element Concentrations ........................................................................ 33
4.3.2. Spatial Variation in Major Element Concentrations........................................ 34
4.3.3. Temporal Variation in Major Element Concentrations ................................... 36
4.3.4. Major Element Ratios ...................................................................................... 37
4.3.5. Chemical Weathering Fluxes and Yields ........................................................ 39
4.4. Organic Chemistry of Stream Waters .................................................................... 42
4.4.1. Dissolved Organic Carbon in Streams............................................................. 42
4.4.2. Dissolved Nutrients in Streams ....................................................................... 43
4.5. Day-to-Night, Night-to-Day Sampling .................................................................. 43
4.6. Dissolved Organic Carbon Incubation Experiment ............................................... 45
4.7. Streambed Sediment and Bedrock Shale Chemistry .............................................. 46
ix
4.7.1. Major and Minor Element Chemistry.............................................................. 46
4.7.2. Streambed Sediment Mineralogy .................................................................... 48
4.7.3. Organic Carbon and Nitrogen Chemistry ........................................................ 48
Chapter 5: Discussion ....................................................................................................... 87
5.1. Watershed Areas and Discharge ............................................................................ 87
5.2. Chemical Weathering Fluxes and Yields ............................................................... 89
5.3. Streambed Sediment Geochemistry ....................................................................... 91
5.4. Dissolved Organic Carbon and Nutrient Dynamics ............................................... 91
5.4.1. Incubation DOC Dynamics ............................................................................. 92
5.5. Dissolved Organic Carbon Fluxes and Yields ....................................................... 92
5.6. Event Particulate Organic Carbon Export Suggested by Sediment Chemistry ...... 94
Chapter 6: Conclusions and Future Directions ............................................................... 111
6.1. Conclusions .......................................................................................................... 111
6.2. Future Directions .................................................................................................. 113
References ....................................................................................................................... 114
Appendix A: Ion Chromatography analysis of waters .................................................... 121
Appendix B: Skalar™ Nutrient analysis of waters ......................................................... 125
Appendix C: Dissolved organic carbon and stable carbon-13 isotope analysis ............. 130
x
List of Tables
Table 2.1. Physical Characteristics of Streams ................................................................. 11
Table 4.1. Watershed Area and Stream Discharge ........................................................... 49
Table 4.2. Field Chemistry and Discharge........................................................................ 51
Table 4.3. Aqueous Major Ion Chemistry ........................................................................ 53
Table 4.4. Total Cation, Silica, and CO2 Yields from Silicate Weathering ...................... 57
Table 4.5. DOC, DON, and DOP Chemistry .................................................................... 61
Table 4.6. Diel Major Ion Chemistry ................................................................................ 64
Table 4.7. Diel DOC, DON, and DOP Chemistry ............................................................ 66
Table 4.8. Major and Minor Elements in Streambed Sediments and Shale ..................... 68
Table 4.9. Mineralogy of Streambed Sediments ............................................................... 70
Table 4.10. Organic Carbon and Nitrogen in Streambed Sediments and Shale ............... 71
Table 5.1. CO2 Yields from World Rivers........................................................................ 98
Table 5.2. Dissolved Organic Carbon Fluxes and Yields ................................................. 99
Table 5.3. Dissolved Organic Carbon Yields from World Rivers .................................. 102
xi
List of Figures
Figure 2.1. Rio Matanzas Mean Daily Discharge (May 2003 to May 2010) ................... 12
Figure 2.2. Geologic Map of Study Area .......................................................................... 13
Figure 2.2. Tectonic Map of Study Area .......................................................................... 14
Figure 2.3. Map of Rio Polochíc Watershed and Polochíc Fault...................................... 15
Figure 2.4. Pictures of Sediment Plumes from Rio Polochíc ........................................... 16
Figure 2.5. Map of Watershed Sampling Points ............................................................... 17
Figure 2.6. Nested Watersheds of Rio Matanzas .............................................................. 18
Figure 2.7. Nested Watersheds of Rio Pueblo Viejo and Rio Samilja ............................. 19
Figure 2.9. Nested Watersheds of Quebrada Chajonja ..................................................... 20
Figure 2.10. Map of Shale Sample Locations ................................................................... 21
Figure 4.1. Stream Discharge v. Watershed Area ............................................................. 72
Figure 4.2. Ca2+ v. F- (μmol L-1) ....................................................................................... 73
Figure 4.3. Na+K v. Ca+Mg (μmol L-1) (corrected for precipitation) ............................. 74
Figure 4.4. Total Cations (TZ+) v. Si (μmol L-1) ............................................................. 75
Figure 4.5. Ca+Mg v. HCO3 (μeq L-1) .............................................................................. 76
Figure 4.6. (A). HCO3/Na v. Ca/Na (molar ratios) ........................................................... 77
Figure 4.6. (B). Mg/Na v. Ca/Na (molar ratios) ............................................................... 78
Figure 4.7. Total Cation Flux v. Watershed Area ............................................................. 79
Figure 4.8. Relative Input of Solutes in Streams .............................................................. 80
xii
Figure 4.9. Dissolved Organic Carbon v. δ13C ................................................................. 81
Figure 4.10. Dissolved Organic Carbon v. SUVA280........................................................ 82
Figure 4.11. DON and NO3- during Day-to-Night, Night-to-Day sampling .................... 83
Figure 4.12. Dissolved Organic Carbon v. Time for Incubation Experiment................... 84
Figure 4.13. Major Elements of Streambed Sediments Normalized to Bedrock Shale .... 85
Figure 4.14. Major Elements of Streambed Sediments Normalized to Gneiss ................ 86
Figure 5.1. Dry Season Rio Matanzas Mean Daily Discharge (2004 to 2010) .............. 103
Figure 5.2. Watershed Area v. Discharge (South Side Watersheds) .............................. 104
Figure 5.3. Relative Input of Solutes in Streams Before and After Rainfall .................. 105
Figure 5.4. Carbon to Nitrogen v. δ13C in Streambed Sediments and Bedrock Shale .... 106
Figure 5.5. Carbon Content v. δ13C in Streambed Sediments and Bedrock Shale ......... 107
Figure 5.6. Picture of Riparian Vegetation for Tributary 2 to Chajonja ......................... 108
Figure 5.7. (A). Map of Landslides and Scours Triggered by Hurricane Mitch............. 109
Figure 5.7. (B). Map of Landslides and Scours Triggered by Hurricane Mitch ............. 110
xiii
CHAPTER 1: INTRODUCTION
Watersheds draining tectonically active mountain terrains have been shown to
transport an amount of sediment, organic carbon, and chemical weathering products
disproportionate to their size (e.g. Milliman and Syvitski, 1992, Lyons et al, 2002, Carey
et al, 2005ab, 2006, Goldsmith et al, 2008ab). This transport of organic carbon and
chemical weathering products can act as a sink of carbon from the atmosphere if such
transport delivers the carbon to and buries it in a basin, effectively removing it from the
atmospheric oxidation until it is exhumed.
The dissolution products of silicate mineral weathering by atmospheric carbonic
acid (formed by the interaction of H2O and CO2 in the atmosphere) interact with the
carbon in that acid to precipitate carbonate minerals in basins that form limestones and
dolomites over geologic time. This formation of carbonate rocks plays an important role
in the global carbon cycle over geologic time scales (e.g. Berner, 1992; Raymo and
Ruddiman, 1992). The burial of particulate organic carbon in suboxic and anoxic basins
can represent a biologically sourced sink of carbon from the atmosphere. The efficiency
of this sink is dependent on the stability of the organic carbon in the basin and also on the
rate of regrowth on the land where this carbon was originally sourced from, e.g. regrowth
on a landslide scar.
Over timescales of thousands to millions of years, these sinks counterbalance the
inputs of carbon to the atmosphere by volcanic outgassing, metamorphism, and
1
exhumation (Raymo and Ruddiman, 1992). Quantification of atmospheric carbon sources
and sinks has become increasingly important in the midst of current global climate
change related to human-induced increases in atmospheric CO2 concentrations, which are
rising too fast for long-term carbon sinks to counterbalance. Given the relationship
between atmospheric CO2 concentrations and global temperatures illustrated by an
800,000 year ice core record from EPICA Dome C (Kӧhler et al., 2010), the prospect of
human-induced climate change is very real. To best prepare for and maybe even prevent
future climate scenarios it is necessary to understand what natural sinks of carbon exist
that may help attenuate human CO2 emissions.
Landslides are a dominant geomorphic process influencing short and long term
dynamics of many steep landscapes on a global scale (Thomas, 1994, 2004). Landslides
influence regional and global carbon cycle dynamics by mobilizing soil and plant
material down a hillslope where it might be delivered to the fluvial network and exported
further downstream to a basin. This stripping of soil and regolith can expose fresh
bedrock to chemical weathering, which would act to accelerate CO2 drawdown from
chemical weathering. Extreme rainfall events are effective triggers of shallow landslides
(Restrepo et al., 2009; Ramos-Sharrón et al., 2012), and have been shown worldwide to
significantly increase rates of fluvial sediment discharge (e.g. Galewsky et al., 2006;
Goldsmith et al., 2008b; Hilton et al., 2008). In addition, extreme storm events have also
been shown to increase fluvial dissolved organic carbon transport, accounting for 25 % to
43 % of the annual dissolved organic carbon export (Yoon and Raymond, 2012). Seismic
activity such as earthquakes can also trigger landslides, however this study focuses on
2
landslide activity in the Sierra de las Minas of Guatemala triggered by Hurricane Mitch in
1998.
Trierweiler et al., (2010) examined the effects of Hurricane Mitch triggered
landslides on stream carbon and nutrient transport, and on chemical weathering yields in
watersheds draining the south side of the Sierra de las Minas. The south side of the Sierra
de las Minas receives approximately 500 mm yr-1 of rainfall compared to the 2500 to
5000 mm yr-1 that falls on the north side of the mountains (Campbell, 1982, Holder,
2006). North side watersheds are the focus of this study. Such a difference in hydrologic
budget provides an ideal environment to determine the influence of precipitation amount
on chemical weathering yields.
The work discussed herein will examine the relationships among hydrologic
budget, extreme storm events, and landslides as they effect chemical weathering, and
fluvial organic carbon transport. The goals of this research were to 1) calculate fluvial
organic and inorganic carbon yields in streams draining the north side of the Sierra de las
Minas, Guatemala, 2) assess the impact of precipitation on stream carbon transport and
chemical weathering, and 3) examine the importance of extreme storm events in
particulate organic carbon transport. To accomplish these aims, the following hypotheses
were tested:
Hypothesis 1: Streams draining the north side of the Sierra de las Minas will yield more
carbon and chemical weathering products than streams draining the south side due to the
greater hydrologic budget of the north side compared to the south side of the mountains.
3
Hypothesis 2: Most of the particulate organic carbon mobilized by landslide activity
during Hurricane Mitch has been transported out of the watersheds draining the north
side of the Sierra de las Minas.
Hypothesis 1 was tested by collecting water samples from and measuring
discharge in streams draining the north side of the Sierra de las Minas. These water
samples were analyzed for major element concentrations associated with silicate and
other mineral weathering processes. This major element chemistry was used to calculate
the weathering rates for the watershed area upstream of the sampling location. The
weathering rates were then used to calculate CO2 drawdown rates normalized to
watershed area, or yields that were compared to CO2 yields of watersheds draining the
south side of the Sierra de las Minas studied by Annette Trierweiller (Trierweiller, 2010;
Trierweiller et al., in review). Dissolved organic carbon (DOC) in streams was also
quantified, providing a value for the DOC export from these rivers.
Hypothesis 2 was tested by collecting streambed sediment and bedrock shale
samples that were then analyzed for organic carbon, total nitrogen, and stable carbon-13
isotope composition of that organic carbon. These chemical signatures were then
compared between the streambed sediment and bedrock shale samples to determine the
origin of carbon in the streambed sediments. Carbon from the bedrock shale, being
uplifted marine sediments, should have a different isotope composition and organic
carbon to nitrogen ratio than any modern soil carbon delivered to the streambeds (e.g.
Redfield, 1934; Batjes, 1996; Masiello and Druffel, 2001). This distinction between
marine shale and terrestrial soil carbon was then used to speculate on the source or
4
sources of organic carbon in the streambed sediments. Organic carbon in streambed
sediments that was chemically distinct from the organic carbon in bedrock shale was
thought to be mobilized soil from upstream landslide activity. The occurrence of soil
carbon in streambed sediments was then compared to the occurrence of landslides
triggered upstream by an extreme storm event (Hurricane Mitch 1998, using maps
created by the USGS Hurricane Mitch project) to understand the fate of that landslide
mobilized soil in the fluvial network.
5
CHAPTER 2: GEOLOGY, GEOMORPHOLOGY, CLIMATE, AND SAMPLE SITE
DESCRIPTION
The Sierra de las Minas are located in eastern Guatemala and are bordered by the
Polochíc river valley to the north and the Motagua river valley to the south. The Rio
Motagua flows into the Caribbean Sea and the Rio Polochíc flows into Lago Izabal, a
shallow inland lake. Deposition at the mouth of the Rio Polochíc has created a deltaic fan
that extends into Lago Izabal. The north to south extent of this fan represents oscillation
of the Polchíc’s mouth related to the meandering of the Polochíc over time. The current
mouth of the Polochíc empties into the north end of Lago Izabal where noticeable
sediment plumes exist even during the dry season (approximately January through April).
The differences between the hydrology of the wet season and the dry season are easily
observed in a seven year record of discharge from the Río Matanzas (a river sampled in
this study that delivers water and sediment to the Río Polochíc) (Fig. 2,1).
2.1. Geologic Setting
This study focuses on the north side of the Sierra de las Minas, which is largely
composed of the San Agustín formation (Paleozoic age, uplifted quartz-monzonite gneiss
with various schists), the Santa Rosa group comprising the Pizarro shale (a succession of
fossiliferous shales Carboniferous to Permian in age representing a paleo-marine shelf),
and an unnamed igneous plutonic formation (Bonis et al., 1970, Wyel, 1980, Bundschuh
and Alvarado, 2007) (Fig. 2.2).
6
The tectonic setting of the Sierra de las Minas is complex. The mountains sit
between the Polochíc North Izabal faults to the north and the Motagua fault to the
south.The Polochíc fault extends from the Middle America Trench through Chiapas,
Mexico and Central Guatemala (Burkart, 1983), intersecting the Motagua fault southeast
of Lago Izabal (Fig. 2.3). The North Izabal fault is a normal fault that runs tangential to
the Polochíc fault, but curves north of Lago Izabal to parallel the Motagua fault (Fig.
2.3). The Motagua fault is a left lateral strike-slip regime that runs south of the Sierra de
las Minas (Burkart, 1983). Burkart (1983) determined the Polochíc fault has undergone
130 km of left-lateral slip since the deposition of Miocene ignimbrites. The Polochíc fault
is also thought to terminate “against a zone of extension…that is part of a set of
parallelogram-shaped depressions that continues offshore into the Bartlett Trench,”
(Muehlberger and Ritchie, 1975).The North Izabal fault shows signs of recent activity
(Schwartz et al., 1979). The Motagua fault slipped 1.1 m along 230 km of its boundary,
along with 0.3 m of vertical displacement in 1976 (Plafker, 1976). This active fault zone
is the result of an oblique collision of the North American plate into the Caribbean plate.
Sequences of this collision are responsible for the lithology of the Sierra de las Minas
(Wyel, 1980). Lago Izabal, the Río Polochíc, and its headwaters draining the north slopes
of the Sierra de las Minas are geomorphic features in this active tectonic terrain.
2.2. Geomorphic Setting & Climate
The Río Polochíc drains an area of 5247 km2 between the Sierra de Santa Cruz to
the North and the Sierra de las Minas to the South, following the Polochíc fault before
emptying into Lago Izabal (Brinson, 1976; Burkart, 1983; Michot et al., 2002) (Fig. 2.4).
7
Noticeable sediment plumes exist at the mouth of the Polochíc building upon established
multi-lobate deltas extending into Lago Izabal (Brinson, 1976; Michot et al, 2002) (Fig.
2.5). Michot et al. (2002) suggest sedimentation rates ≥30 cm yr-1 in Lago Izabal as 60
cm cores were drilled and no sedimentary structures (e.g. turbidites) evident of the
Hurricane Mitch flooding event that occurred 2 years prior to sampling were found.
However, no geochemical analyses were performed to confirm or deny this sedimentation
rate.
The main channel of the Polochíc begins at roughly 100 m above sea level and
meanders 200 km with a slope of 1.05 × 10-2 (m rise/m channel length) to empty into
Lago Izabal at 3–4 m above sea level (Brinson, 1976). The area surrounding the main
channel of the Polochíc is heavily cultivated compared to the less cultivated, steep
northern slopes of the Sierra de las Minas on the south side of the basin (Bundschuh and
Alvarado, 2007; personal observation). The steep slopes of the Sierra de las Minas are
prone to landslides during catastrophic rainfall events such as Hurricane Mitch in 1998
(Resptrepo et al., 2009; Ramos-Sharrón et al., 2012).
The Sierra de las Minas rise ~3000 m above sea level (Bucknam et al., 2001), an
elevation high enough to create a rain shadow between the north and south side of the
range (Campbell, 1982). The difference in rainfall is usually 2000 mm yr-1 (2500 mm yr˗1
on the north side to 500 mm yr-1 on the south side)(Campbell, 1982, Holder, 2006). Such
a rain shadow creates a substantial difference in hydrologic budgets between the north
and south sides of the Sierra de las Minas.
8
2.3. Sampling Sites
Sixteen rivers and streams draining the north side of the Sierra de las Minas were
sampled over the course of a 10 week period between January 21st and March 13th, 2012.
These rivers and streams drained a range of lithologies (Figure 2.6; Table 2.1). Two
rivers, Quebrada Carabajal and Tributary 2 to Chajonja, each drained a single lithology
(Pizarro shale and San Agustín gneiss, respectively). The Rio Zarco, Rio Tze, Rio Raxon,
and Quebrada Cancor drained mostly San Agustín gneiss above the sampling locations.
The Tributary 2 to Chajonja and Quebrada Chajonja watersheds straddled the lithological
divide separating the San Agustín gneiss from the Pizarro shale. Rio Samilja, Rio Toila,
Rio Sibija, Rio Mululha, and Rio Pancajoc watersheds comprised a mixture of Pizarro
shale and granite. The Rio Sibija watershed was composed mostly of Pizarro Shale. Rio
Sibija, Rio Mululha, and Rio Samilja watersheds also included a small portion of a
Permian carbonate-dolomite sequence. The Rio Matanzas watershed included the widest
range of lithologies and had the highest area underlain by the Permian carbonate
sequence (roughly 25%). The Rio Matanzas watershed also comprises San Agustín
gneiss, Pizarro shale, and granite.
Four rivers had subwatersheds within them that were sampled (Rio Matanzas, Rio
Pueblo Viejo, Rio Samilja, and Quebrada Chajonja) (Table 2.1). The Rio Matanzas
watershed includes the Rio Sibija, Rio Mululha, and Rio Pancajoc (Figure 2.7). The Rio
Pueblo Viejo includes input from Rio Chiquito, Rio Raxon, Quebrada Cancor, and
Quebrada Chajonja (Figure 2.8). The Rio Samilja was sampled at three locations from
upstream to downstream. The downstream location of the Rio Samilja included input
9
from the Quebrada Carabajal (Figure 2.8). The Quebrada Chajonja watershed includes
two tributary watersheds that were also sampled (Tributary 1 and Tributary 2 to
Chajonja) (Figure 2.9). Bedrock shale samples were collected throughout of the study
area from east to west where lightly weathered outcrops were found. These sampling
locations are shown in Figure 2.10.
10
Table 2.1 Physical Characteristics of Streams
Watershed
Stream
Order
Bedrock Lithology*
1. Rio Raxon
3
Pzm >> CPsr
2. Quebrada Chajonja
2
CPsr ~ Pzm
3. Trib. 1 to Chajonja
1
Pzm
4. Trib. 2 to Chajonja
1
Pzm ~ CPsr
5. Q. Carabajal
2
CPsr
6. R. Samilja US
3
I > CPsr > Pzm
7. R. Samilja MS
3
CPsr > I > Pzm
8. R. Samilja DS
3
CPsr > I > Pzm > Pc
9. R. Toila
3
CPsr ~ I
10. R. Matanzas
4
Pzm ~ Pc > CPsr > I ~ Pi ~ >> JKts
11. R. Sibija
2
CPsr > I
12. R. Mululha
3
I > CPsr > Pzm >> Pc
13. R. Pancajoc
3
CPsr > I > Pzm >> Pc
14. R. Chiquito
2
CPsr ~ Pzm
15. Q. Cancor
2
Pzm > CPsr
16. R. Pueblo Viejo
4
Pzm > CPsr >> I > Qa
17. R. Zarco
3
Pzm >> CPsr
18. R. Tze
3
Pzm >> CPsr
Subwatersheds**
3, 4
6
6, 7
11, 12, 13, 14
1, 2, 14, 15
*Pzm = San Agustín Gneiss; CPsr = Pizarro Shale; I = Granitic Pluton; Pc = Permian Dolomite; Pi = Permian Igneous; JKts = Jurrasic
to Cretaceous sandstone; Qa = Quaternary Alluvium
**Numbers for subwatersheds correspond to numbers next to the names of the watersheds in the first column
11
3500
3000
Discharge (m3/s)
2500
2000
1500
1000
500
0
May 1,
2003
May 1,
2004
May 1,
2005
May 1,
2006
May 1,
2007
May 1,
2008
May 1,
2009
May 1,
2010
Date
Figure 2.1. Mean daily discharge for Río Matanzas from May 1, 2003 to May 1, 2010
(from INSIVUMEH, pers. comm.). Boxes are around discharges from the dry season
(January through April) and correspond to the same months of the 2012 sampling period.
12
Figure 2.2. Section of the geologic map (from Bonis, 1970) of the study area. Pzm
(purple), CPsr (light blue), Pc (dark blue) and I (red) correspond to the San Augustín
formation, the Santa Rosa group and Pizarro shale, a Permian dolomite, and the unnamed
igneous province respectively. The highest peaks of the Sierra de las Minas are between
2000 and 2400 m a.s.l. The white Qa unit begins at ~200 m a.s.l. The lake in the upper
right is Lago Izabal.
13
Figure 2.3. Map of Polochíc, Motagua, and North Izabal faults. Note the parallel trend of
the North Izabal and Motagua faults. The Izabal graben lies between the Polochíc and
North Izabal faults. Yellow outlines Sierra de las Minas. Adapted from Burkart (1983).
14
Figure 2.4. Map of Sierra de las Minas and Río Polochíc watershed. Red line marks
boundary of Río Polochíc watershed. Green line shows the Polochíc fault. Blue line is the
main channel of the Río Polochíc. Compiled from Burkart (1983) and Brinson (1976).
15
Figure 2.5. Sediment plumes from the NE (left) and S (right) branches of the Polochíc
delta. Taken from Michot et al. (2002).
16
17
Figure 2.6. Maps of sampling locations showing topography (top) and geology (bottom) of the study area. Red lines on the
geologic map mark watershed boundaries. Names of watersheds are listed. Inset shows location of study area in Guatemala.
17
10 km
N
18
10. Rio Matanzas
11. Rio Sibija
12. Rio Mululha
13. Rio Pancajoc
Figure 2.7. Subwatersheds upstream of the Rio Matanzas sampling point.
18
2 km
N
5 km
N
19
5. Quebrada Carabajal
6. Rio Samilja Upstream
7. Rio Samilja Midstream
8. Rio Samilja Downstream
1. Rio Raxon
2. Quebrada Chajonja
3. Tributary 1 to Chajonja
4. Tributary 2 to Chajonja
14. Rio Chiquito
15. Quebrada Cancor
16. Rio Pueblo Viejo
Figure 2.8. Subwatersheds upstream of Rio Pueblo Viejo (left) and Rio Samilja (right) sampling points. Boundaries between
points 6, 7, and 8 represent a sequences of samples collected from upstream to downstream in the Rio Samilja.
19
1 km
N
2. Quebrada Chajonja
3. Tributary 1 to Chajonja
4. Tributary 2 to Chajonja
Figure 2.9. Subwatersheds upstream of Quebrada Chajonja sampling point.
20
N
5
km
21
Figure 2.10. Locations showing where shale samples were collected from outcrops are labeled by name. Numbers
correspond to streams sampling locations shown in Figure 2.5.
21
CHAPTER 3: METHODS
3.1. Bottle Cleaning
The following two procedures were used to clean bottles prior to sampling and
filtering in the field:
1) Rinse 5 times with 18.2 MΩ deionized water (DI), soak in DI for two weeks, then rinse
5 times and fill with DI.
2) Rinse 5 times with DI, soak in 5% HNO3 for one week, rinse and soak in DI for one
week, then rinse 5 times and fill with DI.
Nalgene™ low density polyethylene bottles used for field collection of major ion and
nutrient samples and for filtration of major anion and nutrient samples were cleaned by
procedure 1. Nalgene™ low density polyethylene bottles used for field collection of
dissolved organic carbon samples and for filtration of major cation samples were cleaned
by procedure 2. Glass vials used for filtration of dissolved organic carbon samples were
pre-cleaned by the manufacturer and I-Chem® certified.
3.2. Sample Collection
Stream water and streambed sediment samples were collected from 18 locations
on the north slope of the Sierra de las Minas, each within the Polochic River watershed.
Of these 18 locations, 13 of the sites were sampled on at least four separate occasions, 3
of the sites on two separate occasions, and 2 of the sites only once. In addition, hourly
and bi-hourly samplings were conducted at two of the sites to observe any change in
22
water chemistry during the transition from day to night and then from night to day. All
sampling was conducted during the dry season from January 21 to March 13, 2012.
Major ions, nutrients, silica and DOC samples were collected by placing the
bottles into the water, mouth downstream, and rinsing three times with stream water
before collection, making sure to cap the sample across the surface to air interface (after
Lyons et al. 2005). A bulk precipitation sample was collected for major ion, nutrient, and
silica analysis at Finca la Constancia (15.300227N, 89.724101W, NAD83) over nine
weeks in one 250 mL Nalgene™ LDPE bottle which had been cleaned using procedure 1.
At all times during the collection of stream water samples, new Kimberley Clark PurpleNitrile* gloves were worn. Streambed sediment samples, sand sized or finer grained,
were collected using a stainless steel spatula from undisturbed sediments. Bedrock shale
samples were collected from outcrops near or on the way to the stream collection sites.
3.3. Sample Storage and Filtering
All samples were kept in the dark once collected and either filtered or refrigerated
within 24 hours of collection. Most samples were either filtered or refrigerated within 10
hours of collection. Samples were refrigerated immediately after filtering. Samples
collected for analysis of dissolved organic carbon were filtered through 0.7 μm Millipore
glass fiber filters directly into I-Chem® certified amber glass vials using a glass filter
tower and fritted glass funnel with a vacuum bell-jar after Carey et al. (2005a). Filters
had been combusted at 450°C for 2 hours before use. The glass filter tower and frit were
cleaned according to procedure 2 then combusted at 450°C for 4 hours before use.
23
Samples filtered for dissolved organic carbon analysis were acidified with 1N HCl to a
pH between 2 and 3 immediately after filtering.
Samples collected for major ion and nutrient analysis were filtered through 0.45
μm pore size Whatman Nucleopore filters directly into Nalgene™ low density
polyethylene bottles using a polycarbonate filter tower and fritted polycarbonate funnel
with a vacuum bell-jar after Lyons et al. (2005). Before use, the polycarbonate filter
tower and fritted funnel were cleaned according to procedure 1. Samples filtered for
analysis of major cations were filtered into bottles cleaned according to procedure 2 and
immediately acidified after filtering to a pH between 3 and 4 using 1 N HCl. Samples
filtered for major anion and nutrient analysis were filtered into bottles cleaned according
to procedure 1 but not acidified.
3.4. Analytical Methods
3.4.1 Field Analyses
Conductivity, pH, dissolved oxygen, and temperature measurements were made at
the sampling location using an Orion field meter either by inserting the probes directly
into the stream after sampling or into a 1 L plastic beaker filled with stream water if the
flow was too turbulent for the meter to stabilize in the stream. Alkalinity was analyzed in
the field using a Hach digital titration field kit with a bromcresol green/phenol phthaline
indicator and a 0.01 N HCl solution in 20 mL of stream water.
Stream flow measurements were recorded as the modal flow over a continuous
minute of measurement by an OTT Acoustic Doppler Current meter. The USGS short
term gauging method was followed to divide the cross section into rectangular segments
24
(Rantz, 1982). Flow was measured at 0.2 and 0.8 of the depth (h) if h > 10 cm (Rantz,
1982). If h ≤ 10 cm, then flow was measured at 0.6h.
Chemical fluxes were calculated using measured and estimated stream flows.
Where flow was not able to be measured, it was estimated using an equation derived from
the linear relationship observed between discharge and watershed area discussed in
section 4.1. Fluxes for samples taken from Rio Samilja, Rio Toila, Rio Matanzas, Rio
Mululha, Rio Pancajoc, Rio Pueblo Viejo, Rio Zarco, and Rio Tze were calculated using
discharges estimated from this relationship between discharge and watershed area. Fluxes
for two samples taken from Rio Raxon and one sample taken from Rio Sibija were
calculated using the highest measured flow for that sample site. Those three samples were
taken when stream stage and flow made flow too dangerous to gauge. It was reasoned
that discharge during these three sampling times was greater than the highest measured
discharge at the respective locations (Rio Raxon and Rio Sibija). Fluxes for two samples
from Quebrada Carabajal and one sample from Quebrada Cancor were calculated using
the lowest measured flow for that sample. When these three samples were taken, stream
stage was not noticeably different than when discharge was measured.
3.4.2 Laboratory Analysis
Major ion concentrations of water samples were determined using a DX-120 Ion
Chromatograph following the methods of Welch et al. (1996). Nutrient (NH4, NO3+NO2,
Total Nitrogen, PO4, Total Phosphorous) and dissolved silica concentrations of water
samples were obtained using a Skalar SAN++ nutrient analyzer using the method
supplied by the manufacturer. At least five analyses of 3–4 different standard
25
concentrations were run as unknowns with each analytical run and revealed accuracies
within 5% for major ion and nutrient analysis. Precision was determined by repeating
both standards and samples at least five times over the course of a run and revealed
precision with 2% for major ion and nutrient analyses.
Dissolved organic carbon concentrations and δ13C of dissolved organic carbon
were measured using an OI Wet Chemistry TOC in line with a Picarro 1111-is Cavity
Ringdown Spectrometer. Manufacturer methods provided by OI Analytical were used to
analyze for dissolved organic carbon. Precision and accuracy for DOC analyses were
determined by running multiple replicates of standards and samples and revealed both
precision and accuracy of DOC measurements to be within 2%. To analyze for δ13C of
dissolved organic carbon, the manufacturer’s method was modified to inject a larger
volume of sample and provide a large enough CO2 signal for accurate δ13C
measurements. Single 8 mL injections of sample were analyzed in triplicate over the
course of a single run. The evolved CO2 gas from each 8 mL injection was then collected
in a bag and actively sampled by the Picarro 1111-is to determine δ13C. Triplicate single
injections were the only way to obtain triplicate δ13C analyses of the dissolved organic
carbon in each sample. Standard deviation of δ13C analyses were generally within 0.8 ‰
or less than 3%.
Ultraviolet-visible light spectroscopy was performed on selected dissolved
organic carbon samples using a Varian Cary 1 UV-Vis absorbance analyzer. Specific
ultraviolet absorbance (SUVA) observed at 280 nm over a 1 cm path was normalized to
DOC concentrations to calculate the SUVA280 values for selected samples after Chin et
26
al. (1994). Blank corrections were run at the beginning of each day of analysis with DI.
Specific ultraviolet absorbance by DOC is reflective of the aliphatic or aromatic character
of the DOC, and can thus be used to qualitatively differentiate DOC among a group of
samples (e.g. Chin et al., 1994). A higher SUVA280 value generally means a larger
fraction of DOC in a sample is made up of aromatic dissolved organic matter (DOM)
(e.g. Traina et al., 1990; Chin et al., 1994). More aromatic DOM is generally considered
to originate from terrestrial plant and soil sources (Frazier et al., 2003), whereas less
aromatic DOM originates from microbial activity (McKnight et al., 2001; McKnight et
al., 1994).
Shale and streambed sediment samples were prepared for analysis at The Ohio
State University. Shale samples were broken into chips to expose the least weathered
material using a sedimentary rock hammer. The least weathered chips of shale were then
ground by hand twice, first in a ceramic mortar and pestle then in an agate mortar and
pestle. Streambed sediment samples were dried in a laminar flow hood then crushed in a
SPEX Certiprep alumina ceramic shatterbox. Bedrock shale samples were not crushed in
the shatterbox. Crushed and ground solid samples were then stored in a desiccator until
analysis of total carbon, total nitrogen, total organic carbon, δ13C of total organic carbon,
and major elements.
Bedrock shale and streambed sediment samples were analyzed for total carbon,
total nitrogen, and total organic carbon using a Costech Elemental Analyzer with
methods provided by the manufacturer. Multiple replicate analyses of total carbon and
total nitrogen were always within ±5%. Check standards run for every ten to twelve
27
samples analyzed were always within ±7%. The δ13C of total organic carbon was
determined using a Picarro 1111-is Cavity Ringdown Spectrometer to analyze the
evolved CO2 following combustion for 4 minutes at 894°C in a separate OI Analytical
Solids Module (manufacturer methods). Standard deviations of δ13C for replicate
analyses were generally within ±5% and always within ±15%. USGS-24 graphite and
PDB δ13C check standards were run for every ten samples analyzed and were always
within ±5%.
Streambed sediment samples were also prepared and analyzed for major and
minor element concentrations using a PANalytical PW2440 X-Ray Fluorescence
analyzer after Goldsmith et al. (2008a). Triplicate analyses of samples had analytical
precision within ±2%. Standards run for every six analyses showed accuracy for major
element concentrations always within ±5% and mostly within ±2%.
3.4.3. Geochemical Modeling
Chemical fluxes resulting from silicate weathering, carbonate weathering, and
rainwater input were calculated using a model of Gaillardet et al. (1999) and Goldsmith
et al. (2010). This model is formed from the following mixing equation (for X = Ca, Mg,
HCO3, Cl, K, and SO4)
(
(
)
)
(
)
(
)
(
(
)
)
(
)
( )
28
wherein αi(Na) is the Na proportion derived from i = rain, carbonate weathering, or
silicate weathering with
(
(
)
(
)
(
)
. Ratios of
) for i = carbonate weathering or silicate weathering were taken from Gaillardet et
al. (1999). For i = rain, (
) were the ratios in the bulk rainwater sample collected as part
of this study (
).
Using equation (1), seven equations and 28 parameters were obtained for which all αi(Na)
values were the unknowns. Given the number of equations is greater than the number of
unknowns, the system was over-constrained and a least squares inversion was used to
calculate a solution in MATLAB R2011a. The obtained αi values were then used to
calculate the relative input of each component (i) into stream water.
3.5. Incubation Experiment
An incubation experiment to observe any possible changes in dissolved organic
carbon concentrations related to microbial activity was performed during the field season
with unfiltered water collected from 2 different rivers (Rio Raxon and Quebrada
Chajonja). Replicate water samples were collected at each of the 2 rivers for time points
of 1, 2, 4, 8, and 16 days incubation in Nalgene™ low density polyethylene bottles
cleaned using procedure 2. The samples were kept in the dark at an average temperature
of 25 ± 2°C before being either refrigerated or filtered for dissolved organic carbon
analysis as described in section 3.3 above.
29
CHAPTER 4: RESULTS
4.1. Stream Discharges and Watershed Areas
Measured discharge ranged from 18 L s-1 (Tributary 2 to Chajonja) to 1800 L s-1
(Rio Raxon) (Table 4.1). Five streams were gauged more than once (Quebrada Chajonja,
Tributary 1 to Chajonja, Tributary 2 to Chajonja, Quebrada Carabajal, and Rio Sibija).
The largest variations in discharge were observed in streams draining the two smallest
watersheds (Tributary 1 to Chajonja and Tributary 2 to Chajonja). The lowest discharge
measured in Tributary 1 to Chajonja was less than half of the highest discharge (53 L s-1
to 130 L s-1). The lowest discharge in Tributary 2 to Chajonja was less than one-thirs of
the highest discharge (18 L s-1 to 55 L s-1). The Rio Sibija showed a nearly two-fold
difference in discharge from the lowest to highest discharge (470 L s-1 to 930 L s-1). The
highest discharges measured in each of these three locations were measured either during
or within twenty-four hours of a rain storm. Discharges measure more than twenty-four
hours after rainfall varied by no more than 15% (Quebrada Carabajal 1/26/12 and 3/7/12;
Rio Sibija 3/1/12 and 3/8/12). Too few measurements were made to determine baseflow.
Watershed areas upstream of spot sampling locations ranged from 0.35 km2
(Tributary 2 to Chajonja) to 700 km2 (Rio Matanzas) (Table 4.1). For gauged streams,
watershed area ranged from 0.35 km2 (Tributary 2 to Chajonja) to 24 km2 (Rio Raxon).
All streams that were not gauged had watershed areas greater than the Rio Raxon,
30
suggesting that they also have greater discharge than the Rio Raxon. For all watersheds
where discharge was measured, a significant linear relationship exists wherein
(
( )
|
)
(
|)
(Figure 4.1). This equation was used to estimate discharges for rivers that were not
gauged (Table 4.1). Some estimated discharges are less than measured discharges (Rio
Raxon, Quebrada Chajonja, Tributary 1 to Chajonja, Quebrada Cancor) and some
estimated discharges are greater than measured discharges (Tributary 2 to Chajonja,
Quebrada Carabajal, and Rio Sibija). For Rio Chiquito, the estimated discharge matches
closely to the measured discharge (830±240 L s-1 compared to 820 L s˗1, respectively).
4.2. Stream Temperature, pH, and Conductivity
River temperatures ranged from 25.4 °C (Quebrada Carabajal) to 15.9 °C (Rio
Raxon) with most rivers falling between 17.5 °C and 22.0 °C (Table 4.2). The Quebrada
Carabajal is the only river with multiple temperature readings all above 22.0 °C. Single
temperature measurements from Rio Tze, Rio Pueblo Viejo, and Rio Samilja DS are also
above 22.0°C. River temperature values appear to increase with a decrease in sampling
point elevation, however, this relationship is not significant (p=0.01, tstat < t|crit|). The
water temperature of all streams was less than the air temperature.
River pH measurements ranged from sub-acidic (6.19, Rio Raxon) to sub-basic
(8.17, Rio Matanzas) (Table 4.2). The pH of most rivers was sub-basic with the exception
of the Rio Raxon and single measurements from Rio Samilja MS, Rio Toila, Rio
Mululha, Rio Pancajoc, and Rio Tze. The Rio Raxon was the only river with multiple pH
31
measurements below 7 (6.19 to 6.96). The lowest pH measured in the Rio Raxon (6.19)
corresponds to a sample taken during a precipitation event that lasted roughly three days.
Electrical conductivity in rivers ranged from 8.17 S cm-2 (Rio Raxon) to 79.1 S
cm-2 (Rio Matanzas) (Table 4.2). Rio Raxon, Rio Mululha, and Rio Pancajoc are the only
three rivers with conductivity measurements below 20 μS cm-2 (8.27 to 12.81 μS cm˗2,
11.75 to 15.09 μS cm-2, and 14.52 to 16.24 μS cm-2, respectively).
4.3. Geochemistry of Stream Water
4.3.1. Major Element Concentrations
All major element concentrations in rivers are tabulated in Table 4.3. Na+ is the
most abundant cation in most rivers. Na+ concentrations in rivers ranged from to 47 μmol
L-1 (Rio Raxon) to 200 μmol L-1 (Tributary 2 to Chajonja). In the Rio Matanzas,
Quebrada Chajonja, and Quebrada Cancor , Ca2+ was the most abundant cation in
solution. Ca2+ concentrations in rivers ranged from 16 μmol L-1 (Rio Raxon) to 230 μmol
L-1 (Rio Matanzas). In most rivers, Na+ and Ca2+ were the two most abundant cations.
The Rio Matanzas had Ca2+ and Mg2+ as the two most abundant cations. Mg2+
concentrations ranged from 4.2 μumol L-1 (Rio Raxon) to 120 μmol L-1 (Rio Matanzas).
K+ concentrations ranged from 3.7 μmol L-1 (Rio Zarco) to 21 μmol L-1 (Trib. 2. to
Chajonja). K+ was the least abundant cation in all rivers but the Rio Raxon.
Bicarbonate (HCO3-) was the most abundant anion in all rivers. HCO3concentrations ranged from 68 μmol L-1 (Rio Raxon) to 710 μmol L-1 (Rio Matanzas). Clwas the second most abundant anion in all rivers but the Quebrada Chajonja, Tributary 2
to Chajonja, Quebrada Carabajal, and Quebrada Cancor. Chloride (Cl-) concentrations
32
ranged from 7.5 μmol L-1 (Rio Samilja US) to 25 μmol L-1 (Quebrada Carabajal). Sulfate
(SO42-) was the third most abundant anion in most rivers. SO42˗ concentrations in all
rivers ranged from 3.6 μmol L-1 (Rio Pancajoc) to 25 μmol L-1. Sulfate is the second most
abundant anion in the Quebrada Chajonja. (Quebrada Chajonja). Nitrate (NO3-) was the
fourth most abundant anion in most rivers. NO3˗ was the second most abundant anion in
the Tributary 2 to Chajonja, Quebrada Carabajal, and Quebrada Cancor. NO3concentrations ranged from 0.04 μmol L-1 (Rio Samilja MS) to 46 μmol L-1 (Tributary 2
to Chajonja). Fluoride (F-) was the second least abundant anion in most rivers. F˗
concentrations ranged from 2.1 μmol L-1 (Rio Zarco) to 7.5 μmol L-1 (Tributary 2 to
Chajonja). Phosphate (PO42-) was the least abundant anion in solution. PO42concentrations ranged from 0.059 μmol L-1 (Rio Raxon) to 1.2 μmol L-1 (Tributary 2 to
Chajonja).
Reactive silica (as H4SiO4) concentrations in rivers ranged from 190 μmol L-1
(Rio Raxon) to 870 μmol L-1 (Trib. 2 to Chajonja). The lowest H4SiO4 concentration was
sampled during a roughly three day continuous rainfall event and also corresponds with
the lowest pH, conductivity, and temperature measured. H4SiO4 for all rivers showed no
correlation with temperature (p=0.95), but did show a positive correlation to pH
(p=0.0006, tstat > t|crit|).
4.3.2. Spatial Variation in Major Element Chemistry
Three locations from the Rio Samilja correspond to a stream sequence from
upstream to downstream (Rio Samilja US, MS, and DS, where US means upstream, MS
means midstream, and DS means downstream). Solute concentrations changed by no
33
more than ten percent from upstream to downstream. Solute concentrations both
increased and decreased from upstream to downstream, showing no consistent pattern of
acquiring or diluting solutes.
The Rio Matanzas had higher Ca2+ and Mg2+ and lower Na+ and K+
concentrations than the three rivers that discharge into it upstream of the sampling point
(Rio Sibija, Rio Mululha, and Rio Pancajoc). Mg2+ and Ca2+ concentrations were roughly
an order of magnitude higher in the Rio Matanzas than in the Rio Mululha and Rio
Pancajoc (120 and 230 μmol L-1 compared to 8.8 to 16 and 23 to 27 μmol L-1,
respectively). Mg2+ and Ca2+ concentrations in the Rio Matanzas were roughly two-fold
greater than those found in the Rio Sibija (120 and 230 μmol L-1 compared to 72 and 94
μmol L-1, respectively). Reactive silica concentrations in the Rio Matanzas were similar
to those found in the Rio Mululha and Rio Pancajoc. Reactive silica concentrations in the
Rio Sibija were greater than those found in the Rio Matanzas (620 μmol L-1 compared to
430 μmol L-1, respectively). HCO3- concentrations in the Rio Matanzas were greater than
those found in the Rio Sibija, Rio Mululha, and Rio Pancajoc. Concentrations of HCO3were roughly two-fold greater in the Rio Matanzas than in the Rio Sibija (710 μmol L-1
compared to 440 μmol L-1, respectively). Concentrations of HCO3- were roughly fourfold greater in the Rio Matanzas than in the Rio Mululha and Rio Pancajoc (710 μmol L-1
compared to 150 to 160 μmol L-1, respectively).
The Quebrada Chajonja was sampled downstream of where Tributaries 1 and 2 to
the Chajonja discharge into it. Tributary 1 to the Chajonja had reactive silica and Na+
concentrations similar to the Quebrada Chajonja. Tributary 2 to the Chajonja had greater
34
reactive silica and Na+ concentrations than the Quebrada Chajonja (870 and 200 μmol L-1
compared to 670 and 150 μmol L-1, respectively). Ca2+ concentrations were three to five
times greater in the Quebrada Chajonja than in Tributaries 1 and 2 to the Chajonja (170
μmol L-1 compared to 36 and 59 μmol L-1, respectively). Mg2+ in the Quebrada Chajonja
was greater than in the Tributary 2 to Chajonja and more than twice that in the Tributary
1 to Chajonja (48 μmol L-1 compared to 39 and 20 μmol L-1, respectively). HCO3- was
greater in the Quebrada Chajonja than in Tributaries 1 and 2 to the Chajonja (500 μmol L1
compared to 200 and 300 μmol L-1, respectively).
The Rio Raxon, Quebrada Chajonja, Rio Chiquito, and Quebrada Cancor all flow into the
Rio Pueblo Viejo upstream of where the Rio Pueblo Viejo was sampled. Reactive silica
in the Rio Pueblo Viejo was comparable to that observed in the Rio Raxon and the Rio
Chiquito but lower than concentrations observed in the Quebrada Cancor, and Quebrada
Chajonja (460 μmol L-1 compared to 600 and 670 μmol L-1, respectively). HCO3- in the
Rio Pueblo Viejo was roughly twice that observed in the Rio Raxon (210 μmol L-1
compared to 120 μmol L-1, respectively), similar to that observed in the Rio Chiquito
(230 μmol L-1), and less than that observed in the Quebrada Cancor and Quebrada
Chajonja (360 μmol L-1 and 500 μmol L-1, respectively). Ca2+ in the Quebrada Chajonja
and Quebrada Cancor was roughly twice as much as that observed in the Rio Pueblo
Viejo (170 μmol L-1 and 120 μmol L-1 compared to 59 μmol L-1, respectively). Ca2+ in the
Rio Pueblo Viejo was similar to that observed in the Rio Chiquito and more than twice
that observed in the Rio Raxon (59 μmol L-1 compared to 26 μmol L-1, respectively). Na+
in the Rio Pueblo Viejo was similar to that observed in the Rio Chiquito, Rio Raxon, and
35
Quebrada Cancor, but about half as much as that observed in the Quebrada Chajonja (84
μmol L-1 compared to 150 μmol L-1, respectively).
4.3.3. Temporal Variation in Major Element Chemistry
Three locations were sampled twice (Rio Chiquito, Quebrada Cancor, and Rio
Pueblo Viejo), two locations were sampled three times (Rio Raxon and Quebrada
Chajonja), and 11 locations were sampled four times (Table 4.3). In general, variations in
solute geochemistry were related to changes in the antecendent moisture conditions. The
lowest solute concentrations at a given sampling location correspond to samples taken
either during or within 12 hours following a prolonged rainfall event (2 to 3 days of
continuous rainfall). Typically, solute concentrations in samples taken during or within
12 hours of a prolonged rainfall event were roughly half as much as the highest
concentrations at the same sampling point. These samples are denoted with a ǂ in Table
4.3. Samples with the highest solute concentrations at a given location generally followed
a period of roughly five days to a week without rainfall. These samples were taken to be
the best approximation of base flow concentrations and are the values used to compare
solute ratios in section 4.3.4.
NO3- showed the most variation of any of the solutes, varying by as much as an
order of magnitude at six sampling locations (Tributary 1 to Chajonja, Rio Samilja US,
Rio Samilja MS, and Rio Samilja DS, Rio Sibija, and Rio Mululha). NO3- variations did
not show any pattern with variations in rainfall. Changes in NO3- may be influences by
differences in anthropogenic inputs upstream, however similar land and water uses were
observed throughout the sampled watersheds.
36
SO42- variation showed no relationship with watershed rock type. The Quebrada
Carabajal, the only watershed composed solely of the Pizarro shale, had a range of SO42concentrations close to median of all samples (12 to 14 μmol L-1 compared to 11 μmol
L˗1). The range of SO42- seen in the Quebrada Carabajal is similar, but lower than the
range of SO42- seen in the Tributary 1 to Chajonja, (10 to 19 μmol L-1), which drains only
San Augustín gneiss.
F- in some rivers appeared to be connected to changes in Ca2+ concentrations (Rio
Samilja US, Rio Samilja MS, Rio Samilja DS, Rio Toila, Rio Sibija, and Tributary 2 to
Chajonja) (Figure 4.2). Changes in Ca2+ concentrations in the Rio Matanzas and
Quebrada Carabajal do not appear to be connected to F-.
4.3.4. Major Element Ratios
Two distinct groups of samples appear in a molar plot of Na+K to Ca+Mg (Figure
4.3). Samples in Group 1 had approximately twice as much Na+K than Ca+Mg. The Rio
Raxon, Tributary 1 to Chajonja, Tributary 2 to Chajonja, Rio Mululha, and Rio Pancajoc
compose group 1. All other rivers but the Rio Matanzas fall in group 2, which had
roughly half as much Na+K as Ca+Mg. The Rio Matanzas falls outside of both groups
and has about one-fourth as much Na+K than Ca+Mg . Group 1 samples fall closest to
the Na+K:Ca+Mg ratio in the bulk rainwater sample collected over the course of the field
season.
Total cation (TZ+) to Si molar ratios for most samples ranged from 0.22 (Rio
Raxon) to 0.61 (Quebrada Carabajal). The TZ+ to Si ratio in the Rio Matanzas was
approximately 1:1 (Figure 4.4). TZ+:Si ratios in group 1 samples ranged from 0.22 (Rio
37
Raxon) to 0.33 (Tributary 2 to Chajonja). TZ+:Si ratios in group 2 ranged from 0.30 (Rio
Tze) to 0.61 (Quebrada Carabajal). More Si than cations in solution suggests that the
Pizarro shale, San Augustín gneiss, and granite lithologies that underlie the rivers has
undergone a severe degree of weathering and little other than Si remains to be leached
into solution (Goldsmith et al., 2008a). Rio Matanzas chemistry is dominated by Ca2+ and
Mg2+. Four samples from the Rio Matanzas had Ca2+ and Mg2+ concentrations that
ranged from 140 μmol L-1 to 230 μmol L-1 and 120 μmol L-1 to 120 μmol L-1,
respectively. Samples from the Rio Matanzas also plot closest to the 1:1 stoichiometric
carbonate dissolution line (Ca+Mg μeq L-1 to HCO3 μeq L-1) (Figure 4.5). Group 2
Ca+Mg:HCO3 (μeq L-1) ratios ranged from 0.69 (Rio Samilja US) to 0.92 (Rio Zarco).
Group 1 ratios ranged from 0.37 (Rio Raxon) to 0.59 (Tributary 2 to Chajonja).
Molar Ca:Na ratios in rivers ranged from 0.24 (Rio Pancajoc) to 2.5 (Rio
Matanzas). Ca:Na ratios in group 1 samples ranged from 0.24 (Rio Pancajoc) to 0.30 (Rio
Mululha). Ca:Na ratios in group 2 samples ranged from 0.49 (Rio Tze) to 1.3 (Quebrada
Cancor). Molar Mg:Na ratios in rivers ranged from 0.06 (Rio Raxon) to 2.1 (Rio
Matanzas). Mg:Na ratios in group 1 samples ranged from 0.06 (Rio Raxon) to 0.19
(Tributary 2 to Chajonja). Mg:Na ratios in group 2 samples ranged from 0.16 (Rio
Samilja US) to 0.92 (Quebrada Carabajal). Molar HCO3:Na ratios in rivers ranged from
1.4 (Tributary 1 to Chajonja) to 9.3 (Rio Matanzas). HCO3:Na ratios in group 1 samples
ranged from 1.4 (Tributary 1 to Chajonja) to 1.6 (Rio Mululha). HCO3:Na ratios in group
2 samples ranged from 2.2 (Rio Toila and Rio Tze) to 3.7 (Quebrada Carabajal and
Quebrada Cancor). These molar ratios fall outside the field of ratios expected from
38
carbonate weathering (Gaillardet et al., 1999) (Figure 4.6). Group 1 samples fall within
the field of ratios expected for silicate weathering. Group 2 and Rio Matanzas samples
fall within the field of ratios expected from basalt weathering, though the bedrock
underlying the watersheds does not include any basalt.
4.3.5. Chemical Weathering Fluxes and Yields
Chemical fluxes are strongly correlated to watershed area (p<0.00005, tstat >
t|crit|) (Figure 4.7). The smallest fluxes are from the smallest watershed (Tributary 2 to
Chajonja) and the largest fluxes from the largest watershed (Rio Matanzas). Chemical
yields show no significant relationship with watershed area (p=0.38, tstat < t|crit|),
however the largest yields are seen in the smallest watershed (Tributary 2 to Chajonja).
Fractions of solutes in each stream derived from each input (rain, carbonate
weathering, and silicate weathering) were obtained from the model discussed in section
3.4 (Figure 4.8). Fractions of solutes in rivers derived from rainwater input ranged from
0.7% (Rio Matanzas) to 22% (Quebrada Cancor and Rio Tze). The fraction of solutes
derived from rainwater for the Rio Matanzas is much lower than the next lowest fraction
of 9% for Rio Sibija and Quebrada Carabajal. The low fraction of rain-sourced solutes in
the Rio Matanzas might result from it being the farthest inland from the Caribbean Sea of
any of the watersheds sampled. For all of the rivers sampled but the Rio Matanzas,
weathering reactions account for 91% to 78% of solutes measured in stream water.
Fractions of solutes in rivers sourced from carbonate weathering ranged from 0%
(Rio Raxon, Tributary 1 to Chajonja, Tributary 2 to Chajonja, Rio Mululha, Rio
Pancajoc) to 3.7% (Rio Matanzas). The five rivers that show no input of solutes from
39
carbonate weathering make up Group 1 of samples discussed in section 4.3.4. Based on
the geologic map of Bonis et al. (1970), some portion of two other watersheds, Rio Sibija
and Rio Pancajoc, are underlain by the Permian carbonate lithology (0.06% and 0.08%,
respectively). Rio Sibija derives 0.9% of its solutes from carbonate weathering but Rio
Pancajoc shows no solute input from carbonate weathering. Rio Samilja shows a small
increase in carbonate weathering inputs from upstream to downstream from 0.6% to
0.8%. Nine of 16 rivers sampled show more than 0.5% carbonate weathering input but
only the Rio Matanzas and Rio Sibija are underlain by some portion of the Permian
carbonate sequence according to Bonis et al. (1970).
Fractions of solutes in rivers from silicate weathering ranged from 76%
(Quebrada Cancor) to 96% (Rio Matanzas). Such high fractions of silicate-derived
solutes were not unexpected because the Sierra de las Minas are made up of shale,
granite, and gneiss. Five rivers derive all of their weathering solutes from silicates (Rio
Raxon, Tributary 1 to Chajonja, Tributary 2 to Chajonja, Rio Mululha, and Rio
Pancajoc). The range of silicate weathering input to these five rivers is narrower than the
range for all rivers (82%, Rio Mululha to 90%, Tributary 2 to Chajonja).
The ratios of weathering inputs discussed above were used to determine CO2
yields (flux normalized to watershed area) from silicate weathering. This CO2 yield
corresponds to the effective atmospheric CO2 drawdown from silicate mineral weathering
for each stream sampled. CO2 yields from chemical weathering range from 120±25 x 103
mol km-2 yr-1 (Rio Mululha) to 1100 x 103 mol km-2 yr-1 (Tributary 2 to Chajonja and
Quebrada Chajonja) (Table 4.4).
40
4.4. Organic Chemistry of Stream Water
4.4.1. Dissolved Organic Carbon in Streams
Most dissolved organic carbon (DOC) concentrations ranged from 19.2 μmol L-1
(Rio Zarco) to 397 μmol L-1 (Rio Raxon) (Table 4.5). Two samples taken from the
Tributary 2 to the Chajonja and Rio Matanzas had much higher DOC concentrations than
the others (967 μmol L-1 and 1300 μmol L-1, respectively). These concentrations were
about three to four-fold greater than the next highest concentration (397 μmol L-1 in the
Rio Raxon) and are not concurrent with high dissolved organic nitrogen (DON) and
dissolved organic phosphorous (DOP) concentrations.
The largest range of DOC concentrations were measured in Tributary 2 to
Chajonja and in Rio Matanzas. DOC concentrations in the Tributary 2 to Chajonja ranged
from 64.7 μmol L-1 to 967 μmol L-1. DOC concentrations in the Rio Matanzas ranged
from 192 μmol L-1 to 1300 μmol L-1. The next largest DOC variations in samples taken
from the same location were seen in samples taken from the Rio Raxon. The highest
DOC concentration in a sample from the Rio Raxon (397 μmol L-1) was roughly three
times that of the next highest concentration in it (132 μmol L-1) and the sample with that
low DOC was colelcted during the roughly three day continuous rainfall event discussed
above. In general, DOC in samples taken from the same location varied by one and a half
to two-fold over the course of the field season.
Stable carbon-13 isotope compositions (13C) of DOC ranged from ˗25.8‰ to
˗31.7‰ (Table 4.5). Four samples have 13C compositions more enriched than ˗28.0‰.
Two of these four δ13C enriched samples are those from the Tributary 2 to Chajonja and
41
Rio Matanzas with the highest DOC concentrations. Though repeat sampling of locations
revealed variability in DOC concentrations over the course of the field season, these
differences in DOC do not correspond with changes in 13C (Figure 4.9).However, δ13C
of DOC varied by as much as 2‰ without any change in DOC concentrations for
samples with between 100 and 200 μmol L˗1.
Ultraviolet-Visible Spectroscopic (UV-Vis) analysis of selected DOC samples
compared to DOC concentrations showed a similar pattern to that observed between δ13C
and DOC. Changes in DOC among samples from a given location did not occur with
changes in specific ultraviolet absorbance at wavelength 280 nm (SUVA280) (Figure
4.10).
4.4.2. Dissolved Organic Nitrogen and Phosphorous in Streams
Concentrations of DON typically ranged from 0.91 μmol L-1 (Quebrada
Carabajal) to 12 μmol L-1 (Rio Samilja US, Rio Samilja MS, Rio Samilja DS, Rio Sibija)
(Table 4.5). Four samples had inorganic nitrogen account for all of the nitrogen present
and so were thought to have no DON. A linear regression of DON versus DOC reveals a
significant positive correlation between DON and DOC (p<0.0005). This positive
correlation between DON and DOC suggests that much of the dissolved organic matter
was nitrogenous. DOP concentrations ranged from 0.02 mol/L to 3.5 mol/L and
showed no significant relationship with DOC or DON concentrations.
4.5. Day-to-Night, Night-to-Day Sampling
To determine changes in river chemistry that might occur as a result of natural
diel cycles, two sets of continual sampling were conducted at the Rio Raxon and the Rio
42
Chajonja. The first sampling was an hourly sampling from 1700 to 2100 and 0500 to
0900. The second sampling was a bi-hourly sampling from 1700 to 2300 and 0500 to
1100. The sun was completely set by 2000 during each sampling and would rise between
0600 and 0700 each morning. Dissolved major element concentrations, DOC, δ13C,
DON, and DOP of these samples are tabulated in Tables 4.6 and 4.7.
Few changes occurred in the major ion concentrations of each river from day to
night and night to day (Table 4.6). The largest changes were observed in NO3concentrations. These changes were not consistent from river to river nor from sampling
to sampling. During the first continual sampling, NO3- concentrations increased four-fold
between 2000 and 2100 (2.3 μmol L-1 to 9.5 μmol L-1). These elevated concentrations
persisted through 0700 and then decreased to half as much between 0700 and 0800 (12
μmol L-1 to 5.3 μmol L-1). The first continual sampling of the Rio Raxon was the only
sampling when this apparent systematic change in NO3- occurred.
Changes in DON over the samplings were generally inverse to changes in NO3and might be a result of nitrification. This was most evident during the first sampling of
the Rio Raxon (Figure 4.11). The four-fold increase in NO3- that occurred between 2000
and 2100 is concurrent with a three-fold decrease in DON. No increase in DON was
observed between 0700 and 0800 corresponding to the decrease in NO3-. As with changes
in NO3-, changes in DON were not consistent from river to river nor from sampling to
sampling (Table 4.7).
Changes were also observed in DOC for each of the rivers over the two sampling
periods (Table 4.7). For the Rio Raxon, elevated concentrations of DOC were observed at
43
1700, 1900, and 0700 hours during both sets of sampling. These elevated DOC
concentrations occurred with enriched 13C composition. In the Quebrada Chajonja,
elevated DOC concentrations were observed during the evening of the first sampling
(from 0.59 μmol L-1 to 3.02 μmol L-1), but this did not occur during the second sampling
(Table 4.7). As with the Rio Raxon, the elevated DOC concentrations also have three of
the more enriched 13C compositions observed over the entire field season. DOP
concentrations showed little change over the course of the continual samplings.
4.6. Dissolved Organic Carbon Incubation Experiment
An incubation experiment was conducted with waters collected from Rio Raxon
and Quebrada Chajonja. This incubation experiment was conducted to explore carbon
dynamics that might be related to diel cycles. As little change was observed during the
Day-to-Night, Night-to-Day samplings, then it was hypothesized by the authorthat a
longer time interval in the dark would foster microbial activity that would cause changes
in DOC. Increases in DOC were observed in waters from both the Rio Raxon and
Quebrada Chajonja over the course of the incubation (Figure 4.12). The Quebrada
Chajonja showed the fastest rate of DOC increase over a 48 hour period with a rate of
0.410.1 mol/L per hour (p<0.05, t-stat > t |crit|). After 48 hours, little change in DOC
was observed in water from the Quebrada Chanjonja. Over an eight-day period, the Rio
Raxon showed the greatest increase in DOC at a rate of 0.140.01 mol/L per hour
(p<0.00005, t-stat > t |crit|).
44
4.7. Streambed Sediment and Bedrock Shale Chemistry
4.7.1. Major and Minor Element Chemistry
Major and minor element concentrations of streambed sediments and bedrock
shale are presented in weight percent (wt%) of the oxide component in Table 4.8.
Aluminum in streambed sediments ranged from 10.7 (Quebrada Cancor) to 16.3
(Quebrada Carabajal) wt% Al2O3. Silicon ranged from 62.8 (Rio Pancajoc) to 80.7
(Quebrada Cancor) wt% SiO2. Iron concentrations ranged from 1.42 (Tributary 1 to
Chajonja) to 8.43 (Quebrada Carabajal) wt% Fe2O3. Due to the oxidative nature of the
sample preparation it is impossible to differentiate between ferric and ferrous iron in a
sample using the stated X-ray fluorescence methods (Section 3.4.2) because the reduced
Fe is oxidized. Calcium ranged from 0.19 (Quebrada Chajonja) to 3.45 (Rio Matanzas)
wt% CaO. Rio Matanzas sediments are the only sediments with CaO above 1.0 wt%.
Sediments from the Rio Matanzas also have the highest magnesium with 4.50 wt% MgO,
roughly four times greater than the next highest concentration (Rio Zarco, 1.14 wt%
MgO). Sediments from Rio Samilja upstream showed the lowest magnesium at 0.45 wt%
MgO. Potassium ranged from 2.53 (Quebrada Carabajal) to 5.86 (Rio Pancajoc) wt%
K2O. Sodium ranged from 0.53 (Quebrada Chajonja) to 2.67 (Tributary 1 to Chajonja)
wt% Na2O. All sodiums were above 1.0 wt% Na2O with the exception of Quebrada
Chajonja and Quebrada Carabajal. Quebrada Carabajal also showed the highest MnO and
P2O5 wt% at 0.18 and 0.14, respectively. Quebrada Chajonja had the highest TiO2 wt% at
1.79, roughly two-fold greater than the next highest concentration of 0.90 wt% TiO2
(Quebrada Carabajal).
45
In general, bedrock shale samples had greater Al2O3, Fe2O3, TiO2, and MgO, but
lower CaO, K2O, and Na2O concentrations than streambed sediments (Table 4.8). SiO2
and P2O5 contents were similar in streambed sediment and bedrock shale samples.
Differences between bedrock shale and streambed sediments become more apparent
when streambed sediment concentrations are normalized to the Monte Blanco shale
(Figure 4.13). Major element concentrations in the Monte Blanco shale were chosen to
normalize the streambed sediments because they are approximately median
concentrations of major and minor elements for all bedrock shale samples. Sediments
from the Quebrada Carabajal and Quebrada Chajonja are the most chemically similar to
the shale. The Quebrada Carabajal watershed is underlain entirely by the Pizarro shale,
and roughly 75% of the Quebrada Chajonja watershed is underlain by shale. Calcium,
potassium, and sodium were all enriched in streambed sediments compared to bedrock
shale with the exception of the Quebrada Carabajal and Quebrada Chajonja. Shalenormalized concentrations of calcium were between 2.2 (Quebrada Carabajal) and 110
(Rio Matanzas). Shale-normalized potassium concentrations ranged from 0.6 (Quebrada
Carabajal and Quebrada Chajonja) to 3.3 (Tributary 1 to Chajonja). Shale-normalized
sodium concentrations ranged from 0.9 (Quebrada Carabjal) to 2.4 (Rio Pancajoc).
Major elements concentrations in streambed sediments were also normalized to
concentrations in the San Agustín gneiss (from Newcomb, 1975) and were more
chemically similar to San Agustín gneiss than bedrock shale (Figure 4.14). Gneissnormalized concentrations of calcium ranged from 0.03 (Quebrada Carabajal) to 1.6 (Rio
Matanzas). Calcium was only enriched in streambed sediments from the Rio Matanzas.
46
Gneiss-normalized potassium concentrations ranged from 0.6 (Quebrada Carabajal and
Quebrada Chajonja) to 1.5 (Rio Pancajoc). Gneiss-normalized Sodium concentrations
ranged from 0.2 (Quebrada Carabajal and Quebrada Chajonja) to 1.1 (Tributary 1 to
Chajonja).
4.7.2. Streambed Sediment Mineralogy
X-Ray diffraction analysis of streambed sediments from most sample sites
showed the mineralogy of the streambed sediments is consistent with those minerals
associated with granite, gneiss, and associated weathering products (Table 4.9). Quartz
was present in all streambed sediment samples. Microcline or albite was present in almost
all streambed sediments. Quebrada Carabajal showed no presence of feldspars, but did
show presence of muscovite. Muscovite was also present in sediments from Rio Samilja
DS, Rio Toila, Rio Sibija, Rio Pancajoc, Rio Chiquito, and Rio Tze. Rios Chiquito and
Tze are not underlain by granite, so the muscovite is sourced from either the Pizarro shale
or San Agustín gneiss (Bonis et al. 1970). In addition, illite and chlinochlore, secondary
mineral products of granite and gneiss weathering, were present in most streambed
sediments. Sediments from the Rio Matanzs, Rio Pancajoc, and Tributary 1 to Chajonja
showed neither illite nor clinochlore. Dolomite was present only in sediments from the
Rio Matanzas.
4.7.3. Organic Carbon and Nitrogen Chemistry in Streambed Sediments and
Bedrock Shale
Organic carbon concentrations in streambed sediments ranged from 0.04 (Rio
Samilja Upstream) to 0.58 (Tributary 2 to Chajonja, Rio Pancajoc) wt% carbon (Table
47
4.10). These organic carbon concentrations were less than those generally seen in the
bedrock shale samples, which ranged from 0.20 (Pancajoc) to 0.81 (Monte Blanco II)
wt% organic carbon. Samples from the Tributary 2 to Chajonja, Rio Pancajoc, and
Quebrada Cancor were the only streambed sediments that had organic carbon
concentrations within the range of shale carbon concentrations (0.35–0.58 wt%). The
organic carbon concentrations of these sediments were three to five-fold greater than the
next highest concentrations found in streambed sediments from this study.
The δ13C composition of organic carbon in most streambed sediments were within
the range of the 13C of shale samples analyzed in this study (-22.5‰ to -27.2‰). The
samples that fall outside of the watershed bedrock shale 13C range are Tributary 2 to
Chajonja, Rio Pancajoc, and Quebrada Cancor. These three samples have a 13C more
depleted than the other streambed sediment samples (-29.0‰ to -29.6‰).
Total nitrogen concentrations in streambed sediments ranged from 0.006 (Rio
Samilja Upstream) to 0.088 (Quebrada Carabajal) wt% nitrogen. Shale samples had a
greater nitrogen concentration than streambed sediment samples, ranging from 0.052
(Cancor) to 0.10 (Monte Blanco) wt% nitrogen. However, organic carbon to nitrogen
ratios (C/N) were mostly similar in streambed sediment and in bedrock shale samples
(1.6–9.4) with three exceptions (Figure 4.10). These exceptions are the same three
samples that had the highest organic carbon concentrations and most depleted 13C values
(Tributary 2 to Chajonja, C/N=13; Rio Pancajoc, C/N=13; Quebrada Cancor, C/N=19).
48
Table 4.1 Watershed Areas and Stream
Discharge
Sample Location
Watershed Area
Date
km
2
Meas.
Discharge
Est. Discharge
(L/s)
(L/s)
Rio Raxon
1/21/2012
Quebrada Chajonja
1/24/2012
3/6/2012
3/12/2012
Trib. 1 to Chajonja
2/3/2012
2/16/2012
3/2/2012
3/9/2012
Trib. 2 to Chajonja
2/3/2012
2/16/2012
3/2/2012
3/9/2012
Q. Carabajal
1/26/2012
3/7/2012
24
1800
1100±270
7.1
620
500
490
350±140
1.2
130
110
53
110
95±100
0.35
55
32
18
44
57±93
15
330
280
700±210
49
Table 4.1 cont'd Watershed Areas and Stream Discharge
Sample Location
Date
Watershed Area
km
2
Meas.
Discharge
Est. Discharge
(L/s)
(L/s)
R. Samilja US
35
1600±360
47
2100±450
67
3000±610
42
1900±410
700
31000±5500
R. Samilja MS
R. Samilja DS
R. Toila
R. Matanzas
R. Sibija
2/14/2012
3/1/2012
3/8/2012
R. Mululha
18
930
470
520
830±230
52
2400±490
38
1700±380
R. Pancajoc
R. Chiquito
2/29/2012
Q. Cancor
2/29/2012
R. Pueblo Viejo
18
820
830±230
9
610
440±160
150
6600±1200
83
3700±730
46
2100±440
R. Zarco
R. Tze
50
Table 4.2 Field Chemistry and Discharge
Sample Location
Temp
Date
pH
DO
Cond
-1
°C
mg L
uS cm
-2
Discharge
Ls
-1
Rio Raxon
1/21/2012
3/6/2012
3/12/2012
Quebrada Chajonja
1/24/2012
3/6/2012
3/12/2012
Trib. 1 to Chajonja
2/3/2012
2/16/2012
3/2/2012
3/9/2012
Trib. 2 to Chajonja
2/3/2012
2/16/2012
3/2/2012
3/9/2012
Q. Carabajal
1/26/2012
2/22/2012
3/7/2012
3/13/2012
R. Samilja US
1/27/2012
2/22/2012
3/7/2012
3/13/2012
R. Samilja MS
2/7/2012
2/22/2012
3/7/2012
3/13/2012
R. Samilja DS
2/5/2012
2/22/2012
3/7/2012
3/13/2012
R. Toila
2/5/2012
2/22/2012
3/7/2012
3/13/2012
18.4
15.9
17.7
6.72
6.19
6.96
7.97
8.99
8.54
12.81
8.27
11.35
1800
20.5
18.7
19.6
7.57
7.83
7.69
7.18
9.03
7.96
58.1
56.7
58.2
620
500
490
18.7
7.53
7.35
7.47
7.4
5.48
18.44
21.27
23.01
23.07
130
110
53
110
5.41
18.8
19.0
7.88
7.45
7.41
7.56
7.8
7.9
32.1
33.6
35.2
36.8
55
32
18
44
22.1
24.7
25.4
25.4
7.47
7.52
7.55
7.71
7.96
7.32
7.54
7.61
40.3
39.7
41.8
42.6
330
18.8
18.9
16.9
18.1
7.13
7.52
7.38
7.19
8.72
8.18
9.72
9.53
66.9
24.77
12.29
19.56
21.3
20.5
21.3
7.24
7.43
6.94
7.2
8.98
8.82
8.19
20.15
26.9
14.22
21.49
23.5
21.1
22.0
7.16
7.49
7.14
7.45
7.49
9.04
8.17
21.31
29.68
15.21
24.08
20.9
18.7
20.2
7.26
7.36
6.6
7.18
8.08
8.86
8.45
14.82
22.48
11.25
17.72
17.5
17.7
19.4
51
8.92
8.03
280
Table 4.2 cont’d Field Chemistry and Discharge
Sample Location
Temp
Date
R. Matanzas
1/30/2012
2/14/2012
3/1/2012
3/8/2012
R. Sibija
1/30/2012
2/14/2012
3/1/2012
3/8/2012
R. Mululha
1/30/2012
2/14/2012
3/1/2012
3/8/2012
R. Pancajoc
1/30/2012
2/14/2012
3/1/2012
3/8/2012
R. Chiquito
2/10/2012
2/29/2012
Q. Cancor
2/10/2012
2/29/2012
R. Pueblo Viejo
2/10/2012
2/29/2012
R. Zarco
2/21/2012
R. Tze
2/21/2012
pH
Cond
-1
°C
18.5
DO
mg L
7.94
7.51
8.17
8.12
6.66
7.5
7.2
7.33
7.46
7.58
6.7
7.5
7.23
6.93
8.43
8.08
20.2
20.1
6.84
7.74
7.37
7.1
21.1
20.1
19.5
19.5
20.3
20.3
17.9
19.5
18.8
18.5
8.62
8.62
8.63
8.84
8.68
8.65
uS cm
-2
Discharge
Ls
-1
54.2
79.1
78.4
63.2
32.9
34.4
42.7
39.7
930
470
520
11.75
12.53
15.09
12.18
8.42
8.51
14.81
14.53
16.24
14.52
7.68
7.38
8.36
27.02
26.74
820
20.8
7.16
7.79
7.99
71.6
37.8
610
24.3
7.21
7.38
7.81
23.88
22.2
21.7
7.34
7.68
27.85
22.3
6.92
7.79
16.6
52
Table 4.3 Aqueous Major Ion Chemistry
Sample Location
Na
K
Mg
Ca
Si
NH3
F
Cl
NO3
SO4
PO4
HCO3
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
16
1.0
1.9
3
<0.6
14
<0.6
17
6.4
5.7
<0.01
6.5
80
8.3
5.2
22
430
16
5.3
9.6
12
5.8
0.12
120
47
7.5
4.2
16
190
0.40
3.1
9.1
7.2
4.0
0.06
68
69
8.5
5.8
26
340
0.32
5.4
12
8.5
6.3
0.08
100
150
13
48
170
670
0.24
4.6
17
37
25
0.86
490
140
14
44
170
640
0.35
4.5
17
22
22
0.33
500
140
14
45
170
650
0.65
5.3
16
21
21
0.24
500
100
10
15
31
500
0.21
5.6
15
0.83
9.7
0.13
160
2/16/2012
130
11
17
32
640
0.09
5.6
15
0.77
13
0.13
190
3/2/2012
140
12
19
36
700
0.25
6.9
15
3.5
17
0.21
200
3/9/2012
140
12
20
35
680
0.27
7.2
15
14
19
0.28
190
170
19
34
50
750
0.28
6.9
19
46
11
0.84
260
2/16/2012
190
21
34
51
830
0.18
6.9
17
39
12
1.2
290
3/2/2012
200
16
37
56
870
0.24
7.4
17
42
15
1.1
300
3/9/2012
200
16
39
59
870
0.38
7.5
17
46
17
1.2
300
Date
Precipitation
Rio Raxon
1/21/2012
3/6/2012
ǂ
3/12/2012
53
Quebrada Chajonja
1/24/2012
3/6/2012
ǂ
3/12/2012
Trib. 1 to Chajonja
2/3/2012
ǂ
Trib. 2 to Chajonja
2/3/2012
ǂ
53
Table 4.3 cont'd Aqueous Major Ion Chemistry
Sample Location
Na
K
Mg
Ca
Si
NH3
F
Cl
NO3
SO4
PO4
HCO3
Date
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
1/26/2012
110
6.0
99
77
450
1.0
3.4
23
45
14
0.09
370
2/22/2012
100
6.1
93
69
460
0.49
3.0
22
24
13
0.09
360
110
6.9
99
77
450
0.80
3.0
24
20
14
0.10
390
110
6.7
100
78
440
1.1
2.7
25
18
14
0.08
400
90
11
14
62
510
0.31
5.1
11
8.0
13
0.15
200
88
10
16
65
510
0.28
5.2
9.3
0.46
12
0.16
220
49
7.3
8
36
270
0.31
3.5
7.5
0.48
5.5
0.06
120
73
9.1
12
52
120
0.18
4.3
8.5
1.3
9.8
0.13
180
73
9.5
20
50
410
0.27
3.5
11
0.10
9.0
0.10
190
91
12
29
65
510
0.21
4.9
12
0.04
14
0.13
250
54
8.2
14
40
300
0.36
3.8
9.2
1.1
6.3
0.13
140
77
10
22
54
420
0.38
4.3
11
3.8
8.8
0.13
200
2/5/2012
71
9.6
30
49
390
0.32
4.1
13
14
9.3
0.11
190
2/22/2012
92
12
43
68
490
0.24
4.8
14
1.1
16
0.11
270
55
8.3
21
43
290
0.32
3.9
9.2
5.1
7.8
0.08
160
80
10
32
60
430
0.33
4.4
12
0.74
12
0.09
230
Q. Carabajal
3/7/2012
ǂ
54
3/13/2012
R. Samilja US
1/27/2012
ǂ
2/22/2012
3/7/2012
ǂ
3/13/2012
R. Samilja MS
2/7/2012
2/22/2012
3/7/2012
ǂ
3/13/2012
R. Samilja DS
3/7/2012
3/13/2012
ǂ
54
Table 4.3 cont'd Aqueous Major Ion Chemistry
Sample Location
Na
K
Mg
Ca
Si
NH3
F
Cl
NO3
SO4
PO4
HCO3
Date
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
2/5/2012
65
9.2
17
34
360
0.21
4.2
9.5
5.0
5.4
0.15
150
2/22/2012
89
10
27
50
480
0.11
5.5
11
1.1
11
0.16
210
48
7.3
11
28
260
0.43
3.8
8.2
5.7
5.3
0.08
110
75
9.1
18
40
420
0.27
5.0
10
6.4
9.1
0.13
160
56
18
120
140
320
0.37
3.3
19
13
14
0.10
520
2/14/2012
65
13
120
230
410
1.9
3.5
18
20
15
0.11
710
3/1/2012
83
14
120
230
430
0.25
3.3
21
12
19
0.13
710
3/8/2012
76
14
120
170
400
0.25
3.1
20
14
15
0.11
610
97
19
49
68
450
0.29
3.3
18
7.7
9.6
0.19
300
2/14/2012
110
16
55
74
540
0.11
3.0
15
0.19
11
0.14
340
3/1/2012
130
17
72
94
620
0.16
4.2
15
0.53
11
0.20
440
3/8/2012
130
16
68
90
590
0.20
4.5
15
7.8
10
0.39
410
58
11
8.8
22
270
0.40
3.6
10
7.4
4.4
0.12
100
2/14/2012
69
9.5
8.8
20
390
0.28
3.8
9.6
2.4
3.9
0.12
110
3/1/2012
89
11
13
27
460
0.23
4.9
11
0.57
4.9
0.13
150
3/8/2012
70
9.6
9.1
21
390
0.26
3.7
10
0.56
5.3
0.10
110
R. Toila
3/7/2012
ǂ
3/13/2012
R. Matanzas
55
1/30/2012
ǂ
R. Sibija
1/30/2012
ǂ
R. Mululha
1/30/2012
ǂ
55
Table 4.3 cont'd Aqueous Major Ion Chemistry
Sample Location
Na
K
Mg
Ca
Si
NH3
F
Cl
NO3
SO4
PO4
HCO3
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
72
16
13
23
350
0.45
3.3
13
12
4.6
0.12
120
2/14/2012
82
14
13
22
450
0.35
4.0
13
8.4
3.7
0.13
130
3/1/2012
96
14
16
23
500
0.42
3.6
13
2.9
3.6
0.16
160
3/8/2012
86
13
14
21
470
0.36
3.7
12
8.3
5.4
0.18
130
2/10/2012
88
13
37
61
480
0.19
2.8
21
21
9.9
0.10
230
2/29/2012
91
14
37
65
470
0.32
2.9
24
29
12
0.15
230
2/10/2012
95
19
25
110
600
0.24
3.5
17
26
11
0.18
310
2/29/2012
98
20
27
120
600
0.14
3.7
18
19
10
0.14
360
2/10/2012
84
13
24
59
460
0.12
3.5
15
16
9.2
0.10
210
2/29/2012
79
13
22
58
380
0.14
3.4
16
14
8.9
0.10
200
2/21/2012
68
3.7
61
61
370
0.35
2.1
18
19
11
0.18
250
2/21/2012
70
6.7
28
35
390
0.28
2.8
19
7.2
8.1
0.16
160
Date
R. Pancajoc
1/30/2012
ǂ
R. Chiquito
56
Q. Cancor
R. Pueblo Viejo
R. Zarco
R. Tze
56
Table 4.4 Total Cation, Silica, and CO2 Yields from Silicate
Weathering
+
TZ yield from silicate
weathering
Sample Location
3
Date
-2
10 mol km yr
CO2 yield from
silicate weathering
H4SiO4 yield
-1
3
-2
10 mol km yr
-1
3
-2
10 mol km yr
-1
Rio Raxon
1/20/2008
200
890
250
57
3/5/2008
^
81
400
140
3/11/2008
^
150
700
210
1/23/2008
760
1500
1100
3/5/2008
600
1100
890
3/11/2008
580
1100
870
2/2/2008
360
1500
480
2/15/2008
370
1600
460
3/1/2008
210
830
240
3/8/2008
430
1700
470
2/2/2008
1000
3300
1100
2/15/2008
660
2100
730
3/1/2008
390
1200
430
3/8/2008
970
3000
1100
Quebrada Chajonja
Trib. 1 to Chajonja
Trib. 2 to Chajonja
^ denotes yields calculated using the only discharge measured at that site, which was likely less than the discharge at the time of sampling.
57
Table 4.4 cont'd Total Cation, Silica, and CO2 Yields from Silicate Weathering
+
TZ yield from silicate
weathering
Sample Location
3
Date
-2
10 mol km yr
CO2 yield from silicate
weathering
H4SiO4 yield
-1
3
-2
10 mol km yr
-1
3
-2
10 mol km yr
-1
Q. Carabajal
1/25/2008
2/21/2008
#
3/6/2008
160
280
230
120
240
190
140
240
210
230
210
3/12/2008
#
140
R. Samilja
58
2/4/2008
*
160
±
33
590
±
120
240
±
48
2/21/2008
*
170
±
34
590
±
120
260
±
52
3/6/2008
*
76
±
15
310
±
63
140
±
29
3/12/2008
*
130
±
26
480
±
98
210
±
42
2/4/2008
*
140
±
31
450
±
97
180
±
39
2/21/2008
*
200
±
43
600
±
130
270
±
57
3/6/2008
*
100
±
22
320
±
70
130
±
28
3/12/2008
*
160
±
34
520
±
110
200
±
43
1/29/2008
*
340
±
60
360
±
64
600
±
107
2/13/2008
*
450
±
81
470
±
83
820
±
145
2/29/2008
*
470
±
82
500
±
88
820
±
145
3/7/2008
*
400
±
70
460
±
82
700
±
123
R. Toila
R. Matanzas
# denotes yields calculated using the lowest discharge measured at that site. * denotes yields calculated using estimated discharge.
58
Table 4.4 cont’d Total Cation, Silica, and CO2 Yields from Silicate Weathering
+
TZ yield from silicate
weathering
Sample Location
3
Date
-2
10 mol km yr
CO2 yield from silicate
weathering
H4SiO4 yield
-1
3
-2
10 mol km yr
-1
3
-2
10 mol km yr
-1
R. Sibija
1/29/2008
^
290
660
440
2/13/2008
320
790
500
2/29/2008
210
460
320
3/7/2008
220
480
340
R. Mululha
59
1/29/2008
*
78
±
16
330
±
67
120
±
25
2/13/2008
*
86
±
18
460
±
94
140
±
28
2/29/2008
*
120
±
25
540
±
110
180
±
37
3/7/2008
*
89
±
18
460
±
94
140
±
28
1/29/2008
*
110
±
24
410
±
92
150
±
33
2/13/2008
*
110
±
24
530
±
120
160
±
36
2/29/2008
*
140
±
30
600
±
130
190
±
43
3/7/2008
*
120
±
26
560
±
130
160
±
36
R. Pancajoc
^ denotes yield calculated using the highest discharge measured at that site. *denotes yields calculated using estimated discharge.
59
Table 4.4 cont'd Total Cation, Silica, and CO2 Yields from Silicate Weathering
+
TZ yield from silicate
weathering
Sample Location
3
Date
-2
10 mol km yr
CO2 yield from
silicate weathering
H4SiO4 yield
-1
3
-2
10 mol km yr
-1
3
-2
10 mol km yr
-1
R. Chiquito
2/9/2008
#
2/28/2008
190
550
270
200
530
260
340
960
490
370
960
570
Q. Cancor
2/9/2008
#
2/28/2008
60
R. Pueblo Viejo
2/9/2008
*
160
±
30
510
±
93
240
±
43
2/28/2008
*
150
±
28
430
±
79
230
±
41
2/20/2008
*
190
±
37
430
±
86
300
±
59
2/20/2008
*
120
±
24
430
±
91
170
±
36
R. Zarco
R. Tze
# denotes yields calculated using the lowest discharge measured at that site. * denotes yields calculated using estimated discharge.
60
Table 4.5 DOC, DON, and DOP Chemistry
Sample Location
Date
Precipitation
13
DOC
δ CDOC
DON
DOP
μmol/L
‰
μmol/L
μmol/L
-
-
0.7
0.27
1/21/2012
77.2
-28.8
-
3.45
3/6/2012
397
-30.0
8.5
-
3/12/2012
132
-31.0
8.1
0.36
1/24/2012
26.1
-
3.3
0.70
3/6/2012
68.8
-
12
1.21
3/12/2012
52.2
-
8.8
0.63
2/3/2012
133
-29.8
11
0.26
2/16/2012
66.2
-30.3
6.4
0.26
3/2/2012
61.6
-
4.2
0.46
3/9/2012
70
-
2.9
0.37
2/3/2012
64.7
-26.7
8.7
0.71
2/16/2012
967
-25.8
7.0
0.37
3/2/2012
45.5
-
6.4
0.55
3/9/2012
54.6
-
-
0.88
1/26/2012
28.1
-
0.91
3.24
2/22/2012
26.7
-
2.2
0.89
3/7/2012
38.5
-
5.8
1.16
3/13/2012
36.1
-
3.0
1.69
1/27/2012
91.4
-28.4
7.1
1.07
2/22/2012
100
-30.3
12
0.17
3/7/2012
320
-30.3
10
-
3/13/2012
157
-28.3
11
0.01
Rio Raxon
Quebrada Chajonja
Trib. 1 to Chajonja
Trib. 2 to Chajonja
Q. Carabajal
R. Samilja US
61
Table 4.5 cont'd DOC, DON, and DOP Chemistry
Sample Location
Date
13
DOC
δ CDOC
DON
DOP
μmol/L
‰
μmol/L
μmol/L
R. Samilja MS
2/7/2012
260
-28.5
8.2
-
2/22/2012
77.7
-27.6
8.2
0.18
3/7/2012
70.2
-28.6
12
-
3/13/2012
104
-29.7
7.6
0.03
2/5/2012
154
-28.9
6.3
-
2/22/2012
91.3
-29.3
9.3
0.17
3/7/2012
291
-29.4
12
-
3/13/2012
148
-29.2
6.2
0.10
2/5/2012
160
-30.2
7.1
-
2/22/2012
84
-29.8
8.6
-
3/7/2012
299
-29.5
9.6
-
3/13/2012
140
-30.7
4.3
0.02
1/30/2012
192
-30.5
11
0.10
2/14/2012
1302
-26.2
5.1
3.44
3/1/2012
60.4
-
5.9
0.80
3/8/2012
87.2
-30.5
8.3
0.50
1/30/2012
198
-28.8
12
0.33
2/14/2012
116
-30.5
6.6
0.44
3/1/2012
347
-29.7
9.2
0.36
3/8/2012
169
-30.5
5.0
0.26
R. Samilja DS
R. Toila
R. Matanzas
R. Sibija
62
Table 4.5 cont'd DOC, DON, and DOP Chemistry
Sample Location
Date
13
DOC
δ CDOC
DON
DOP
μmol/L
‰
μmol/L
μmol/L
R. Mululha
1/30/2012
302
-29.7
10
-
2/14/2012
123
-29.4
8.6
-
3/1/2012
130
-29.3
6.6
0.15
3/8/2012
127
-30.8
7.2
0.10
1/30/2012
244
-30.0
11
-
2/14/2012
96.6
-28.2
5.7
0.03
3/1/2012
85
-29.7
9.4
0.08
3/8/2012
103
-31.7
9.1
0.10
2/10/2012
35.9
-
2.7
0.43
2/29/2012
81.9
-30.7
7.4
0.52
2/10/2012
34.1
-
1.2
0.27
2/29/2012
48.1
-
-
0.25
2/10/2012
76.4
-29.7
5.8
-
2/29/2012
165
-30.2
5.6
-
2/21/2012
19.2
-
-
0.54
2/21/2012
20.2
-
4.9
0.46
R. Pancajoc
R. Chiquito
Q. Cancor
R. Pueblo Viejo
R. Zarco
R. Tze
63
Table 4.6 Diel Aqueous Major Ion Chemistry
Sample Location
Date
Time
CST (UTC6)
Na
K
NH3
Mg
Ca
Si
F
Cl
NO3
SO4
PO4
HCO3
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
1700
73
8.3
0.21
5.0
23
410
4.7
11
1.8
7.0
0.09
98
1800
73
8.4
0.30
5.0
23
420
5.4
10
2.0
5.2
0.08
100
1900
74
8.6
0.19
5.2
24
410
5.1
10
2.1
5.5
0.08
100
2000
73
8.4
0.13
5.5
23
410
4.6
11
2.3
7.0
0.09
100
2100
73
8.5
0.16
5.5
24
400
4.3
11
9.5
7.1
0.09
100
500
74
8.6
0.12
5.5
23
410
5.7
11
11
7.8
0.09
97
600
74
8.5
0.16
5.1
23
420
5.1
12
9.7
6.6
0.10
100
700
74
8.5
0.17
6.4
24
410
5.1
10
12
8.6
0.09
99
800
74
8.5
0.20
5.3
24
400
5.0
12
5.3
5.2
0.09
110
900
74
8.2
0.17
5.2
24
400
5.4
10
6.7
6.3
0.09
110
1700
87
8.5
0.17
6.5
28
460
5.6
12
9.3
7.5
0.11
130
1900
88
8.7
0.19
6.4
29
460
5.7
12
8.7
7.1
0.11
130
2100
89
8.8
0.19
6.2
29
470
5.6
12
1.5
6.6
0.10
140
2300
89
8.7
0.17
6.3
29
450
5.6
13
3.4
8.9
0.13
130
500
89
8.8
0.22
6.4
29
470
5.9
11
13
7.1
0.12
130
700
88
8.4
0.24
6.3
29
470
5.8
11
3.4
7.9
0.11
130
900
89
8.4
0.22
6.2
28
470
5.7
11
7.7
7.8
0.13
120
1100
90
8.6
0.23
6.1
29
470
6.1
12
11
7.7
0.10
130
Rio Raxon
2/8/2012
64
2/9/2012
2/23/2012
2/24/2012
64
Table 4.6 cont'd Diel Aqueous Major Ion Chemistry
Sample Location
Date
Time
CST (UTC6)
Na
K
NH3
Mg
Ca
Si
F
Cl
NO3
SO4
PO4
HCO3
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
μmol/L
1700
140
13
0.32
42
140
670
5.1
18
40
20
0.25
420
1800
130
13
0.21
43
150
660
5.0
17
41
20
0.20
460
1900
140
13
0.26
44
160
660
5.2
17
23
21
0.22
470
2000
130
13
0.23
44
160
660
4.9
17
60
20
0.23
470
2100
140
13
0.26
44
150
670
5.4
17
57
20
0.24
460
500
140
13
0.23
44
160
630
5.1
18
52
18
0.28
480
600
140
14
0.25
45
160
670
4.8
18
29
20
0.22
480
700
140
13
0.22
44
160
650
5.2
17
48
20
0.28
480
800
140
13
0.20
45
160
660
5.5
18
59
19
0.29
480
900
130
13
0.23
44
160
680
5.2
18
36
21
0.30
460
1700
140
13
0.15
49
190
690
5.3
18
13
24
0.19
540
1900
140
13
0.20
48
190
670
4.9
20
28
23
0.25
540
2100
140
14
0.29
50
190
710
5.4
17
51
23
0.32
550
2300
140
13
0.15
49
190
760
5.4
17
21
24
0.21
540
500
140
13
0.22
49
180
690
5.2
17
41
21
0.28
540
700
140
13
0.15
49
190
710
5.3
17
16
32
0.19
530
900
140
13
0.12
49
190
710
5.2
17
10
23
0.17
550
1100
140
13
0.17
50
190
730
5.2
18
16
22
0.20
560
Quebrada
Chajonja
2/8/2012
65
2/9/2012
2/23/2012
2/24/2012
65
Table 4.7 Diel DOC, DON, and DOP Chemistry
Date
13
Time
DOC
δ CDOC
TON
TOP
CST (UTC-6)
μmol/L
‰
μmol/L
μmol/L
Sample Location
Rio Raxon
2/8/2012
1700
1800
1900
2000
2100
2/9/2012
500
600
700
800
900
2/23/2012
1700
1900
2100
2300
2/24/2012
500
700
900
1100
5.65
1.13
6.91
0.85
0.93
0.94
3.22
10.85
0.96
5.68
-26.14
-28.05
-26.10
-26.88
-28.43
-29.87
-26.95
-26.55
-28.15
-26.57
17.44
17.76
16.44
17.65
6.13
9.00
4.65
5.70
7.12
4.25
0.14
0.79
0.19
0.12
0.07
0.08
0.12
0.15
0.16
0.10
3.56
3.50
0.88
0.84
1.25
3.71
0.80
0.80
-26.95
-26.71
-*
-27.62
-29.26
-26.77
-28.11
-28.85
5.50
4.21
6.92
9.13
4.98
6.44
9.10
2.16
0.17
0.20
0.18
0.19
0.11
0.07
0.10
0.15
*– means δ13C was undetectable
66
Table 4.7 cont’d Diel DOC & Nutrient Chemistry
Date
13
Time
DOC
δ CDOC
TON
TOP
CST (UTC-6)
μmol/L
‰
μmol/L
μmol/L
Sample Location
Quebrada Chajonja
2/8/2012
1700
1800
1900
2000
2100
2/9/2012
500
600
700
800
900
2/23/2012
1700
1900
2100
2300
2/24/2012
500
700
900
1100
0.59
2.82
3.02
2.38
0.33
1.23
0.33
0.33
0.35
0.34
-*
-25.55
-25.67
-26.44
-26.58
-
-#
7.36
-
1.07
0.62
0.55
0.75
0.79
0.64
0.61
0.81
0.78
0.66
0.42
0.34
0.37
0.32
0.35
0.31
0.39
0.50
-
6.96
1.50
2.62
3.02
1.91
0.63
0.50
0.70
0.68
0.75
0.67
0.63
0.67
* – means δ13C was undetectable
#
– means all nitrogen in sample was inorganic.
67
Table 4.8 Major and Minor Elements in Streambed Sediments and Shale
Sample Location
68
Streambed Sediments
Rio Raxon
Quebrada Chajonja
Trib. 1 to Chajonja
Trib. 2 to Chajonja
Q. Carabajal
R. Samilja US
R. Samilja MS
R. Samilja DS
R. Toila
R. Matanzas
R. Sibija
R. Mululha
R. Pancajoc
R. Chiquito
Q. Cancor
R. Pueblo Viejo
R. Zarco
R. Tze
Al2O3
wgt %
SiO2
wgt %
Fe2O3
wgt %
CaO
wgt %
TiO2
wgt %
MgO
wgt %
MnO
wgt %
K2O
wgt %
Na2O
wgt %
P2O5
wgt %
11.9
14.7
12.7
15.1
16.3
13.0
15.1
14.2
13.3
11.2
16.4
11.9
17.2
14.8
10.7
13.8
15.5
14.4
77.8
73.2
76.6
72.3
70.1
76.6
73.2
74.3
76.0
71.5
70.8
77.7
70.3
73.5
80.8
74.4
71.4
73.6
1.68
5.52
1.50
3.43
8.44
1.60
3.87
3.75
3.48
3.12
5.78
2.21
2.63
3.39
1.92
2.58
5.14
3.63
0.83
0.20
0.69
0.66
0.07
0.53
0.55
0.47
0.46
3.50
0.22
0.51
0.34
0.48
0.62
0.90
0.52
0.55
0.22
1.85
0.18
0.73
0.90
0.20
0.52
0.44
0.46
0.39
0.78
0.39
0.40
0.65
0.22
0.46
0.65
0.51
0.56
0.98
0.53
0.90
0.79
0.48
0.66
0.68
0.75
4.57
1.13
0.54
0.71
0.79
0.54
0.69
1.24
1.08
0.05
0.08
0.05
0.08
0.18
0.04
0.05
0.05
0.06
0.05
0.10
0.06
0.05
0.06
0.04
0.06
0.07
0.06
4.79
2.84
4.91
4.26
2.53
5.27
4.12
4.26
3.91
4.26
3.58
5.09
6.57
4.47
3.84
4.84
4.03
4.64
2.11
0.54
2.81
2.41
0.54
2.20
1.86
1.74
1.54
1.24
1.11
1.49
1.66
1.70
1.29
2.16
1.29
1.52
0.10
0.09
0.09
0.10
0.14
0.08
0.12
0.10
0.10
0.10
0.11
0.12
0.09
0.10
0.06
0.12
0.10
0.09
68
Table 4.8 cont'd Major and Minor Elements in Streambed Sediments and Shale
Sample Location
69
Bedrock Pizarro Shale*
Chajonja
San Marcos
Monte Blanco
Monte Blanco II
Samilja
Samilja II
Pancajoc
Al2O3
wgt %
SiO2
wgt %
Fe2O3
wgt %
CaO
wgt %
TiO2
wgt %
MgO
wgt %
MnO
wgt %
K2O
wgt %
Na2O
wgt %
P2O5
wgt %
21.1
23.9
19.5
14.7
15.4
18.5
20.5
63.8
62.5
67.5
72.0
69.9
68.2
65.1
8.18
6.66
6.67
6.24
7.71
5.86
7.45
0.005
0.04
0.03
1.10
0.05
0.01
0.01
0.95
1.07
1.05
0.97
0.68
0.86
1.09
1.77
1.29
1.57
0.86
2.71
1.84
1.80
0.05
0.01
0.03
0.09
0.06
0.01
0.03
3.69
2.85
2.73
1.78
2.42
3.00
2.92
0.30
1.58
0.86
2.12
0.90
1.64
0.93
0.11
0.12
0.07
0.13
0.12
0.11
0.15
*multiple samples of Pizarro shale were collected from locations spanning the study area (Figure 2.10).
69
Table 4.9 Mineralogy of Streambed Sediments
Sample Location
70
Streambed Sediments
Trib. 1 to Chajonja
Trib. 2 to Chajonja
Q. Carabajal
R. Samilja MS
R. Samilja DS
R. Toila
R. Matanzas
R. Sibija
R. Mululha
R. Pancajoc
R. Chiquito
R. Pueblo Viejo
R. Zarco
R. Tze
Quartz
Microcline
Albite
x
x
x
x
x
x
x
x
x
x
x
x
x
x
X
X
x
x
Anorthite
Muscovite
Illite
x
X
X
X
X
X
X
X
X
X
X
X
x
x
x
Clinochlore
Augite
Dolomite
x
X
x
x
x
x
x
x
x
X
x
x
x
x
x
x
x
x
x
70
x
x
x
x
Table 4.10 Organic Carbon and Total Nitrogen in Streambed Sediments
and Bedrock Shale
Sample Location
POC
13
δ CPOC
‰
wgt%
Streambed Sediments
Rio Raxon
Quebrada Chajonja
Trib. 1 to Chajonja
Trib. 2 to Chajonja
Q. Carabajal
R. Samilja US
R. Samilja MS
R. Samilja DS
R. Toila
R. Sibija
R. Mululha
R. Pancajoc
R. Chiquito
Q. Cancor
R. Pueblo Viejo
R. Zarco
R. Tze
Bedrock Shale
Chajonja
San Marcos
Monte Blanco
Monte Blanco II
Pancajoc
Cancor
N
C/N
wgt%
0.067
0.15
0.061
0.58
0.14
0.044
0.13
0.092
0.086
0.13
0.074
0.58
0.11
0.35
0.11
0.12
0.12
-26.3
-24.8
-27.3
-29.6
-24.3
-26.6
-24.6
-23.8
-23.9
-25.1
-25.7
-29.0
-25.9
-29.0
-26.1
-26.6
-27.4
0.009
0.016
0.008
0.044
0.088
0.006
0.037
0.032
0.018
0.067
0.015
0.045
0.044
0.019
0.018
0.042
0.026
7.7
9.4
8.1
13
1.6
8.0
3.6
2.9
4.9
2.0
4.9
13
2.5
19
6.1
2.9
4.6
0.29
0.50
0.49
0.81
0.20
0.44
-27.1
-27.2
-24.5
-24.5
-23.8
-22.5
0.076
0.10
0.10
0.10
0.096
0.052
3.8
5.0
4.8
8.0
2.0
8.5
71
2000
Discharge = 43.6 ± 7.85 * WS Area +
33.8 ± 92.4
p<0.00005, t-stat > t |crit|
1800
1600
Discharge (L/s)
1400
1200
1000
800
600
400
200
0
0
5
10
15
Watershed Area
20
25
30
(km2)
Figure 4.1. Discharge v. Watershed Area for rivers draining the north side of the Sierra
de las Minas.
72
8.0
R. Raxon
Q. Chajonja
7.0
Trib. 1 to Chajonja
Trib. 2 to Chajonja
F (μmol L-1)
6.0
Q. Carabajal
R. Samilja US
5.0
R. Samilja MS
R. Samilja DS
4.0
R. Toila
R. Matanzas
3.0
R. Sibija
R. Mululha
2.0
R. Pancajoc
R. Chiquito
1.0
Q. Cancor
R. Pueblo Viejo
0.0
0
50
100
150
Ca (μmol
L-1)
200
250
R. Zarco
R. Tze
Figure 4.2. Ca v. F for all samples. Corrected for precipitation using the chemistry of the
bulk rainwater sample.
73
250
Group 1
Group 2
200
Na+K (μmol/L)
R. Matanzas
150
100
50
0
0
50
100
150
200
250
300
350
400
Ca +Mg (μmol/L)
Figure 4.3. Na+K v. Ca+Mg corrected for precipitation. Plot portrays single samples
from each river that represent samples collected more than 24 hours after rainfall.
74
Group 1
800
Group 2
R. Matanzas
TZ+ (μmol/L)
600
400
200
0
0
200
400
600
800
Si (μmol/L)
Figure 4.4. Total dissolved cations versus dissolved reactive Si corrected for
precipitation. Portrays single samples from each stream that are from samples collected
more than 24 hours after rainfall.
75
800
Group 1
700
Group 2
R. Matanzas
Ca + Mg (μeq/L)
600
500
400
300
200
100
0
0
100
200
300
400
500
600
700
800
HCO3 (μeq/L)
Figure 4.5. Ca+Mg v. HCO3 corrected for precipitation. Portrays single samples from
each stream that were collected more than 24 hours after rainfall.
76
100
Carbonates
Molar HCO3/Na ratio
Range of basalt values
10
Group 2
Group 1
R. Matanzas
1
Silicates
0.1
0.1
1
10
100
Molar Ca/Na ratio
Figure 4.6 (A). HCO3/Na v. Ca/Na corrected for precipitation. Portrays single samples
that are the best approximation of baseflow chemistry. Basaltic compositions are taken
from Dessert et al. (2003). End member compositions for felsic silicates and carbonates
are a range of values determined by Négrel et al. (1993) and Gaillardet et al. (1999).
77
10
Range of basalt values
Molar Mg/Na ratio
Carbonates
1
Group 2
Group 1
0.1
Silicates
R. Matanzas
0.01
0.1
1
10
100
Molar Ca/Na ratio
Figure 4.6 (B). Mg/Na v. Ca/Na corrected for precipitation. Portrays single samples that
are the best approximation of baseflow chemistry. Basaltic compositions are taken from
Dessert et al. (2003). End member compositions for felsic silicates and carbonates are a
range of values determined by Négrel et al. (1993) and Gaillardet et al. (1999).
78
1000000
TZ+ Flux (103 mol/yr)
100000
10000
1000
100
0.1
1
10
Watershed Area (km2)
Figure 4.7. Total cation flux v. watershed area.
79
100
1000
Group 1
100
Group 2
80
60
81
40
Rainwater
20
Carbonate Weathering
Silicate Weathering
R. Matanzas
Q. Chajonja
Q. Cancor
Q. Carabajal
R. Zarco
R. Sibija
R. Samilja DS
R. Chiquito
R. Samilja MS
R. Pueblo Viejo
R. Samilja US
R. Tze
R. Toila
Trib. 2 to Chajonja
Trib. 1 to Chajonja
R. Raxon
R. Pancajoc
R. Mululha
0
Figure 4.8. Diagram showing the relative source of solute input based on the model of Gaillardet et al. (1999) and Goldsmith et
al. (2008). Sites are in order of least carbonate input to most carbonate input. Groups 1 and 2 are those introduced in Chapter 4.
80
-27
R. Raxon
Samilja US
R. Matanzas
-28
R. Mululha
R. Pancajoc
R. Toila
δ13CDOC (‰)
-29
Samilja DS
Samilja MS
-30
-31
-32
0
100
200
300
400
500
DOC (μmol/L)
Figure 4.9. DOC v. δ13C for multiple samples taken from the same locations over the
course of the field season.
81
5
4.5
SUVA280
4
3.5
R. Raxon
3
R. Samilja US
R. Samilja MS
2.5
R. Samilja DS
R. Toila
2
0
50
100
150
200
250
300
350
400
450
DOC (μmol/L)
Figure 4.10. DOC v. SUVA280 for multiple samples taken from the same location over
the course of the field season.
82
Nitrate and TON (μmol L-1)
20
18
Nitrate
16
TON
14
12
10
8
6
4
2
0
1700
1800
1900
2000
2100
500
600
700
800
900
Time (CST, UTC-6)
Figure 4.11. Total organic nitrogen and Nitrate behavior from 1700 February 8, 2012 to
0900 February 9, 2012. Line breaks represent a period of 8 hours from 2100 to 0500
during which no samples were collected. Error of measurements is 5%. Sunset began at
~1800. Sun was fully set by 2000.
83
120
DOC (μmol/L)
100
80
60
40
R. Raxon
20
Q. Chajonja
0
0
50
100
150
200
250
300
350
400
Time (hours)
Figure 4.12. DOC concentrations over time for incubation experiments conducted during
the field season with unfiltered water collected from Rio Raxon and Quebrada Chajonja.
84
1000
100
10
85
1
0.1
Al2O3
SiO2
Fe2O3
CaO
TiO2
MgO
MnO
K2O
Figure 4.13. Streambed sediment concentrations normalized to Monte Blanco shale.
85
Na2O
P2O5
R. Raxon
Q. Chajonja
Trib. 1 to Chajonja
Trib. 2 to Chajonja
Q. Carabajal
R. Samilja US
R. Samilja MS
R. Samilja DS
R. Toila
R. Matanzas
R. Sibija
R. Mululha
R. Pancajoc
R. Chiquito
Q. Cancor
R. Pueblo Viejo
R. Zarco
R. Tze
10
R. Raxon
Q. Chajonja
Trib. 1 to Chajonja
Trib. 2 to Chajonja
Q. Carabajal
R. Samilja US
1
R. Samilja MS
86
R. Samilja DS
R. Toila
R. Matanzas
R. Sibija
0.1
R. Mululha
R. Pancajoc
R. Chiquito
Q. Cancor
R. Pueblo Viejo
0.01
Al2O3
R. Zarco
SiO2
Fe2O3
CaO
TiO2
MgO
MnO
K2O
Na2O
R. Tze
Figure 4.14. Streambed sediment concentrations normalized to concentrations from San Agustín Gneiss taken from Newcomb
(1975).
86
CHAPTER 5: DISCUSSION
5.1. Watershed Area and Discharge
Average daily discharges in the Rio Matanzas were obtained from a gaging
station operated by the Instituto Nacíonal de Sismología, Vulcanología, Meteorología e
Hidrología (INSIVUMEH) of Guatemala (pers. comm.) for the years 2003 to 2010. These
data show a pronounced dry season from December through April and a pronounced wet
season from May through November (Figure 2.1). More specifically, the lowest flows
observed between days 1 to 91 (January through March) from 2004 through 2010 were
observed between days 40 and 80 (Feb 9 to March 20 or 21, depending on leap year).
These low discharges are similar to the discharge for the Rio Matanzas calculated using
the linear relationship of discharge and watershed area in section 4.1 (~25–30 m3 s-1
compared to ~31 m3 s-1, respectively) (Figure 5.1). This similarity further supports the
legitimacy of extrapolating discharge to larger watersheds using a simple linear
relationship between discharge and watershed area for smaller gaged streams in the same
hydrologic regime. Though the INSIVUMEH hydrograph does show evidence of storms
during the dry season, the effect of dry season storms on discharge was as much as an
order of magnitude less than the effect of the wet season storms on Rio Matanzas
discharge. Given the differences between the wet and dry season observed in the
INSIVUMEH record from May 2003 to May 2010 (Figure 2.1), it is reasonable to
87
suggest that discharges measured or estimated in this study underestimate the annual
average discharge for the studied rivers. This means that any annual flux and yield
calculations made using these discharge values may underestimate actual annual fluxes
and yields.
A linear relationship between discharge and watershed area for streams draining
( )
the south side of the Sierra de las Minas was observed wherein
(
)
(
|
|)
(Trierweiller, 2010, Trierweiller et al., in review) (Figure 5.2). The slope of this
relationship for streams draining the south side of the Sierra de las Minas is roughly one
fourth the slope of the relationship for streams draining the north side of the mountains
mentioned in section 4.1 (11±1.8 compared to 44±7.7, respectively). The difference
between these relationships is likely caused by the four to five-fold difference in
precipitation between the south and north side of the Sierra de las Minas (~500 mm yr-1
versus ~2500 mm yr-1, respectively) (Holder, 2006). This precipitation difference is the
result of a rain shadow created by the Sierra de las Minas as winds from the Caribbean
Sea bring rain from the northwest to the southeast. This wind direction creates a
windward and leeward side of the Sierra de las Minas wherein the windward, north side
of the range receives more rainfall than the south, leeward side of the range (Holder,
2006).
Gaillardet et al. (2011) also found a linear relationship between discharge and
watershed area for streams in the Lesser Antilles. In addition, windward watersheds were
found to have a roughly two-fold greater slope than leeward watersheds. This difference
88
was also mainly attributed to the roughly two-fold greater precipitation received by the
windward side of island chain (Gaillardet et al., 2011). From this, a negative feedback
mechanism is suggested for the global volcanic CO2 cycle. This feedback mechanism is
predicated on rain shadows created by high-relief volcanoes that cause local increases in
the hydrologic cycle which foster increased chemical weathering (Gaillardet et al., 2011).
Though the Sierra de las Minas is not an active volcanic mountain belt, this negative
feedback mechanism should not be ignored when considering the role of high standing
islands and active mountain belts in the global carbon cycle. The importance of physical
denudation promoting high rates of weathering in these terrains has been illustrated (e.g.
Carey et al., 2005b; Lyons et al., 2005; Goldsmith et al., 2008a). The role of orographic
hydrologic forcing on global geochemical cycles may warrant more consideration,
especially when considering transport limitations on chemical weathering as noted by
West et al., (2005) and observed positive correlations between precipitation and chemical
yields (e.g. Carey et al., 2005b).
5.2. Chemical Weathering Fluxes and Yields
The CO2 yields observed in this study for watersheds draining the north side of
the Sierra de las Minas are within the range of values seen in world rivers (Table 5.1) and
fall mostly within the range of those values seen in active margins and high standing
islands (e.g. Andes and New Zealand). These yields also have a much higher range than
those observed for watersheds on the south side of the Sierra de las Minas (1.1 to 375 x
103 mol km-2 yr-1) (Trierweiler, 2010) (Table 5.1), supporting the hypothesis that an
increase in hydrologic budget leads to an increase in weathering yields. The highest
89
yields observed rival those seen in volcanic terrains, which have been shown to have
higher chemical weathering rates than most sedimentary and metamorphic regions
(Louvat and Allègre, 1997; Dessert et al., 2001; Goldsmith et al., 2010). This is an
interesting find considering the Sierra de las Minas have no volcanic rocks and are mostly
composed of the Pizarro shale and San Augustín gneiss with some granite at higher
elevations. These high CO2 yields may result from the frequent and widespread landslide
activity that occurs in the Sierra de las Minas as landslides can expose fresh rock surfaces
to chemical weathering (Lyons et al., 2005). Future quantification of landslide density
within each watershed will elucidate this potential for landslides to increase chemical
weathering rates. The high rates of silicate weathering observed in the Sierra de las Minas
underscore the importance of small mountainous rivers draining actively uplifting terrains
in the global carbon cycle as noted by others (Lyons et al., 2005; Carey et al., 2006;
Goldsmith et al., 2008).
Because there is so little input from carbonate weathering, the differences in
solute weathering fractions among the rivers are controlled by the rain-derived solute
input. This is supported by comparing solute input fractions for samples taken during
rainfall events and samples taken at least 3 days after rainfall events (Figure 5.3). During
rainfall events, solute input from rainwater in the Rio Raxon, Tributary 1 to Chajonja,
and Tributary 2 to Chajonja increased from 13% to 22%, 13% to 15%, and 10% to 12%,
respectively. The model used to calculate relative inputs of silicate weathering, carbonate
weathering, and rainwater input insists that the sum of all inputs is 100%, and so these
90
increases in rainwater input correspond with equal decreases in relative silicate
weathering input.
The presence of carbonate derived solutes in streams not known to be underlain
by this Permian carbonate sequence as mapped by Bonis et al. (1970) suggests a sporadic
presence of carbonate in the Pizarro shale underlying these rivers. This suggestion is
supported by elemental analysis of bedrock shale samples, which showed inorganic
carbon concentrations between 0.11 and 0.53 wt% in three bedrock shale samples.
Specifically, inorganic carbon was found in bedrock shale samples collected within the
Rio Chajonja and Quebrada Carabajal watersheds (2% and 1% carbonate weathering
input, respectively). Jacobson et al. (2003) also noted the input of calcite weathering in
New Zealand watersheds draining not carbonate but a schist bedrock lithology.
5.3. Streambed Sediment Geochemistry
Enrichment of CaO, K2O, and Na2O in sediments from most streams compared to
bedrock shale suggests the streambed sediments are sourced not only from the Pizarro
shale exposed at the lower elevations of the Sierra de las Minas but also from the San
Agustín gneiss and granite lithologies that compose the top of the mountain range. The
almost two order of magnitude difference in calcium observed when normalizing
streambed sediments to Monte Blanco shale results from the extremely low calcium in
the Monte Blanco shale (0.03 wt% CaO). All but one bedrock shale sample (Monte
Blanco II, 1.10 wt% CaO) had calcium less than 0.05 wt% CaO. Sediments from the Rio
Matanzas were the only sediments with a presence of dolomite, likely the reason why
CaO and MgO concentrations observed in those sediments were the highest seen.
91
5.4. Dissolved Organic Carbon and Nutrient Dynamics
No observed changes in δ13C of DOC with changes in DOC suggest that increases
in DOC are not the result of a change in DOC source but rather a change in input from
the same or similar sources. The variations observed in δ13C at low DOC concentrations
may result from changes in source of DOC. The δ13C of DOC in streams with low
concentrations of DOC would be more susceptible to changes in source than the δ13C of
DOC in streams with high concentrations of DOC. No concurrent changes in SUVA280
with changes in DOC concentration further support the idea that a single source or similar
sources are responsible for the observed variations in DOC. SUVA280 values in rivers
were typically between 3 and 4.5, suggesting a high aromatic content from a terrestrial
source. The Quebrada Chajonja was the only river with SUVA280 values below 2.
Increases in DOC during the continual day-to-night, night-to-day sampling that
corresponded with increases in δ13C of that DOC might indicate a change in DOC source
from terrestrial to animal or human waste. People would be travelling back to their homes
or to the fields at these times and would often stop to bathe in the streams. Increases in
NO3- concurrent with decreases in DON observed during the transition from day to night
may indicate microbial nitrification of organic nitrogen after the sun falls.
5.4.1. Incubation DOC Dynamics
Dissolved organic carbon (DOC) incubation experiments performed with water
from two rivers (Rio Raxon and Quebrada Chajonja) showed an increase in DOC
concentrations over a time period of sixteen days, but these increases occurred at
different rates. The differences in rate of DOC increase between waters from the two
92
rivers are likely a result of a difference in DOC type determined by UV-Vis analysis.
Quebrada Chajonja DOC has a lower, or more aliphatic, SUVA280 than DOC from the
Rio Raxon (1.7 compared to 3.3, respectively). This qualitative change in the DOC from
the Quebrada Chajonja may mean that its DOC can be more readily utilized by microbial
communities than DOC from the Rio Raxon, hence the faster initial rate of increase in the
Quebrada Chajonja.
5.5. Dissolved Organic Carbon Fluxes and Yields
Riverine dissolved organic carbon (DOC) fluxes for ranged from 26 x 103 mol
yr˗1 (Tributary 2 to Chajonja) to 1300000±230000 x 103 mol yr-1 (Rio Matanzas) (Table
5.2). The error in DOC flux for the Rio Matanzas reflects the error inherent in estimating
discharge from watershed area using the equation discussed in section 5.1. Dissolved
organic carbon yields ranged from 16 x 103 mol km-2 yr-1 (Quebrada Carabajal) to 2800 x
103 mol km-2 yr-1 (Tributary 2 to Chajonja) (Table 5.2). In general, these DOC yields are
comparable to but on the low end of the CO2 yields observed from chemical weathering
discussed above (in 103 mol C km-2 yr-1).
DOC yield in the Rio Raxon appeared to increase with an increase in discharge.
Though discharge was only measured once in the Rio Raxon, the highest DOC yield
corresponds to a sample taken during a precipitation event of approximately three days
when the stage of the river was much higher than when discharge was measured. It is not
surprising that DOC increased with discharge as the increase in precipitation that would
cause an increase in discharge would also cause an increase in overland flow. This
increase in overland flow will transport more DOC into the stream as there is more water
93
running over organic debris on the surface (Brinson, 1976; McDowell and Asbury, 1994).
This relationship between discharge and DOC has been most recently noted by Yoon and
Raymond (2012), who observed a roughly five-fold increase of DOC concentrations in
samples taken from the Esopus Creek watershed in eastern New York during Hurricane
Irene in 2011. This increase in DOC with an increase in discharge is especially important
when considering the role of Hurricane Mitch (1998) in transporting carbon through
rivers draining the Sierra de las Minas. If such an increase in DOC concentrations
occurred during the Hurricane Mitch event, then DOC flux during that event would have
would have been much greater than the fluxes observed in this study.
Dissolved organic carbon yields (in tons km-2 yr-1) for rivers in this study have a
wide range when compared to world rivers (Table 5.3). The highest yields in this study
match up well with yields from Papua New Guinea (Burns et al., 2001), a similar tropical
mountain region with high rainfall, and are much greater than those measured in a Puerto
Rican montane forest over a decade (McDowell and Asbury, 1994). This difference
between the highest yield values for this study and those in Puerto Rico may be due to
differences in precipitation between the two regions, but could also be a result of data
resolution. The highest yields in this study are based on spot sampling over a ten-week
period in the dry season, whereas the yields for Puerto Rican watersheds are based on
continual sampling over multiple wet and dry seasons. The DOC yields in this study are
based on data collected during the dry season. Given the stark differences in wet season
and dry season hydrology observed in the Rio Matanzas, the annual yields for streams
draining the north side of the Sierra de las Minas are likely underestimated in this study.
94
5.6. Event Particulate Organic Carbon Export Suggested by Sediment Chemistry
As mentioned in section 4.7.3, carbon to nitrogen ratios and 13C in streambed
sediment and bedrock shale samples were mostly similar (Figure 5.5). Most streambed
sediment samples also had less organic carbon than the bedrock shale samples analyzed
in this study (Figure 5.6). These relationships suggest that most, if not all of the
particulate organic carbon in the streambed sediments is sourced from the bedrock
Pizarro shale. This means that any soil that may have been mobilized during landslide
activity has since been mobilized out of the streambed and exported farther down the
watershed. If this landslide mobilized soil was transported to Lago Izabal at the mouth of
the Rio Polochíc, into which all sampled rivers drain, then it may have been buried and
effectively removed from the atmosphere. The high (≥30 cm yr-1) sedimentation rate at
the mouth of the Polochíc determined in sediment cores (Michot et al., 2002) is
comparable to rates observed in the Bengal fan (Suckow et al., 2001), where a ~70%
organic carbon burial efficiency has been determined (Galy et al., 2007). Thus, upwards
of 70% of the particulate organic carbon mobilized by landslides that was transported
through the fluvial network to Lago Izabal may have been buried and removed from
atmospheric oxidation. This burial of organic carbon is also suggested by the presence of
organic-rich layers in sediment cores taken from sites on and near the Polochíc delta,
implying carbon burial at the mouth of the river (Michot et al, 2002). No attempt was
made to quantify the carbon content of these layers, but they were classified using color
and texture. The soil may have also been delivered to the Polochíc valley floodplain. The
valley floods during most wet seasons and was flooded during Hurricane Mitch (Claus
95
Droeges, pers. comm.). The valley is heavily cultivated, so it is possible that any
landslide mobilized soil carbon deposited on the Polochíc valley floodplain now
participates in the agricultural carbon and soil dynamics of the region.
Three streambed sediment samples fall outside the C/N ratio and 13C range of
the shale samples (Quebrada Cancor, Tributary 2 to Chajonja, and Rio Pancajoc) (Figure
5.4). These three sediment samples have higher organic carbon than the other streambed
sediment samples and show a much more depleted 13C signature than the shale samples
(Figure 5.5). This suggests that much of the organic carbon in the streamed sediments of
these rivers may be derived from soil carbon. It is unclear why soil carbon would be
stable in these three streambeds compared to the others. One of the three streams drained
the smallest watershed sampled and had a high density of riparian vegetation (Figure
5.6). This vegetation may impede export of particulate organic matter from the
watershed. Future analysis of soil carbon, nitrogen, and 13C may elucidate the
speculations discussed above. If these chemical signatures can be used to determine the
fate of landslide mobilized soil, then this may represent a way to estimate POC transport
post-event. Of course, these chemical data would need to be combined with measured
landslide areas and at least an estimation of soil profile thickness before the landslide
event.
It seems reasonable to speculate that some of the landslide mobilized soil carbon
would be quickly exported out of the streambed. Others have observed large increases in
particulate organic carbon export associated with large storms (Goldsmith et al., 2008b).
Goldsmith et al. (2008b) found that particulate organic carbon yield from the Choshui
96
River during Typhoon Mindulle was equal to 72–95% of the annual particulate organic
carbon export for the highest yielding world rivers. In addition, the USGS Hurricane
Mitch project mapped landslide scours throughout the northern Sierra de las Minas that
extend into the Polochíc valley from first and second order watersheds where landslides
had occurred (Figure 5.7). Long landslide scours extending the entire length of a given
watershed were observed in all streams but the Quebrada Carabajal, Quebrada Cancor,
Tributary 1 to Chajonja, Tributary 2 to Chajonja, Rio Chiquito, and Rio Pancajoc. The
terminations of the landslide scours in the Rio Chiquito and Quebrada Carabajal are distal
from the sampling point, whereas the scours in the Rio Pancajoc and Quebrada Cancor
are proximal to the sampling location. Differences in landslide scour transport of
mobilized soil provide the best explanation of the differences observed in carbon,
nitrogen, and δ13C of streambed sediments and bedrock shale discussed above.
A landslide scour that runs the entire length of a watershed may indicate that
landslide mobilized material was immediately exported down the fluvial-hillslope
interface and completely out of the watershed during Hurricane Mitch. However, a scour
that terminates near a sampling point may have delivered its organic carbon to the
streambed sediments sampled at that point. Any immediate export of material probably
delivered carbon to Lago Izabal, where it would have been buried in the high sediment
flux and effectively removed from the atmosphere. Future analysis of soil carbon
concentrations on the north side of the Sierra de las Minas combined with quantification
of landslide areas will allow for an estimate of particulate organic carbon flux from
97
watersheds into Lago Izabal caused by Hurricane Mitch. This analysis will likely affirm
the importance of event controlled carbon export in regional and global carbon budgets.
98
Table 5.1 CO2 Yields from Silicate Weathering for World Rivers
CO2 yield from silicate
weathering
3
Watershed Region
This Study
Dominica Rivers
a
1.1–375
b
190–1575
Taranaki Region, New Zealand
c
217–2926
Sedimentary and Ruapehu Region,
c
New Zealand
Greywacke and Argillite Region, New Zealand
North Island, New Zealand
128–851
c
875
d
170–1074
d
296–946
South Island, New Zealand
e
51
f
220–1000
Congo
Himalayas
f
Deccan Traps
-2
110±3.1–1100
South Side of Sierra de las Minas
Andes
-1
10 mol yr km
100–320
g
Reunion Island
580–2540
h
Martinique and Guadeloupe
a
Trierweiler (2010)
b
Goldsmith et al. (2010)
c
Goldsmith et al. (2008a)
d
Lyons et al. (2005)
e
Gaillardet et al. (1995)
f
Edmond and Huh (1997)
g
Louvat and Allègre (1997)
h
Dessert et al. (2001)
i
Rad et al. (2006)
1300–4400
i
1100–1400
99
Table 5.2 Dissolved Organic Carbon Flux and Yield
Sample Location
DOC flux
3
Date
10 mol yr
DOC yield
-1
3
-2
10 mol km yr
-1
Rio Raxon
1/21/2012
3/6/2012
^
4380
22500
183
938
^
7490
312
1/24/2012
3/6/2012
510
1080
72
152
3/12/2012
Trib. 1 to Chajonja
807
114
2/3/2012
2/16/2012
545
230
454
192
3/2/2012
3/9/2012
103
243
86
203
Trib. 2 to Chajonja
2/3/2012
112
320
2/16/2012
3/2/2012
976
25.3
2790
72
3/9/2012
75.5
216
3/12/2012
Quebrada Chajonja
Q. Carabajal
1/26/2012
2/22/2012
#
292
236
19
16
3/7/2012
3/13/2012
#
340
319
23
21
R. Samilja US
1/27/2012
*
4610
±
1070
132
±
30
2/22/2012
3/7/2012
*
*
5050
16100
±
±
1170
3720
144
460
±
±
33
106
3/13/2012
R. Samilja MS
2/7/2012
*
7920
±
1830
226
±
52
*
17200
±
3770
366
±
80
2/22/2012
*
5150
±
1130
110
±
24
3/7/2012
*
4650
±
1020
99
±
22
3/13/2012
*
6890
±
1510
147
±
32
^denotes fluxes and yields calculated using the only discharge measured at that site.
#denotes fluxes and yields calculated using the lowest discharge measured.
*denotes fluxes calculated using estimated discharge.
100
Table 5.2 cont'd Dissolved Organic Carbon Flux and Yield
Sample Location
DOC flux
3
Date
10 mol yr
DOC yield
-1
3
-2
10 mol km yr
-1
R. Samilja DS
2/5/2012
*
14600
±
3020
218
±
45
2/22/2012
*
8640
±
1790
129
±
27
3/7/2012
*
27500
±
5680
410
±
85
3/13/2012
*
14000
±
2890
209
±
43
2/5/2012
2/22/2012
3/7/2012
3/13/2012
R. Matanzas
1/30/2012
2/14/2012
3/1/2012
3/8/2012
R. Sibija
1/30/2012
2/14/2012
3/1/2012
3/8/2012
R. Mululha
1/30/2012
2/14/2012
3/1/2012
3/8/2012
R. Pancajoc
1/30/2012
2/14/2012
3/1/2012
3/8/2012
R. Chiquito
2/10/2012
2/29/2012
*
*
*
*
9590
5030
17900
8390
±
±
±
±
2170
1140
4050
1900
228
120
426
200
±
±
±
±
52
27
96
45
*
*
*
*
157000
1070000
49500
71500
±
±
±
±
29000
198000
9140
13200
266
1810
84
121
±
±
±
±
49
335
15
22
^
5810
3400
5140
2770
*
*
*
*
21900
8920
9430
9210
±
±
±
±
4860
1980
2090
2040
421
172
181
177
±
±
±
±
93
38
40
39
*
*
*
*
13100
5180
4560
5520
±
±
±
±
3010
1190
1050
1270
345
136
120
145
±
±
±
±
79
31
28
33
#
940
2120
R. Toila
323
189
286
154
52
118
*denotes fluxes and yields calculated using estimated discharge.
^denotes fluxes and yields calculated using the highest discharge measured at that site.
#denotes fluxes and yields calculated using the only discharge measured at that site.
101
Table 5.2 cont'd Dissolved Organic Carbon Flux and Yield
Sample Location
DOC flux
3
Date
10 mol yr
DOC yield
-1
3
-2
10 mol km yr
-1
Q. Cancor
2/10/2012
2/29/2012
R. Pueblo Viejo
2/10/2012
2/29/2012
R. Zarco
2/21/2012
R. Tze
2/21/2012
#
656
925
*
*
14900
32300
±
±
2880
6250
106
231
±
±
21
45
*
2240
±
454
27
±
5.5
*
1270
±
29
28
±
0.6
#denotes fluxes and yields calculated using the only discharge measured at that site.
*denotes fluxes and yields calculated using estimated discharge.
102
Table 5.3 DOC Yields from World Rivers
DOC yield
-2
Watershed Region
tons km yr
This Study
0.21–37
New Zealand
Guadeloupe
a
0.57–5.2
b
1.6±0.9–5.7±2.6
c
1.6
d
1.5
Yukon
Yukon
Mackenzie
d
0.72
d
St. Lawrence
Niger
1.35
e
0.5
f
British Rivers (median)
Canadian Atlantic
3.2
g
2.9
Puerto Rico forested montane
Sepik, Papua New Guinea
Himalaya, Sikkim
Pearl, China
a
b
h
i
j
k
0.4–5.2
4.9–15.5
67
2.95
Carey et al. (2005a)
Lloret et al. (2011)
c
Strieg et al. (2004)
d
Telang et al. (1991)
e
Martin and Probst (1991)
f
Hope et al. (1997)
g
Clair et al. (1994)
h
i
McDowell and Asbury (1994)
Burns et al. (2001)
j
k
-1
Sharma and Rai (2004)
Callahan et al. (2004)
103
250
2004
2005
200
2006
103
Discharge (m3/s)
2007
2008
150
2009
2010
100
50
0
1
31
61
91
Day of the Year
Figure 5.1. Mean daily discharge in the Rio Matanzas during the dry season (January through March) for years 2004 to 2010.
Units on x-axis are day of the year beginning at January 1st for each of the seven years represented.
104
2000
1800
1600
Discharge = 11.7 ± 2.17 * WS Area + 147.45 ± 54.79
p<0.00005, t-stat > t|crit|
Discharge (L/s)
1400
1200
1000
800
600
400
200
0
0
20
40
60
Watershed Area
80
100
(m2)
Figure 5.2. Discharge v. Watershed Area for rivers draining the south side of the Sierra
de las Minas (from Trierweiler, 2010, Trierweiler et al., in review).
105
100%
80%
60%
40%
Rainwater
Silicate Weathering
20%
Trib. 2 to Chajonja*
Trib. 2 to Chajonja
Trib. 1 to Chajonja*
Trib. 1 to Chajonja
R. Raxon*
R. Raxon
0%
Figure 5.3. Relative input of solutes for samples taken during storms (denoted with *)
and samples taken during near baseflow conditions.
106
-21
Shale
Sediment
δ13CPOC (‰)
-23
-25
-27
-29
-31
0
2
4
6
8
10
12
14
16
18
20
C/N
Figure 5.4. δ13CPOC v. C/N in streambed sediment and shale samples. Error bars
represent one standard deviation of replicate or triplicate measurements. Markers that
show no error bars have standard deviations within the area of the marker. Three
sediment samples (from Quebrada Cancor, Tributary 2 to Chajonja, and Rio Pancajoc)
are more depleted in δ13CPOC and have higher C/N ratios than other streambed sediments
and shale samples.
107
-21
Shale
Sediment
δ13CPOC (‰)
-23
-25
-27
-29
-31
0
5
10
15
20
25
1/Corg (wgt%)
Figure 5.5. δ13CPOC v. 1/Corg in streambed sediment and shale samples. Error bars
represent one standard deviation of replicate or triplicate measurements. Markers that
show no error bars have standard deviations within the area of the marker. Three
sediment samples (from Quebrada Cancor, Tributary 2 to Chajonja, and Rio Pancajoc)
are more depleted in δ13CPOC and have higher carbon concentrations than other streambed
sediments and shale samples.
108
Figure 5.6. Photograph of Tributary 2 to Chajonja showing abundant near stream and
some in stream vegetation.
109
109
Figure 5.7. (A). Map of Landslide activity triggered by Hurricane Mitch (in red). Red lines are scours. Labels bolded and
underlined are those with scours that do not extend the full length of the watershed. Courtesy of USGS.
110
110
Figure 5.7. (B). Map of landslide activity triggered by Hurricane Mitch (in red) for watersheds. Red lines are scours. Bolded and
underlined labels are those with scours that do not extend the full length of the watershed. Courtesy of USGS.
111
CHAPTER 6: CONCLUSIONS AND FUTURE DIRECTIONS
6.1. Conclusions
This study supports other observations illustrating the important role active
mountain terrains play in the global carbon cycle and therefore the global climate cycle.
CO2 yields calculated for the north side of the Sierra de las Minas rival those seen in
volcanic terrains and other active margins (110±3.1–1100 x 103 mol km-2 yr-1). This
range of CO2 yields is about an order of magnitude higher than the range of yields
calculated for the south side of the Sierra de la Minas (1.1–375 x 103 mol km-2 yr-1)
(Trierweiler, 2010). This difference in yields can be attributed to lithologic differences,
but is thought to more likely results from the differences in precipitation between the
north and south side of the mountains. Differences in precipitations between the north
and the south side of the Sierra de las Minas result from a rain shadow created by the
high peaks of the mountain range. This orographic forcing on hydrologic budgets should
not be ignored when considering the importance of mountain building events in global
chemical, and specifically carbon cycling.
The range of dissolved organic carbon yields calculated in this study runs from
the lowest observed global values to the second highest global value observed (0.21–37 t
km-2 yr-1). This large range may be due to variations in dissolved organic carbon caused
by storm event increases in DOC. Dissolved organic carbon was shown to increase
112
during storms. Thus, it is likely that the lowest DOC yields calculated herein
underestimate actual yields because samples were collected during the dry season. Others
have also observed increased dissolved organic carbon concentrations and thus yields
from extreme rainfall events (Yoon and Raymond, 2012), accounting for roughly 43% of
the annual dissolved organic carbon flux. Similar increases in dissolved organic carbon
yields occurred during Hurricane Mitch. If such increases did occur, then eventcontrolled carbon export calculations focused mainly on particulate material may
significantly underestimate actual organic carbon flux.
This study also illustrated the usefulness of carbon isotope chemistry to provide
insight into past event-controlled particulate carbon export. Observed similarities and
differences in δ13C between bedrock shale and streambed sediments suggest that much of
the soil organic carbon mobilized by landslides during Hurricane Mitch was exported out
of the mountain watersheds and either into the valley or, more likely, Lago Izabal. This
speculation is consistent with findings by others that have illustrated the efficiency of
particulate carbon export during extreme storm events (Goldsmith et al., 2008). Such
efficient carbon export is equal to between 72% and 95% of the annual particulate carbon
export observed in the highest yielding rivers (Goldsmith et al., 2008). Future
quantification of landslide density and soil carbon content in watersheds draining the
north side of the Sierra de las Minas will allow for calculations of Hurricane Mitch
particulate carbon export. It is expected that this event export will rival that seen for
Typhoon Mindulle in 2004 (Goldsmith et al., 2008).
113
6.2. Future Directions
Future work should first focus on quantifying landslide density within each
watershed. These calculated densities will provide meaningful insights into the role
landslides play as a control on chemical weathering and organic carbon transport in
active mountain terrains. Precipitation can play an important role in triggering landslides,
and so it is likely that orographic increases in hydrologic budget will create a positive
feedback involving precipitation, landslides, and fluvial yields. Increased temporal
resolution of landslide occurrence during periods between extreme storm events will
further elucidate this potential feedback relationship. In addition, event sampling during
extreme storms such as Hurricane Mitch, similar to that conducted by Goldsmith et al.
(2008), would provide ground-truth for estimates of particulate carbon transport
calculated using satellite images to quantify landslide density (e.g. Ramos-Sharrón et al.,
2012). Such event sampling would also provide an opportunity to quantify chemical
weathering and dissolved organic carbon yields during an extreme storm in the Sierra de
las Minas. In addition, wet season sampling would provide data that could be compared
to dry season data and shed more light on the role of precipitation as a control on fluvial
yields. Study of sediments delivered to Lago Izabal by the Rio Polochíc could provide the
data necessary to confirm speculations on carbon delivery to Lago Izabal during
Hurricane Mitch and other extreme storm events.
114
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121
Appendix A: Ion Chromatography analysis of waters
122
Major Ion Data
Sample Name
F
Cl
SO4
Na
K
Mg
Ca
ppm
ppm
ppm
ppm
ppm
ppm
ppm
Rio Raxon
1/21/2012
0.10
0.34
0.56
1.8
0.27
0.20
1.9
3/6/2012
0.058
0.32
0.39
1.0
0.25
0.16
1.4
3/12/2012
0.10
0.41
0.60
1.5
0.28
0.23
2.2
1/24/2012
0.093
0.62
2.1
3.2
0.44
1.8
3.8
3/6/2012
0.085
0.59
2.1
3.2
0.46
1.6
4.3
3/12/2012
0.10
0.58
2.0
3.1
0.46
1.7
4.4
1/26/2012
0.065
0.81
1.3
2.3
0.20
1.3
4.9
2/22/2012
0.057
0.79
1.2
2.2
0.20
1.1
4.7
3/7/2012
0.058
0.84
1.4
2.4
0.23
1.3
4.9
3/13/2012
0.052
0.88
1.4
2.4
0.22
1.3
5.0
1/27/2012
0.10
0.34
0.97
2.0
0.38
0.60
4.4
2/22/2012
0.099
0.33
1.1
1.9
0.33
0.61
4.5
3/7/2012
0.067
0.27
0.53
1.1
0.24
0.31
2.9
3/13/2012
0.081
0.30
0.95
1.6
0.30
0.46
3.9
1/30/2012
0.062
0.67
1.3
1.2
0.60
1.8
6.6
2/14/2012
0.067
0.65
1.4
1.4
0.42
2.5
11
3/1/2012
0.064
0.75
1.8
1.8
0.45
2.6
10
3/8/2012
0.058
0.70
1.4
1.7
0.47
2.0
7.9
1/30/2012
0.063
0.62
0.92
2.1
0.66
1.8
4.6
2/14/2012
0.056
0.53
1.1
2.4
0.53
2.0
4.8
3/1/2012
0.081
0.53
1.1
2.9
0.56
2.5
5.4
3/8/2012
0.085
0.52
0.99
2.8
0.55
2.4
5.3
1/30/2012
0.061
0.38
0.38
1.3
0.36
0.38
1.8
2/14/2012
0.072
0.34
0.38
1.5
0.31
0.34
1.8
3/1/2012
0.092
0.41
0.47
2.0
0.37
0.51
2.2
3/8/2012
0.070
0.37
0.51
1.5
0.32
0.36
1.8
Quebrada Chajonja
Q. Carabajal
R. Samilja US
R. Matanzas
R. Sibija
R. Mululha
123
Major Ion Data
Sample Name
F
Cl
SO4
Na
K
Mg
Ca
ppm
ppm
ppm
ppm
ppm
ppm
ppm
R. Pueblo Viejo
2/10/2012
0.066
0.54
0.89
1.9
0.48
1.1
4.0
2/29/2012
0.064
0.57
0.86
1.8
0.48
1.0
3.9
2/21/2012
0.047
0.63
0.78
1.6
0.15
2.5
4.1
2/21/2012
0.053
0.66
0.78
1.6
0.24
1.3
2.6
Precipitation
B.D.
0.59
0.55
0.37
0.036
0.095
0.27
Field Blank 1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Field Blank 2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Field Blank 3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Field Blank 4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1700
0.089
0.39
0.67
1.7
0.30
0.25
1.8
1800
0.10
0.35
0.50
1.7
0.30
0.25
1.8
1900
0.096
0.36
0.53
1.7
0.31
0.25
1.9
2000
0.088
0.39
0.67
1.7
0.30
0.27
1.9
2100
0.083
0.39
0.68
1.7
0.31
0.27
1.9
500
0.11
0.37
0.75
600
0.097
0.43
0.63
1.7
0.31
0.25
1.8
700
0.096
0.37
0.82
1.7
0.31
0.32
1.9
800
0.096
0.42
0.50
1.7
0.31
0.26
1.9
0.10
0.37
0.60
1.7
0.30
0.26
1.9
1700
0.11
0.44
0.72
1900
0.11
0.43
0.68
2.0
0.32
0.31
2.2
2100
0.11
0.42
0.63
2.0
0.32
0.30
2.3
2300
0.11
0.44
0.85
2.0
0.31
0.31
2.3
R. Zarco
R. Tze
Rio Raxon
2/8/2012
2/9/2012
900
1.7
0.31
0.27
1.9
2/23/2012
2.0
124
0.31
0.32
2.2
Major Ion Data
Sample Name
F
Cl
SO4
Na
K
Mg
Ca
ppm
ppm
ppm
ppm
ppm
ppm
ppm
Rio Raxon
2/24/2012
500
0.11
0.40
0.68
2.0
0.32
0.31
2.3
700
0.11
0.39
0.63
2.0
0.31
0.33
1.3
900
0.11
0.39
0.75
2.0
0.30
0.31
2.2
1100
0.12
0.42
0.74
2.0
0.31
0.30
2.3
Filter Blank 1
0.0
0.0
0.0
0.0
0.0
0.0
0.19
Filter Blank 2
0.0
0.0
0.0
0.0
0.0
0.0
0.12
1700
0.097
0.65
2.0
3.1
0.47
1.9
6.3
1800
0.095
0.61
2.0
3.0
0.49
1.9
7.0
1900
0.10
0.61
2.0
3.0
0.49
1.9
7.2
2000
0.092
0.61
1.9
3.0
0.49
1.9
7.2
0.10
0.61
1.9
3.1
0.48
1.9
6.9
500
0.097
0.64
1.7
3.1
0.49
1.9
7.4
600
0.092
0.64
2.0
3.1
0.49
2.0
7.4
700
0.098
0.62
1.9
3.1
0.49
1.9
7.4
800
0.10
0.62
1.9
3.1
0.48
1.9
7.4
900
0.098
0.63
2.0
3.0
0.48
1.9
7.3
1700
0.10
0.63
2.3
3.2
0.48
2.1
8.4
1900
0.094
0.72
2.2
3.2
0.48
2.1
8.4
2100
0.10
0.62
2.2
3.3
0.49
2.1
8.5
0.10
0.61
2.3
3.2
0.48
2.1
8.4
500
0.099
0.61
2.0
3.2
0.47
2.1
8.3
700
0.10
0.62
3.1
3.2
0.46
2.1
8.5
900
0.10
0.61
2.2
3.2
0.46
2.1
8.5
0.099
0.64
2.1
3.2
0.48
2.1
8.6
Quebrada Chajonja
2/8/2012
2100
2/9/2012
2/23/2012
2300
2/24/2012
1100
125
Appendix B: Skalar™ Nutrient Analysis of waters
126
Nutrient Data
Sample Name
Ammonia
Phosphate
Nitrate +
Nitrite
Total
Nitrogen
Total
Phosphorous
Reactive
Silica
ppb
ppb
ppb
ppb
ppb
ppb
Rio Raxon
1/21/2012
266.1
3.7
11.6
323.8
110.4
12036.1
3/6/2012
6.8
1.8
7.2
226.3
-11.7
5399.9
3/12/2012
Quebrada
Chajonja
5.5
2.4
8.5
237.7
13.4
9605.3
1/24/2012
4.2
26.6
37.2
570.1
48.2
18743.1
3/6/2012
5.9
10.1
21.8
477.1
47.5
17834.3
3/12/2012
11.0
7.6
21.0
426.0
27.0
18270.8
1/26/2012
17.6
2.9
45.3
661.7
103.1
12620.8
2/22/2012
8.3
2.7
23.9
373.7
30.3
12941.0
3/7/2012
13.6
3.0
19.6
367.6
38.9
12696.2
3/13/2012
19.1
2.6
17.9
309.0
54.8
12451.2
1/27/2012
5.3
4.6
8.0
216.7
37.6
14226.2
2/22/2012
4.7
5.1
0.5
184.4
10.2
14197.9
3/7/2012
5.3
1.9
0.5
151.0
-5.4
7470.3
3/13/2012
3.1
4.0
1.3
168.6
4.3
11651.6
1/30/2012
6.3
3.2
13.2
350.8
6.4
8868.4
2/14/2012
32.6
3.3
19.6
373.6
109.9
11480.1
3/1/2012
4.2
4.1
12.4
260.6
28.8
12179.6
3/8/2012
4.3
3.5
14.5
322.3
18.8
11335.3
1/30/2012
5.0
6.0
7.7
275.0
16.3
12571.5
2/14/2012
1.9
4.3
0.2
96.0
18.1
15111.1
3/1/2012
2.7
6.3
0.5
138.8
17.3
17324.7
3/8/2012
3.4
12.2
7.8
182.1
20.4
16531.1
1/30/2012
6.8
3.7
7.4
256.1
-5.3
7707.7
2/14/2012
4.7
3.6
2.4
157.7
2.7
10829.9
3/1/2012
3.9
4.1
0.6
103.1
8.6
12808.4
3/8/2012
4.4
3.2
0.6
112.2
6.3
10879.8
Q. Carabajal
R. Samilja US
R. Matanzas
R. Sibija
R. Mululha
127
Nutrient Data
Sample Name
Ammonia
Phosphate
Nitrate +
Nitrite
Total
Nitrogen
Total
Phosphorous
Reactive
Silica
ppb
ppb
ppb
ppb
ppb
ppb
R. Pancajoc
3.7
3.9
5.1
5.5
11.6
8.4
326.0
201.6
0.8 9690.5
4.8 12492.6
2.9
177.6
7.7
14140.4
3/8/2012
7.7
5.9
7.1
6.2
8.3
248.3
8.5
13106.1
1/30/2012
2/14/2012
3/1/2012
Trib. 1 to
Chajonja
2/2/2012
3.6
4.2
0.8
163.9
12.1
14090.9
2/15/2012
1.5
4.0
0.8
101.7
12.0
17829.8
3/1/2012
4.2
6.4
3.5
111.9
20.7
19653.8
3/8/2012
4.7
8.8
13.8
238.1
20.2
19170.8
Trib. 2 to
Chajonja
2/2/2012
4.7
26.2
46.0
770.4
48.1
21179.6
2/15/2012
3.0
37.3
39.4
653.6
48.9
23344.6
3/1/2012
4.0
34.6
41.5
674.6
51.6
24355.3
3/8/2012
6.4
35.7
46.1
643.7
63.0
24509.8
2/5/2012
3.6
4.5
5.0
173.4
-0.1
10168.2
2/22/2012
1.9
4.9
1.1
136.5
4.1
13467.1
3/7/2012
7.3
2.6
5.7
220.2
-3.5
7297.7
3/13/2012
4.6
3.9
6.4
154.6
4.5
11688.9
2/5/2012
5.4
3.4
13.6
282.5
2.9
10887.6
2/22/2012
4.1
3.5
1.1
149.4
9.5
13716.6
3/7/2012
5.4
2.4
5.1
246.6
-6.0
8054.4
3/13/2012
5.5
2.8
0.7
101.5
5.1
12057.3
2/7/2012
4.5
3.2
0.1
120.3
2.2
11550.9
2/22/2012
3.6
4.1
0.0
117.8
8.9
14401.3
3/7/2012
6.2
4.1
1.1
192.8
-6.2
8541.7
3/13/2012
6.4
4.0
3.8
164.2
5.8
11843.6
2/10/2012
3.2
3.0
20.9
332.9
16.3
13586.6
2/29/2012
5.4
4.5
29.4
520.0
20.7
13093.8
2/10/2012
4.0
5.5
25.9
383.4
13.9
16924.7
2/29/2012
2.3
4.4
18.9
270.8
12.3
16936.9
R. Toila
R. Samilja DS
R. Samilja MS
R. Chiquito
Q. Cancor
128
Nutrient Data
Sample Name
Ammonia
Phosphate
Nitrate +
Nitrite
Total
Nitrogen
Total
Phosphorous
Reactive
Silica
ppb
ppb
ppb
ppb
ppb
ppb
R. Pueblo Viejo
2/29/2012
2.0
2.4
3.0
3.1
16.0
13.9
306.3
274.3
-3.6 12797.3
1.6 10783.3
2/21/2012
6.0
5.7
18.7
255.1
22.4
10334.6
2/21/2012
4.8
5.1
7.2
173.4
19.3
10902.4
Precipitation
233.0
-0.3
7.9
292.4
8.4
-36.9
Field Blank 1
9.2
-0.1
0.1
222.1
-1.3
18.3
Field Blank 2
9.3
-0.3
0.2
254.8
-0.8
5.8
Field Blank 3
9.7
-0.3
0.3
203.7
-1.2
-5.1
Field Blank 4
9.8
0.0
0.4
207.0
-2.4
-13.3
1700
3.6
2.9
1.8
269.3
7.1
11551.0
1800
5.0
2.6
2.0
277.0
27.0
11686.2
1900
3.2
2.5
2.1
259.3
8.3
11596.0
2000
2.2
2.7
2.3
279.7
6.4
11381.9
2100
2.8
2.7
9.5
219.4
4.8
11332.4
500
2.1
2.8
11.5
287.0
5.3
11624.5
600
2.7
3.0
9.7
201.1
6.7
11656.7
700
2.9
2.7
11.9
247.1
7.3
11568.0
800
3.4
2.7
5.3
174.4
7.7
11335.8
900
2.9
2.7
6.7
152.8
5.9
11262.6
1700
2.9
3.5
9.3
206.8
8.7
12766.3
1900
3.2
3.4
8.7
180.8
9.6
12886.7
2100
3.2
3.1
1.5
117.3
8.6
13110.2
2300
2.9
4.0
3.4
175.2
10.0
12574.3
2/10/2012
R. Zarco
R. Tze
Rio Raxon
2/8/2012
2/9/2012
2/23/2012
129
Nutrient Data
Sample Name
Ammonia
Phosphate
Nitrate +
Nitrite
Total
Nitrogen
Total
Phosphorous
Reactive
Silica
ppb
ppb
ppb
ppb
ppb
ppb
Rio Raxon
2/24/2012
500
3.7
3.8
12.7
247.2
7.1
13184.6
700
4.1
3.4
3.4
137.8
5.6
13232.0
900
3.7
4.1
7.7
235.7
7.3
13086.5
1100
3.9
3.2
11.4
189.7
7.8
13210.7
Filter Blank 1
10.9
0.2
0.0
194.6
-4.0
0.9
Filter Blank 2
12.5
0.0
0.0
195.3
-0.6
-29.7
1700
5.4
7.7
39.8
505.5
40.7
18124.8
1800
3.6
6.2
41.2
448.1
25.4
17949.8
1900
4.4
6.8
22.8
422.2
23.8
18261.6
2000
3.9
7.0
60.1
485.1
30.2
17859.3
2100
4.4
7.6
57.3
477.4
32.1
18197.5
500
4.0
8.6
52.1
525.2
28.5
18389.8
600
4.3
6.8
28.9
402.9
25.8
18545.5
700
3.7
8.6
47.7
530.9
33.6
17787.0
800
3.5
9.0
59.3
524.7
33.0
18335.6
900
3.9
9.4
35.9
464.5
30.0
17987.5
1700
2.6
5.8
12.6
273.8
25.2
19186.7
1900
3.4
7.6
28.3
328.5
23.1
19053.6
2100
5.0
9.8
51.4
406.0
31.5
17707.7
2300
2.6
6.6
20.8
312.1
27.7
19151.8
500
3.8
8.7
41.3
441.0
31.8
19352.0
700
2.6
6.0
16.2
263.7
26.8
19083.6
900
2.0
5.1
10.5
189.1
24.6
18940.5
1100
2.9
6.3
16.1
251.7
27.2
18869.7
Quebrada
Chajonja
2/8/2012
2/9/2012
2/23/2012
2/24/2012
130
Appendix C: Dissolved Organic Carbon and stable carbon-13 isotope analysis
131
DOC and stable carbon-13 isotope data
δ13C of
DOC
(‰)
DOC
(ppm)
Sample Name
1
2
3
1
2
3
Rio Raxon
0.913
4.774
1.581
0.935
4.766
1.575
0.933
4.765
1.605
-28.79
-28.41
-29.21
-30.64
-29.46
-29.97
-29.33
-30.80
-32.99
0.313
0.824
0.632
0.316
0.825
0.627
0.310
0.828
0.619
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
0.339
0.327
0.464
0.418
0.342
0.322
0.466
0.429
0.331
0.313
0.456
0.453
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
1.110
1.196
3.877
1.874
1.111
1.206
3.836
1.881
1.069
1.209
3.806
1.911
-27.08
-30.03
-28.05
-28.11
-31.28
-31.45
-31.11
-29.75
-30.09
-29.34
-28.40
-27.24
3.134
0.963
0.862
1.261
3.140
0.929
0.832
1.261
3.086
0.905
0.835
1.217
-29.62
-27.73
-28.27
-28.09
-27.29
-27.52
-28.86
-26.36
-30.66
-28.09
-30.86
-30.18
2.284 2.321 2.313
2/14/2012 15.228 15.749 15.899
0.722 0.727 0.727
3/1/2012
1.047 1.052
1.04
3/8/2012
-29.97
-30.94
-30.64
-26.95
-26.08
-25.66
N/A
N/A
N/A
-29.20
-32.38
-30.03
-30.45
-29.08
-29.58
-28.95
-29.44
-29.88
-29.21
-28.50
-30.25
-27.74
-33.07
-31.48
1/21/2012
3/6/2012
3/12/2012
Quebrada Chajonja
1/24/2012
3/6/2012
3/12/2012
Q. Carabajal
1/26/2012
2/22/2012
3/7/2012
3/13/2012
R. Samilja US
1/27/2012
2/22/2012
3/7/2012
3/13/2012
R. Matanzas
1/30/2012
2/14/2012
3/1/2012
3/8/2012
R. Sibija
1/30/2012
R. Mululha
1/30/2012
2/14/2012
3/1/2012
3/8/2012
3.507
1.437
1.550
1.473
3.724
1.494
1.555
1.551
3.651
1.502
1.561
1.532
132
DOC and stable carbon-13 isotope data
δ13C of
DOC
(‰)
DOC
(ppm)
Sample Name
1
2
3
1
2
3
R. Pancajoc
1/30/2012
2/14/2012
3/1/2012
3/8/2012
2.847
1.157
0.999
1.242
2.956
1.159
1.019
1.244
2.984
1.162
1.043
1.213
-29.88
-30.21
-29.81
-26.72
-29.53
-28.32
-30.86
-28.60
-29.57
-30.92
-31.51
-32.77
1.586
0.784
0.738
0.852
1.592
0.803
0.727
0.837
1.603
0.795
0.752
0.831
-28.93
-30.54
-30.04
-28.53
-30.47
-31.76
N/A
N/A
N/A
N/A
N/A
N/A
0.782 0.773 0.776
11.849 11.730 11.219
0.548 0.543 0.548
0.642 0.663 0.659
-26.58
-26.74
N/A
-25.85
-25.86
-25.68
N/A
N/A
N/A
N/A
N/A
N/A
Trib. 1 to Chajonja
2/2/2012
2/15/2012
3/1/2012
3/8/2012
Trib. 2 to Chajonja
2/2/2012
2/15/2012
3/1/2012
3/8/2012
R. Toila
2/5/2012
2/22/2012
3/7/2012
3/13/2012
2.323
1.408
4.151
2.005
2.367
1.397
4.134
2.028
2.422
1.358
4.21
2.065
-28.87
-28.39
-29.11
-31.05
-29.92
-30.39
-30.18
-29.13
-29.87
-29.60
-29.84
-31.96
1.915
1.005
3.603
1.654
1.934
0.997
3.572
1.687
1.926
1.021
3.584
1.708
-29.83
-29.27
-31.39
-31.58
-28.17
-29.69
-29.19
-29.61
-29.75
-29.82
-31.29
-30.96
1.835
1.079
3.53
1.739
1.857
1.078
3.492
1.779
1.867
1.130
3.463
1.8
-28.23
-27.88
-30.52
-30.33
-29.30
-28.23
-29.31
-29.78
-29.07
-29.81
-27.14
-30.63
0.443
0.967
0.423
0.973
0.426
1.007
N/A
N/A
N/A
-30.23
-31.72
-30.26
0.404
0.587
0.392
0.556
0.431
0.588
N/A
N/A
N/A
N/A
N/A
N/A
R. Samilja DS
2/5/2012
2/22/2012
3/7/2012
3/13/2012
R. Samilja MS
2/7/2012
2/22/2012
3/7/2012
3/13/2012
R. Chiquito
2/10/2012
2/29/2012
Q. Cancor
2/10/2012
2/29/2012
133
DOC and stable carbon-13 isotope data
δ13C of
DOC
(‰)
DOC
(ppm)
Sample Name
1
2
3
1
2
3
R. Pueblo Viejo
0.908
1.980
0.899
1.954
0.945
2.013
-32.56
-27.63
-28.93
-30.01
-29.90
-30.79
2/21/2012
0.243
0.231
0.219
N/A
N/A
N/A
2/21/2012
0.255
0.250
0.224
N/A
N/A
N/A
0.108
1.250
1.138
0.095
1.256
1.124
N/A
N/A
1.309
1.205
-27.38
-30.60
-33.11
-31.21
-29.90
-30.12
5.619
1.114
6.716
0.896
0.897
5.633
1.144
6.981
0.752
0.949
5.711
1.141
7.020
0.904
0.944
-26.74
-26.13
-25.53
-26.83
-28.63
-28.68
-25.85
-26.39
-26.06
-25.05
-26.40
-29.18
-30.88
-27.19
-27.22
0.919
3.166
12.633
0.932
5.564
0.936
3.234
9.071
0.978
5.703
0.952
3.256
-28.97
-29.40
-31.23
-27.13
-27.26
-26.45
-26.35
-26.76
0.977
5.776
-31.78
-28.68
-23.98
-26.38
-26.85
-26.49
3.512
3.468
0.881
0.866
3.567
3.514
0.871
0.797
3.588
3.532
0.883
0.868
-26.97
-26.67
-27.21
-26.08
-26.84
-27.22
N/A
N/A
N/A
-29.56
-25.09
-28.21
2/10/2012
2/29/2012
R. Zarco
R. Tze
Precipitation
Field Blank 1
Field Blank 2
Field Blank 3
Rio Raxon
2/8/2012
1700
1800
1900
2000
2100
2/9/2012
500
600
700
800
900
2/23/2012
1700
1900
2100
2300
134
DOC and stable carbon-13 isotope data
δ13C of
DOC
(‰)
DOC
(ppm)
Sample Name
1
2
3
1
2
3
1.218
3.703
0.794
0.774
1.267
3.737
0.807
0.815
1.275
3.699
0.794
0.816
-30.37
-28.94
-28.48
-26.11
-26.82
-27.37
-27.90
-28.93
-27.52
-29.27
-28.29
-28.99
0.736
0.764
0.783
0.780
0.746
0.765
N/A
N/A
N/A
N/A
N/A
N/A
0.612
2.875
3.071
2.415
0.348
0.544
2.722
2.959
2.339
0.311
0.601
2.849
3.023
2.378
0.340
1.192
0.336
0.346
0.335
0.343
1.247
0.335
0.323
0.356
0.351
0.427
0.343
0.338
0.372
0.340
0.318
0.399
0.509
Rio Raxon
2/24/2012
500
700
900
1100
Filter Blank 1
Filter Blank 2
Quebrada Chajonja
2/8/2012
1700
1800
1900
2000
2100
N/A
N/A
N/A
-25.57
-25.67
-25.42
-25.34
-25.18
-26.49
-26.03
-26.20
-27.08
N/A
N/A
N/A
1.247
0.326
0.331
0.357
0.331
-25.89
-27.95
-25.90
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
0.416
0.329
0.311
0.347
0.415
0.341
0.325
0.387
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
0.354
0.299
0.387
0.504
0.353
0.302
0.389
0.499
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
2/9/2012
500
600
700
800
900
2/23/2012
1700
1900
2100
2300
2/24/2012
500
700
900
1100
135
DOC and stable carbon-13 isotope data
δ13C of
DOC
(‰)
DOC
(ppm)
Sample Name
1
2
3
Raxon Incubations
1 day
1 day
1
0.931
5.390
0.922
5.431
0.949
5.453
N/A
-32.72
N/A
-27.06
-26.66
-27.80
2 days
2 days
0.991
0.992
0.999
0.997
1.002
1.004
N/A
N/A
N/A
N/A
N/A
N/A
4 days
4 days
1.088
1.071
1.098
1.079
1.105
1.073
-29.94
-32.95
-33.35
-33.20
-30.83
-32.75
8 days
8 days
1.239
1.174
1.272
1.198
-31.47
1.217
-28.25
-27.68
-30.89
-33.35
16 days
16 days
1.163
1.255
1.271
1.289
1.240
1.310
-30.51
-29.90
-28.31
-28.08
-31.04
-30.64
Chajonja Incubations
0.427
1 day
0.460
1 day
0.430
0.457
0.440
0.465
N/A
N/A
N/A
N/A
N/A
N/A
2 days
2 days
0.537
0.638
0.551
0.642
0.545
0.657
N/A
N/A
N/A
N/A
N/A
N/A
4 days
4 days
0.571
0.565
0.562
0.567
0.562
0.579
N/A
N/A
N/A
N/A
N/A
N/A
8 days
8 days
0.539
0.662
0.602
0.681
0.580
0.675
N/A
N/A
N/A
N/A
N/A
N/A
16 days
16 days
0.710
0.578
0.703
0.564
0.711
0.596
N/A
N/A
N/A
N/A
N/A
N/A
136
2
3