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ENVIRONMENTAL CONTROLS ON CARBONATE MINERAL DISSOLUTION: RATES AND MAGNITUDES
By
JOHN E. EZELL
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2016
© 2016 John E. Ezell
To My Family
4
ACKNOWLEDGMENTS
I would like to thank my advisor, committee, family, friends, and all those who
remind us that when you’re all alone and there’s nobody home it’s nice to be able to
count on a friend.
5
TABLE OF CONTENTS page
ACKNOWLEDGMENTS .................................................................................................. 4
LIST OF TABLES ............................................................................................................ 7
LIST OF FIGURES .......................................................................................................... 8
ABSTRACT ................................................................................................................... 10
CHAPTER
1 INTRODUCTORY REMARKS ................................................................................ 12
2 TEMPORAL VARIATIONS IN CALCITE DISSOLTUION RATES DURING FLOODING OF KARST SPRINGS ......................................................................... 20
2.1 Introduction ....................................................................................................... 20 2.2 Study Sites and Methods .................................................................................. 23
2.2.1 Study Sites .............................................................................................. 23 2.2.2 Methods ................................................................................................... 25
2.2.2.1 Field methods and sample analyses .............................................. 25 2.2.2.2 Mixing estimates of river water and groundwater ........................... 27 2.2.2.3 Dissolution rates estimates ............................................................ 28 2.2.2.4 Impacts of mixing/dissolution Ca2+ additions and DOC
remineralization on carbonate dissolution ............................................... 30 2.3 Results ............................................................................................................. 31
2.3.1 Peacock Springs ..................................................................................... 31 2.3.2 Madison Blue Spring .............................................................................. 32
2.4 Discussion ....................................................................................................... 34 2.4.1 Temporal Variations in Dissolution Rates ................................................ 34 2.4.2 Comparisons of Rate Models .................................................................. 35 2.4.3 Saturation States and Dissolution Magnitude Through the Recession .... 36
2.5 Conclusions ...................................................................................................... 38
3 RELATIVE AMOUNTS OF DISSOLUTION IN CARBONATE TERRAINS FROM LOSING RIVERS AND DIRECT PRECIPITATION ................................................. 49
3.1 Introduction ....................................................................................................... 49 3.2 Study Sites and Methods .................................................................................. 51
3.2.1 Study Sites .............................................................................................. 51 3.2.2 Methods ................................................................................................... 53
3.2.2.1 Monitoring data and historical reversal estimates .......................... 53 3.2.2.2 Field methods and sample analyses .............................................. 54 3.2.2.3 Recharge and dissolution modeling ............................................... 56
3.3 Results .............................................................................................................. 60
6
3.3.1 Rainfall and Recharge ............................................................................. 60 3.3.2 Hydrologic Responses ............................................................................. 60 3.3.3 Historic Record of High Water Events ..................................................... 60 3.3.4 Dissolution Estimates .............................................................................. 62
3.4 Discussion ........................................................................................................ 63 3.4.1 Dissolution Estimates .............................................................................. 64 3.4.2 Implications for Regional Geomorphology and Hydrology ....................... 67
3.5 Conclusions ...................................................................................................... 68
4 THE IMPACT OF BIOGEOCHEMICAL DRIVEN CARBONATE DISSOLUTION WITH POTENTIAL CLIMATIC IMPLICATIONS ...................................................... 76
4.1 Introduction ....................................................................................................... 76 4.2 Study Site and Methods .................................................................................... 80
4.2.1 Study Site ................................................................................................ 80 4.2.2 Field Methods and Sample Analyses ...................................................... 80 4.2.3 Estimates of Potential Dissolution and Chemical Species ....................... 83
4.3 Results .............................................................................................................. 84 4.4 Discussion ........................................................................................................ 86
4.4.1 Relative Impact of Tidal and Solar Radiation Cycles on Dissolution Potential ........................................................................................................ 86
4.4.2 Implications for Platform Dissolution........................................................ 89 4.4.3 Quantifying Dissolution Driven by Carbonic vrs. Sulfuric Acid and C
Flux to the Atmosphere ................................................................................. 90 4.5 Conclusions ...................................................................................................... 94
5 SUMMARY ........................................................................................................... 105
LIST OF REFERENCES ............................................................................................. 108
BIOGRAPHICAL SKETCH .......................................................................................... 117
7
LIST OF TABLES
Table page 2-1 Various dissolution rates. ................................................................................... 40
2-2 DOC concentrations, SI values, and dissolution rates for the four sampled floods. ................................................................................................................. 41
4-1 Water chemistry and parameters for grab samples ............................................ 96
8
LIST OF FIGURES
Figure page 2-1 Maps of river and cave systems. ........................................................................ 42
2-2 Conductivity and temperature through time at spring vents ................................ 43
2-3 Concentrations of calcium and calcite saturation indices through time. .............. 44
2-4 Time variations in the river stage, dissolution rates for reversals, and cumulative dissolution ........................................................................................ 45
2-5 Total calcite dissolution as measured by Ca2+ for each event by the SD equation (black) and the PWP equation (Gray). ................................................. 46
2-6 Predicted calcite dissolution values and SI range durations. .............................. 47
2-7 Measured and mixed Ca2+ concentrations and measured SI 0 and mixed SI 0 Ca2+ concentrations through time.. ..................................................................... 48
3-1 Karst terrain under normal and storm conditions.. .............................................. 70
3-2 Maps of the drainage basin and cave. ................................................................ 71
3-3 Stage data for Pinetta (dashed red line) and Madison Blue (black solid line) ..... 72
3-4 River and spring responses to rainfall.. .............................................................. 73
3-5 Limestone river bank along the Suwannee River in north Florida. ..................... 74
3-6 Long term Pinetta Gauge Station stage data from 1932 to 2013 ........................ 75
4-1 Map of The Bahamas and San Salvador.. .......................................................... 97
4-2 Conceptual model of a cross section of Inkwell Bluehole during high and low tide. . .................................................................................................................. 98
4-3 Depth profiles collected on May 6, 2012 showing............................................... 99
4-4 Dissolved oxygen, water depth, and pH plotted through time at the nearshore site in Inkwell. . ................................................................................................ 100
4-5 pH values and variation from mean water level ................................................ 101
4-6 Sulfide concentrations and variation from mean water level ............................. 102
4-7 d 13C values and variation from mean water level. ............................................ 103
9
4-8 Dissolved inorganic carbon concentrations and variation from mean water level .................................................................................................................. 104
10
Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
ENVIRONMENTAL CONTROLS ON CARBONATE MINERAL DISSOLUTION: RATES
AND MAGNITUDES
By
John E. Ezell
May 2016
Chair: Jonathan Martin Major: Geology
Carbonate minerals, which are highly soluble and the largest C reservoir on
Earth, compose around 20% of Earth’s land surface. Their dissolution affects
geomorphology, hydrology, water chemical composition, and C cycling. Controls on
and rates of dissolution are therefore critical processes in carbonate terrains, which are
investigated here in northern Florida springsheds and a bluehole on San Salvador
Island, Bahamas. Carbonate dissolution results from rainfall reacting with rocks at the
land surface and forcing river water into river banks and spring systems. During one
storm in north Florida, calcite dissolution from rainfall (~6 x 109mmol) was greater than
dissolution from river water penetrating river banks (~2.4 x 109mmol) and a spring (~3.8
x 108mmol). Dissolution from rainfall occurs more frequently than dissolution from river
water; however, river intrusion focuses dissolution in small areas. Dissolution rates
increase up to 17 orders of magnitude during spring reversals resulting in episodic
dissolution in spring systems. During spring reversals, undersaturated river water
dissolves calcite and undersaturation is enhanced by organic carbon remineralization.
Dissolution rates during a spring reversal are slowed more by mixing with groundwater
near equilibrium with calcite than by addition of calcium from dissolution. Both rainfall
11
and river water dissolution formed the hydrology and geomorphology of north Florida,
which includes extensive cave systems and surface rivers. In blueholes, tidal and diel
cycles control water-column chemistry through photosynthesis/respiration and water
column variations. In Inkwell bluehole, up to 0.8mmol/L of sulfuric acid is formed during
the day, decreasing water column pH by up to 0.31 pH units, and up to 0.4mmol/L of
carbonic acid is formed at night, reducing water column pH by as much as 0.18 units.
Calcite dissolution potential increases by 0.62mmol/L from sulfuric acid but only
0.25mmol/L from carbonic acid. Since sulfuric acid dissolution provides CO2 while
carbonic acid dissolution removes CO2 from the atmosphere, the greater dissolution
from sulfuric over carbonic acid produces a net source of carbon to the atmosphere.
These results show that carbonate dissolution’s impact on landscapes, regional
hydrology, and global carbon cycle depends on causes, rates, and distribution of
dissolution, which are variable across carbonate landscapes.
12
CHAPTER 1 INTRODUCTORY REMARKS
Carbon is an integral building block of life for all flora and fauna and is stored in
in three distinct natural reserves: the atmosphere, the lithosphere, and the hydrosphere.
Shifts from one reserve to another can impact water resources, geomorphology, and
Earth’s climate. Transitions between the reserves are constantly occurring and have the
potential to impact life on Earth, but these transitions remain poorly understood in many
settings.
There is ~7 x 107 Pg C stored in carbonate rocks around the world (Martin et al.,
2013), which represents the largest reserve on Earth. This reserve fluctuates over time,
gaining during carbonate precipitation and losing during carbonate dissolution.
Carbonate precipitation primarily occurs in the ocean, but dissolution can occur
anywhere there is carbonate and fluid undersaturated with respect to carbonate
minerals. We therefore focus on carbonate dissolution in this work.
The total volume of carbonate that will dissolve is dependent on the duration of
carbonate dissolution and the rate at which the carbonate is dissolving, since natural,
flowing fresh waters frequently do not reach complete equilibrium with respect to
carbonate minerals. Carbonate dissolution rates are controlled by the undersaturation of
the water and the ability of water to transport reaction byproducts away from the
reaction site. Dissolution rates are not linear across a range of undersaturations
(Dreybrodt, 1990; Dreybrodt, W., 1998) Rates slow rapidly when ~30% saturation is
reached (Kaufmann and Dreybrodt, 2007) and again somewhere between 60% and
85% saturation depending on experiment construction (Svensson and Dreybrodt, 1992;
White, 2002). Another factor affecting the saturation of water with respect to a
13
carbonate mineral is fluid flow in the system. If flow is sufficient to remove dissolved
ions from the reaction site, dissolution rates will be determined by the rate of CO2
conversion to carbonic acid, in most systems. If flow does not remove ions, waters
immediately next to the reaction site will become more saturated and dissolution will
slow once ion removal is dependent on diffusion rather than advection (Liu and
Dreybrodt, 1997).
The total volume of a carbonate mineral (e.g. calcite) a given amount of water
can dissolve is also dependent on the undersaturation of the water. Waters at complete
equilibrium with respect to calcite have a saturation index (SI) equal to zero and cannot
dissolve any more material. This saturation index can be lowered if the water reacts to
form acid or if the water mixes with a second water with different chemistry. Addition of
new ions to the solution can allow further dissolution as a consequence of the common
ion effect. In natural systems, fresh waters seldom reach complete equilibrium with
respect to calcite because dissolution rates slow as the water approaches equilibrium
with respect to calcite.
Natural controls on the undersaturation of water with respect to a given
carbonate mineral usually include the quantity and type of acids produced and how
much of a mineral the water has already dissolved. Carbonate dissolution is frequently
driven by carbonic acid, which is formed when rainfall reacts with CO2 produced by the
remineralization of organic carbon, atmospheric CO2, and/or soil CO2 (Eq. 1-1).
Carbonic acid reacts with the basic carbonate minerals, in this case limestone, and a
Ca2+ ion and two bicarbonates are released (Eq. 1-2). Dissolution can also be driven by
sulfuric acid, which is formed when H2S is oxidized (Eq. 1-3). This process frequently
14
occurs near the fresh water-salt water interface, where O2 and S2- are both present.
During sulfuric acid dissolution, Ca2+ and CO2 are produced along with water and
sulfate (Eq. 1-4).
𝐶𝑂2 + 𝐻2𝑂 ↔ 𝐻2𝐶𝑂3 (1-1)
𝐻2𝐶𝑂3 + 𝐶𝑎𝐶𝑂3 ↔ 𝐶𝑎2+ + 2𝐻𝐶𝑂3− (1-2)
𝐻2𝑆 + 2𝑂2 ↔ 𝐻2𝑆𝑂4 (1-3)
𝐻2𝑆𝑂4 + 𝐶𝑎𝐶𝑂3 ↔ 𝐶𝑎2+ + 𝐶𝑂2 + 𝐻2𝑂 + 𝑆𝑂42− (1-4)
Each acid increases the amount of carbonate mineral (e.g. calcite) that water can
dissolve, but when the water dissolves calcite, the water comes closer to saturation with
respect to calcite. The total volume of carbonate a water can dissolve (SI = 0) is easily
determined by basic geochemical modeling of the ions and properties (e.g. temperature,
pH, etc.) of the water, but when ion concentrations and water properties change in
natural settings because of dissolution, organic matter remineralization, or mixing with a
second water source, modeling the dissolution capability of a given water becomes
much more difficult. In some surface water-groundwater interactions, carbonate
dissolution volumes and rates have yet to be estimated accurately.
Carbonate dissolution rates and volumes are important to understand and the
removal of these carbonate minerals also has implications. Dissolution begins when
carbonate platforms are exposed by uplift or falling sea levels. Carbonic acid is formed
as rainfall equilibrates with CO2 in the atmosphere and gains further CO2 from soil
microbial respiration. This acidic water dissolves soluble rock at the land surface and
may be channeled along geologic planes of weakness (joints or fractures) or flow paths
that become preferred by capturing increasing volumes of rainfall (Hanna and Rajaram,
15
1998). The rainfall also picks up organic carbon from the soil. When rainwater
penetrates the platform down to the water table, the organic carbon is remineralized and
more CO2 is produced. Over time, preferential flow paths widen and deliver more
organic-carbon-rich water to the water table, where enlarged voids are created (Florea
et al. 2007, Gulley et al. 2013). These flow paths continue to transport water more
rapidly than the surrounding matrix and are enlarged by the higher flow rate. Eventually,
these voids become major conduits, which make up the traversable cave and spring
systems seen today. These conduits transport most of the subsurface flow in the Upper
Floridan aquifer hydrologic system.
Some conduits in north Florida have surface expressions as springs, which
discharge to nearby rivers. When rivers flood, river water can be forced into the aquifer
through river banks, and the river water can also reverse the flow direction of springs,
forcing river water into the spring that normally discharges groundwater to the river.
The river water is undersaturated with respect to calcite and dissolves the matrix rock,
but the extent of dissolution is not fully understood because of variations in natural
controls on dissolution that govern dissolution rates and volumes.
After terrestrial carbonate is dissolved, the dissolution byproducts enter either the
hydrosphere or atmosphere. To understand the impact of this transition from one
sphere to another, we consider dissolution/weathering of carbonate minerals on a global
scale. The two major types of weathering that occur on the planet are silicate and
carbonate weathering. Silicates are more plentiful than carbonates and weathering
silicates acts as a sink for atmospheric C (Brady, 1991). Though silicate weathering
16
takes longer than carbonate weathering, silicate weathering is frequently considered the
only weathering to impact the global C cycle:
𝐶𝑂2 + 𝐶𝑎𝑆𝑖𝑂3 ↔ 𝐶𝑎𝐶𝑂3 + 𝑆𝑖𝑂2 (1-5)
Recent research showed that that carbonate weathering can impact the global C
cycle (Liu et al. 2011; Torres et al. 2014), but even as a subset of carbonate weathering,
some believe that there is no net flux of C into or out of the atmosphere when
dissolution is driven by carbonic acid (Berner et al. 1983). This belief stems from
carbonic acid dissolution reactions (Eq. 1-1 and 1-2), which show that for every C that is
sequestered from atmospheric CO2, another C is released as bicarbonate. However,
studies have shown carbonate dissolution to potentially affect the global carbon cycle
over a few hundred years (Liu et al. 2011). Liu et al. (2011) proposed that dissolved
bicarbonate was taken up from streams by plants, incorporated by the plants, washed
out to sea, and buried, thereby sequestering the C and leading to a net carbon sink in
the global C cycle.
The global C cycle can also be impacted by carbonate dissolution driven by
sulfuric acid, which results in the release of CO2 to the atmosphere, making it a net
source of C to the atmosphere (Torres et al. 2014). Therefore, carbonate dissolution
can act as a sink or source of C to the atmosphere. These sinks and sources are
important because CO2 is considered a greenhouse gas that is linked to warming and
cooling phases of Earth’s history.
In addition to comprising the largest reserve of C on Earth, carbonate rocks also
represent ~20% of the Earth’s land surface (Ford & Williams 2007). Measures of
carbonate dissolution and associated C fluctuations in the various reserves are critical
17
to understanding the global C cycle budget. This research addresses carbonate
dissolution rates and quantities, as well as the resultant fluxes of C from this dissolution.
This research was conducted in north Florida and in San Salvador, The Bahamas,
enabling study of carbonate dissolution in both sub-tropical and tropical climates and in
fresh-water and brackish-water systems. We aim to better understand natural controls
on undersaturation, changes in aqueous chemistry through time, and the resulting
impacts of carbonate dissolution on the different carbon reserves.
Chapter 2 addresses carbonate dissolution rates in Peacock and Madison Blue
Spring, Florida, during four spring reversals that occurred from 2009 to 2012.
Dissolution rates declined following the start of the reversal, despite continued
production of CO2 from organic carbon remineralization. Dissolution rates of intruding
river water were slowed primarily by mixing with matrix water that was nearly saturated
with respect to calcite and secondarily by Ca2+ concentrations generated by river water
dissolution of calcite. Conduit expansion is primarily driven by dissolution that occurs
during spring reversals.
Chapter 3 re-examines one of the spring reversals studied in Chapter 2, which
occurred at Madison Blue Spring in 2012. This work estimated total dissolution that
occurred during the spring reversal, along the river, and across the drainage basin.
River water drives dissolution by triggering a spring reversal and penetrating the river
banks to reach and react with the rock matrix, but rainfall drives dissolution across the
drainage basin by filtering through the soil and reacting with the rock matrix. These
dissolution estimates were compared to determine which process was most responsible
for shaping the landscape seen today. This work used time series geochemical data
18
and hydrologic modeling to generate the first quantitative estimates of dissolution that
occurred during a spring reversal. Overall, rainfall dissolved more calcite than the spring
reversal or river bank penetration, but rainfall dissolution was spread over the drainage
basin whereas the river-water dissolution was spatially concentrated. These dissolution
patterns likely result in the current geomorphology and hydrology seen today in north
Florida. If denudation rates were faster, cave systems would be exposed before they
developed kilometers of subterranean passages, and if river-water dissolution were
greater, surface rivers would cease to exist.
Chapter 4 studies biogeochemical and tidal processes that affect carbonate
dissolution in a bluehole on San Salvador, The Bahamas. This work tracked aqueous
geochemistry changes though time and tidal cycles to determine which factors control
calcite saturation in the water column. We also investigated the respective roles of
carbonic and sulfuric acid in carbonate dissolution. Carbonic acid was found to primarily
form during the night when plants respired CO2, and sulfuric acid formed primarily
during the day when photosynthesis produced oxygen in the water column, which
reacted with H2S. The decreases in pH associated with each acid and time of day were
modeled to estimate potential carbonate dissolution. Sulfuric acid was found to dissolve
more carbonate than carbonic acid, and this bluehole study could potentially serve as
an example of processes that occur in the matrix across the carbonate platform.
These three studies all focused on carbonate dissolution, which has an important
role in regional hydrology, local geomorphology, and global carbon cycling. A better
understanding of the natural controls on dissolution rates and volumes through time is
19
required to predict future impacts of carbonate dissolution on water resources,
landscape evolution, and atmospheric chemistry.
20
CHAPTER 2 TEMPORAL VARIATIONS IN CALCITE DISSOLTUION RATES DURING FLOODING
OF KARST SPRINGS
2.1 Introduction
Dissolution is the defining feature of carbonate bedrock terrains, which dissolve
when they come into contact with water that is undersaturated with respect to calcite.
Dissolution increases permeability, thereby forming productive aquifers that provide
potable water to approximately 20% of the world’s population (Ford and Williams, 2007).
Dissolution commonly results from the presence of carbonic acid, formed by the
hydration of dissolved CO2:
𝐶𝑂2 + 𝐻2𝑂 ↔ 𝐻2𝐶𝑂3 (2-1)
𝐻2𝐶𝑂3 + 𝐶𝑎𝐶𝑂3 ↔ 𝐶𝑎2+ + 2𝐻𝐶𝑂3−
(2-2)
Although other acids can dissolve carbonate minerals, for example sulfuric acid
during the oxidation of dissolved sulfide (Botrell et al., 1991; Hercod et al., 1998;
Johnson and Hallberg, 2005; Spence and Telmer, 2005), reaction 2-2 represents the
most common dissolution mechanism for fresh water in the near surface (Palmer, 1991;
White, 1988; Dreybrodt and Gabrovsek, 2002). Dissolution can be a time-varying
process that depends on environmental conditions that control the composition of water,
the saturation state with respect to bedrock minerals, and rate of dissolution. Although
dissolution rates have been measured in laboratory experiments (Plummer et al., 1978;
Buhmann and Dreybrodt, 1985a, b) and time variations in the saturation states of water
in karst aquifers have been measured in natural systems (Shuster and White, 1971;
Jacobson and Langmuir, 1974), little is known about temporal variations in dissolution
rates of natural karst aquifers.
21
Several experimental approaches have been used to quantify calcite dissolution
rates (Table 2-1). One early approach was based on the summation of reaction rates for
each step of the calcite dissolution reaction, including CO2 dissolution and hydration of
CO2 to carbonic acid (eq. 2-1), and subsequent dissolution of carbonate minerals
(reaction 2-2; Plummer et al., 1978). This approach uses temperature-dependent
laboratory-derived reaction time constants and activities of H+, H2CO3, H2O, Ca2+, and
HCO3- to estimate dissolution rates across a range of pH and pCO2 values. Additional
experiments have been conducted in open conditions at constant pCO2 values similar to
Earth’s atmosphere (~0.005 atm) and under closed conditions, with an initial pCO2
range of 0.01-0.1 atm, similar to what might be found in soils, to assess the role of pCO2
in calcite dissolution (Buhmann and Dreybrodt, 1985a; b). In both open and closed
systems, dissolution rates were found to depend on Ca2+ and CO2 concentrations,
temperature, and hydrodynamics of the system (Buhmann and Dreybrodt, 1985a;b)
(Table 2-1). In more recent studies, atomic force microscopy has been used to track
dissolution on a microscopic scale at atmospheric and lower CO2 concentrations (Dove
and Platt, 1996; Shiraki et al., 2000) (Table 2-1).
Most studies of dissolution rates in natural systems are commonly reported as
long-term averages of denudation rates (Table 2-1), which represent the average rate of
land surface lowering (Opdyke et al., 1984; Jennings, 1985; Adams et al., 2010). Rates
of 0.015 to 0.040 mm/yr were found by measuring the height of pedestals formed by
dissolution surrounding glacial erratics that armor soluble rocks (Jennings, 1985).
Denudation rates of up to 0.03 mm/yr (Opdyke et al., 1984) and 0.09 mm/yr (Pitty,
1968) were estimated from concentrations of dissolved ions in rivers and springs in
22
Florida and the United Kingdom, respectively, assuming dissolution is the sole control
on their concentrations (Table 2-1). Adams et al. (2010) combined modeling of the
isostatic rebound of northern Florida, variations in sea level, and a relationship between
rainfall and dissolution to estimate denudation rates in Florida of around 0.09 mm/yr
over the past 2 million years, focusing on the same region studied by Opdyke et al.
(1984) (Table 2-1). Adams et al. (2010) estimated rates that were about 3.5 times
faster than those found by Opdyke et al. (1984), assuming that uplift was caused solely
by isostatic rebound.
Dissolution rates that occur within active hydrological systems, including rivers
and caves, would be expected to be much faster than whole-landscape denudation
rates because CO2 fluxes are concentrated in these zones (Covington et al., 2015).
Maintaining undersaturation requires water flow, which delivers undersaturated water to
reaction faces and removes reaction products. As undersaturation changes through
time, dissolution rates should also change. Time series measurements of aqueous
geochemistry in these zones, as reported here, could thus provide information on time
variation of dissolution rates, information that is not available from landscape
denudation studies. Because flow rates increase and saturation states decrease most
during floods, these events should dominate dissolution in karst aquifers. Floods may
be particularly important, as they introduce river water into aquifers when river
elevations rise above the hydraulic head of springs, causing flow to reverse, thereby
flooding the aquifers (Gèze, 1987; Albéric, 1998; Gulley et al., 2011),
Changes in flow direction at springs and within karst conduits dictate that
estimates of dissolution magnitude must consider time-varying dissolution rates. Little is
23
known of the magnitude of changes in dissolution rates between flood and baseflow.
Even less is known about the specific processes that cause dissolution rates to change,
which include calcite dissolution, mixing between intruded water and groundwater
during recession, and reactions such as DOC remineralization. Consequently, in this
paper we: (1) calculate rates and magnitudes of calcite dissolution as river water
intrudes into the upper Floridan aquifer using its chemical composition and two
laboratory-based models with differing structures and assumptions, and (2) evaluate
potential controls on changing dissolution rates. Our calculations of the magnitude of
dissolution refine previous estimates made by Gulley et al. (2011) for one intrusion
event, and include estimates of dissolution rates and magnitudes of three additional
intrusion events characterized by a range of magnitudes.
2.2 Study Sites and Methods
2.2.1 Study Sites
The two spring systems in this study, Madison Blue and Peacock Springs, are
located in north-central Florida (Fig. 2-1). Madison Blue Spring discharges to the
Withlacoochee River ~20 km upstream of its confluence with the Suwannee River.
Madison Blue Spring is located near the Cody Scarp, which is a regional geomorphic
feature that marks the erosional edge of the Miocene Hawthorn Group (Fig. 2-1A). The
Hawthorn Group rocks are predominately low-permeability siliciclastic sands and
claystones that confine the Upper Floridan aquifer to the north and east of both spring
systems. Peacock Springs is located on the Suwannee River ~55 km downstream of
the confluence with the Withlacoochee River. The Withlacoochee and Suwannee
Rivers are both tannic and primarily receive runoff from wetlands, agricultural fields, and
forested land. The low permeability of the Hawthorn Group can produce large volumes
24
of surface runoff that cause common floods on the two rivers and intrusion of river water
into the springs (Gully et al., 2011; Brown et al., 2014).
Both Madison Blue and Peacock springs have extensive mapped conduit
systems and exploration is on-going. Conduits for both spring systems occur in the
eogenetic (Vacher and Mylroie 2002) Upper Floridan aquifer, which has approximately
30% primary porosity within the matrix rocks (Budd and Vacher, 2004). Madison Blue
Spring is a first magnitude spring (> 2.3 m3/sec; Meinzer, 1927), discharging up to 6.3
m3/sec at velocities up to 0.90 m/s from >7 km of mapped and additional unmapped
conduits. Peacock Springs is not a true spring with perennial discharge, but instead a
group of karst windows (including sampling sites Peacock 1 and Orange Grove) (Fig. 2-
1B) linked by mapped conduits. Mapped conduit lengths are 12.6 km and exploration is
continuing. At the closest approach, the cave is within two kilometers of the Suwannee
River.
Both springs receive inflow from matrix porosity during baseflow conditions and
neither spring is linked to sinking streams. Both springs have water with similar
chemical compositions during baseflow that reflects equilibration with calcite. River
water intrudes both springs as stage increases above the elevation of the potentiometric
surface at the spring vent. At the Madison Blue Spring, intrusions occur at various river
elevations depending on antecedent groundwater heads. At Peacock Springs, intrusion
of the primary karst window starts when the river stage reaches ~8 m above sea level
(masl) to top a sill separating the karst windows from the river. Which karst windows
receive river water from overland flow during flooding depends on the magnitude of the
25
flood, with the Orange Grove site requiring larger flood events to receive water than
does the Peacock 1 site.
2.2.2 Methods
2.2.2.1 Field methods and sample analyses
Daily average river stages during the floods were obtained from two US
Geological Survey (USGS) gauging stations (http://waterwatch.usgs.gov/?m=real&r=fl).
These stations include Blue Spring Station (USGS Gauge Station 02319302) at
Madison Blue Spring and Luraville Bridge Station (USGS Gauge Station 02320000)
near Peacock Springs. These stations are the nearest river stage monitoring points to
the cave systems.
Sensors were placed in the rivers, springs, and conduits to record water
characteristics. In Situ Multi-Parameter Series TROLL 9500s were placed inside both
springs, about 30 m upstream of the spring vent. These sensors recorded specific
conductance and temperature at 30-minute intervals and were recalibrated
approximately monthly during the study. Schlumberger conductivity, temperature, and
depth (CTD) Diver loggers were placed in the Suwannee and Withlacoochee Rivers
upstream of Peacock and Madison Blue Spring systems, respectively, as well as at
various points in the cave systems. CTDs logged approximately every 30 minutes and
were calibrated when the data were downloaded, approximately every six months.
Variations in specific conductance and temperature in river and cave waters were used
to track the timing and extent of intrusion events.
Water samples were collected from rivers, spring vents, and karst windows
during four high-flow events and their subsequent recessions. These events raised
river elevations enough to intrude river water into the spring vents, but not all stages
26
were sufficient to overtop their banks and thus were not true floods. For simplicity,
however, these events will be referred to as floods. Sampling typically began a few
days after the start of intrusion. At Peacock Springs, six samples were collected at the
Orange Grove karst window and from the Suwannee River at the Luraville gauging
station between 16 April and 14 July 2009 (reported in Gulley et al., 2011) and seven
samples were collected from the Peacock 1 karst window and from the Suwannee River
at the Luraville gauging station between 3 February and 1 April 2010. At Madison Blue
Spring, seven samples were collected between 6 April and 9 May 2011 and 17 samples
were collected between 5 March and 15 May 2012 from the spring vent and
Withlacoochee River. Each sampling event is referred to here by the year in which
sampling took place (e.g., 2009 flood, 2010 flood, etc.).
Samples were collected using a peristaltic pump connected to flexible PVC
tubing extended with rigid PVC pipe from the edge of the water body (spring vent, karst
window, or river). Water was pumped into a flow-through cell that held a sonde
connected to a calibrated YSI 556MPS instrument that measured pH, dissolved oxygen
(DO), and specific conductance (SpC). Water was pumped over the sonde at low flow
rates for at least eight minutes until all values stabilized. Filtered water samples were
collected in acid-washed, 20- mL plastic screw-top bottles and preserved with trace-
metal-grade nitric acid to pH < 2 for subsequent analyses of major cation concentrations
(Na+, K+, Mg2+, and Ca2+). Filtered water samples were collected unpreserved in new,
but not acid-washed, 20- mL plastic screw-top bottles to measure major anion
concentrations (Cl-, SO42-). Dissolved organic carbon (DOC) samples were collected in
pre-rinsed, 40- mL ashed amber glass bottles and preserved with HCl. Dissolved
27
inorganic carbon (DIC) samples were collected in 20-mL French square glass bottles
and treated with three drops of saturated HgCl2 to prevent microbial activity. All samples
were kept on ice in the field and refrigerated after returning to the lab.
Dissolved inorganic carbon concentrations were measured by acidifying water
samples using an AutoMate Prep Device plumbed to a UIC (Coulometrics) 5011 carbon
coulometer, which measured the evolved CO2. The method was standardized with
known quantities of dissolved KHCO3 and generated data accuracy better than 1% on
all sample measurement runs. Dissolved organic carbon concentrations were measured
with a Shimadzu TOC-5000A total organic carbon analyzer by sparging samples for 2
minutes with C-free air to remove inorganic C. After high temperature combustion of
the organic carbon (OC), CO2 was measured through infrared analysis. The coefficient
of variance was <5% for replicate injections of each sample, and values reported here
are means of all DOC sample injections for individual samples. Cation and anion
concentrations were measured with an automated Dionex DX500 Ion Chromatograph.
Of the 74 samples collected in this study, 69 had a charge balance error < 10% and all
errors were positive. The five samples with charge balance errors > 10% (also positive)
were collected near the peak of floods, resulting in low ion concentrations, and had
DOC concentrations in excess of 10 mg/L. DOC concentrations exceeding 10 mg/L
contribute an unquantified negative charge to the system waters (Cantrell et al., 1990,
Hemond, 1990) affecting charge balance.
2.2.2.2 Estimates of mixing of river water and groundwater
The relative fractions of river water and groundwater in conduits were estimated
through each flood recession based on two-end-member mixing of Cl concentrations of
intruding river water and ground water (Brown et al., 2014; Brown et al. in prep). The Cl
28
concentrations were estimated to be 0.25 mM ± 3% at Madison Blue and 0.20 mM ± 3%
at Peacock for the intruding river water end-member, and 0.16 mM ± 3% at Madison
Blue and 0.17 mM ±3 % at Peacock for the pre-intrusion water end-member. This model
assumes that Cl is conservative in this system, which is likely because no Cl-bearing
minerals are known from the region. Cl concentrations vary through time when spring
water is completely displaced by intruding river water in the conduits, limiting the
accuracy of mixing model estimates at the beginning of the recession (Brown et al.,
2014).
2.2.2.3 Dissolution rate estimates
We focused our geochemical modeling on carbonate dissolution through time
using two independent rate models and coefficients. One model was developed by
Plummer et al. (1978, herein referred to as the PWP model). The PWP model
estimates the rate, R, of the overall reaction mechanism, based on empirically derived
rates for each step in the carbonate dissolution reaction, according to:
𝑅 = 𝑘1𝑎𝐻+ + 𝑘2𝑎𝐻2𝐶𝑂3+ 𝑘3𝑎𝐻2𝑂 + 𝑘4𝑎𝐶𝑎2+𝑎𝐻𝐶𝑂3
− (2-3)
where k represents a temperature-dependent reaction rate and 𝑎 is the activity of
individual reaction species. Each value of k is calculated from dissolution
measurements of Icelandic Spar under conditions of pCO2 ranging from 0.0 to 1.0 atm
and temperatures between 5° and 60° C (Plummer et al., 1978). The first term is mass-
transfer controlled and thus depends on flow rate, but the second and third terms are
controlled by reaction rate. Therefore, the total dissolution rate is only partly controlled
by flow regime.
29
The second model is modified from Svensson and Dreybrodt (1992; herein
referred to as SD model). This model uses ratios of measured Ca2+ concentrations and
estimates of Ca2+ concentrations of water that would be at equilibrium with calcite
(herein referred to as “equilibrium Ca2+ concentrations”) to estimate R according to:
𝑅 = 𝛼(1 − 𝐶/𝐶𝑠)𝑛 (2-4)
where C is the measured Ca2+ concentration and Cs is the equilibrium Ca2+
concentration, n is the empirical reaction order (unitless), α is the laboratory-derived
dissolution rate (mmol cm−2 s−1). The equilibrium concentration of the water with
respect to calcite was calculated using the phreeqc.dat database in PHREEQc
(Parkhurst and Appelo, 1999) and all measured solute concentrations. The α values
from Svensson and Dreybrodt (1992) were derived from dissolution experiments
conducted in an environment at 20° C with pCO2 at 5 x 10-3 atm, and include a range of
Ca2+ concentrations that gives C < xCs, with x ≈ 0.8. Both α and n values vary with the
saturation state of the water. When x > 0.6, the empirical reaction order (n) is 3–4
(Svensson and Dreybrodt, 1992). For values of x < 0.6, n ≈ 1.5−2.3. For x > 0.3, α ≈ 1.6
to 2.2 x 10−7 mmol cm−2 s−1. For x < 0.3, α ≈ 3 x 10−6 (Svensson and Dreybrodt, 1992;
Kaufmann and Dreybrodt, 2007). The n and α values used in this study were the
averages of the range of values when not explicitly stated. Averaging the range of
values appears appropriate based on a sensitivity analysis that indicates variations in n
and α varied rates by ~70% over the full range of compositions of flood waters, but only
by around 30% when most dissolution occurs near the start of the floods.
Model equations 2-3 and 2-4 were used to estimate dissolution rates for both
flood and baseflow samples with units of mass per area per unit time (mmol/cm2/day).
30
The amount of dissolution for each sample was estimated by multiplying that sample
dissolution rate by the time interval between sampling events with a right Riemann sum
extending to the date of the measurement. Dissolution for each flood was calculated by
summing dissolution amounts from the initial sample to the return to baseflow. The
flood dissolution amounts are considered minima because of the lack of samples during
the first few days of each flood and the use of a right Riemann sum, which should
slightly underestimate the amounts.
2.2.2.4 Impacts of mixing/dissolution Ca2+ additions and DOC remineralization on carbonate dissolution
Dissolution rates in natural systems slow when Ca2+ concentrations increase as
calcite dissolves and Ca2+-rich water mixes with Ca2+-poor water. We examined
whether dissolution or mixing slows dissolution more by using two data sets: (1)
measured sample ion concentrations and (2) ion concentrations estimated from
conservative mixing models. The first is comprised of measured ion concentrations of
samples collected during flood recession described in section 2.2.1. The mixed
composition of waters is determined from a weighted average of fractions of flooded
river water and pre-intrusion groundwater ion concentrations described in section 2.2.2.
These two data sets will be referred to as “measured model” and “mixed model” in this
paper. The models are calculated only for the 2010 and 2012 events because these
events experienced complete displacement of conduit waters, represent both sample
locations, and were sampled at sufficiently high resolution. The measured model
represents Ca2+ concentrations that result from both mixing and in situ calcite
dissolution, whereas the mixed model represents Ca2+ concentrations that result solely
from mixing, excluding in situ calcite dissolution. We assume the differences between
31
the measured and mixed models represent the magnitude of in situ dissolution.
Because both the measured and mixed model show water remained undersaturated
during the recession, the remaining potential dissolution capacity of the water to
dissolve calcite was estimated by using PHREEQc to react the measured model and
mixed model water compositions to a SIcal = 0. These solutions will be referred to as
“measured SI 0” and “mixed SI 0.” If the mixed model predicts more potential dissolution
than the measured model, we assume the extra potential dissolution results from in situ
remineralization of OC.
2.3 Results
Temperature and water compositions, as reflected in the SpC, changed
systematically throughout each intrusion event regardless of its size, duration, or
season (Fig. 2-2). Generally, SpC decreased more in large than small floods and
temperature decreased more during winter than summer floods. These changes in SpC
and T correspond with changes in the Ca2+ concentrations and SIcal values. The SIcal
values were low at the start of intrusion and decreased to vanishingly small values (6 x
10-18 mmol/cm2/day) at baseflow (Fig. 2-3). The return to near-equilibrium conditions
corresponds to slow dissolution rates (Fig. 2-4). Although the dissolution patterns are
generally the same in each event, the magnitudes of the floods and hydrologic
characteristics differ at each spring, which affect the dissolution rates and total calcite
dissolved. These differences are described below for each spring.
2.3.1 Peacock Springs
During the 2009 flood, the river stage increased by more than 8 m,
simultaneously with decreases in SpC of ~365 µS/cm (409 to 44 µS/cm) and
temperature of ~4° C (21.7 to 17.7° C) (Fig. 2-2). The 2010 flood was smaller, with an
32
increase in stage of 3.5 m and decreases in SpC of ~ 270 µS/cm (322 to 53 µS/cm) and
temperature of ~12° C (20.7 to 8.4° C). This flood occurred in winter, causing the large
decrease in temperature. Chloride mixing models and temperature data indicate water
in the conduits was completely displaced by intruding river water during both floods.
The 2009 flood was characterized by a minimum SIcal value of -6.43, whereas the
2010 flood had a minimum SIcal value of -5.27 (Fig. 2-3 and Table 2-2). The SIcal values
during the 2009 flood reflect dissolution rates that ranged from 0.15 to 0.20
mmol/cm2/day and total dissolution of 1.60 and 2.01 mmol/cm2 based on the SD and
PWP models, respectively (Table 2-2). Water in this event had SIcals of -0.5 and -1 for
most of the flood recession (Fig. 2-6A). During the 2010 flood, the maximum dissolution
rates were calculated to be 0.007 and 0.02 mmol/cm2/day (Fig. 2-4) with total
dissolutions of 0.10 mmol/cm2 and 0.75 mmol/cm2 (Fig. 2-5 and Table 2-2), as
estimated by the SD and PWP models, respectively. This flood had SIcal < -1 for more of
the recession than any other flood (Fig. 2-6B).
Both the mixed and measured models predict that Ca2+ concentrations increase
with time following both intrusions (Fig. 2-7). Following the 2010 flooding, measured
Ca2+ concentrations were ~59% greater than the mixed model estimated concentrations
(Fig. 2-7C). Measured Ca2+ concentrations gained ~11% more Ca2+ when equilibrated
to SI 0. Mixed Ca2+ concentrations gained ~64% more Ca2+ after being equilibrated
with calcite (Fig. 2-7A). During the 2010 flooding, the measured SI 0 data had ~ 8%
more Ca2+ than mixed SI 0 (Fig. 2-7E).
2.3.2 Madison Blue Spring
During the 2011 flood, the river stage increased by ~1 m simultaneously with
decreases in SpC of ~45 µS/cm (from 304 to 257 µS/cm) and temperature of ~0.5° C
33
(20.9 to 20.4° C) (Fig. 2-2). These small changes in both SpC and temperature values
indicate that only 26% of the conduit spring water was displaced by intruding river
water. The 2012 flood was larger, with an increase in stage of ~2.5 m, simultaneous
with decreases in SpC of ~250 µS/cm (from 345 to 86 µS/cm) and temperature of ~5.1°
C (20.6 to 15.5° C), indicating all conduit water was displaced (Fig. 2-2D).
The 2011 flood was characterized by a minimum SIcal value of only -1.19,
whereas the SIcal value decreased to a minimum of -4.73 in the 2012 flood (Fig. 2-3 and
Table 2-2). These differences in saturation states are reflected in low dissolution rates
during the 2011 flood of 0.0004 to 0.01mmol/cm2/day as calculated by the SD model
and PWP models, respectively (Table 2-2). Dissolution during floods ranged from
0.0004 to 0.37 mmol/cm2 based on the SD and PWP models, respectively. During the
entire flood, SIcal ranged between 0 and -1, with values between SIcals of 0 and -0.5 for
~95% of that time. During the 2012 flood, maximum dissolution rates at Madison Blue
Spring were 0.14 (Fig. 2-4) to 0.02 mmol/cm2 based on the SD and PWP models,
respectively. Dissolution during the flood ranged from 0.60 to 0.81 mmol/cm2 based on
the SD and PWP models, respectively. This flood had SIcal values between 0 and -1 for
approximately 90% of the time, and values varied between SIcals of -1 to -4 the rest of
the time (Fig. 2-6B).
Concentrations of Ca2+ increased with time following spring reversals for both the
mixing model and measured data sets (Fig. 2-7). Following the 2012 flooding,
measured Ca2+ concentrations were ~8% greater than mixed concentrations (Fig. 2-
7D), but gained ~8% when equilibrated to SI 0 (Fig. 2-7B). Mixed Ca2+ concentrations
gained ~ 12% more Ca2+ after being equilibrated with calcite (Fig. 2-7B). During the
34
2012 flooding, the measured SI 0 data had ~ 4% more Ca2+ than the mixed SI 0 (Fig. 2-
7F).
2.4 Discussion
The amount of calcite that dissolves as surface water intrudes karst aquifers
depends on the volume of intruding water, the residence time in the aquifer of intruded
water, its undersaturation with respect to calcite, and dissolution reaction rates. Both
the volume of intruding river water and the residence time in the aquifer depend on the
magnitude of difference in hydraulic head gradients and the length of time they are
oriented from the river to the aquifer (Gulley et al., 2011). This return to nearly
equilibrated water could result from mixing with near-calcite-saturated and low-DOC
groundwater, dissolution of calcite by the intruding water during the intrusion, less
production of CO2 by remineralization of DOC as energetically favored terminal electron
acceptors (e.g., O2) are consumed, or a combination of these factors. For the following
discussion, we used water compositions and changes in saturation state to estimate
reaction rates and magnitudes of dissolution during the flood.
2.4.1 Temporal Variations in Dissolution Rates
The four sampled intrusion events exhibited different maximum dissolution rates,
total dissolution (Table 2-2) and temporal variations in rate. Most dissolution occurs
early in the floods as dissolution rates decrease during recessions; more than 90% of
calcite dissolution occurred within the first 20% of all floods (Fig. 2-4). The return to
slow reaction rates during flood recession reflects water saturation states being near
equilibrium with calcite at the approach to baseflow. Variations in maximum rates result
from differences in the flood magnitudes, which correspond to the maximum amount of
undersaturation (Fig. 2-3). In addition to lower saturation states, large floods force more
35
river water into the spring system over a longer period of time than do smaller floods.
Large intrusion events also force more water into the rock matrix from the conduits
(Martin and Dean, 2001; Moore et al., 2010), thereby increasing the surface area with
which undersaturated water reacts.
2.4.2 Comparison of Dissolution Rate Models
Dissolution rates and magnitudes vary between floods, but within individual
floods, the rates depend on the model used to calculate them. The SD model (equation
2-4) estimated less dissolution than the PWP model (equation 2-3), except for
Suwannee River during the 2012 flood (Fig. 2-5). The SD model estimates are ~80% of
the PWP model estimates during the 2009 flood, ~14% of the PWP model estimates
during the 2010 flood, and ~0.12% of the PWP model estimates during the 2011 flood.
These differences result from differences in model behavior near equilibrium and at
different pCO2 values. The PWP model is appropriate for water that is far from
saturation with respect to calcite (<20% of the Ca2+ concentration when at SIcal = 0)
(Plummer et al., 1979; Buhmann and Dreybrodt, 1985), but rates may be overestimated
in waters near SI 0 with high ion concentrations (Svensson and Dreybrodt, 1992), which
may inhibit dissolution by retarding acids from reaching reaction sites. Consequently,
the SD model may better characterize dissolution than the PWP model in waters close
to equilibrium with calcite, which is the normal for most of the recession following the
intrusion and rapid shift toward equilibrium with respect to calcite (Fig. 2-4). The SD
model was developed using 5 x 10-3 atm of CO2 and the samples we measure have
pCO2 values that ranged between 0.0009 and 0.15 atm. The changing pCO2 should
also alter the Cs value in the SD model, therefore accounting, at least partially, for
differences in the modeled and measured samples. Because the PWP coefficients
36
were determined at pCO2 pressures up to 1 atm, results from this model may be more
accurate at the high pCO2 concentrations seen during some portions of the study.
The PWP model uses several different temperature-dependent rate constants
and the first term is mass-transfer controlled, whereas the second and third terms are
controlled by the reaction rate. This equation design accounts for both differences in
flow and reaction rates. In contrast, the SD model relies solely on the calcite saturation
state of water to determine reaction rates, and the exponent in the SD model (eq. 2-4)
creates abrupt changes in rates as saturation thresholds are crossed. Each model thus
predicts different amounts of total dissolution depending on the extent of
undersaturation experienced and length of time spent at different levels of
undersaturation (Fig. 2-6 B). In the case of a flood that does not result in highly
undersaturated conduit waters (e.g., the 2011 flood), the PWP model estimates more
dissolution than the SD model because of its assumption of linearity between
dissolution and saturation state even when water is near equilibrium with calcite. In
contrast, the SD model estimates reaction rates ~4 orders of magnitude slower than the
PWP model when water is between SIcal 0 and -1 (Fig.2- 6 A).
2.4.3 Saturation States and Dissolution Magnitude Through the Recession
The greatest undersaturation occurs at the beginning of intrusion events because
of CO2 produced by OC remineralization and lack of water contact with carbonates in
the river channel. Ground water near equilibrium with calcite mixes with the intruded
river water as hydraulic head gradient differences decrease and intrusion slows. Mixing
slows dissolution rates because the ground water is near equilibrium, but in situ
dissolution also diminishes the undersaturation and slows dissolution rates. The
following discussion estimates the relative importance of mixing, in situ dissolution, and
37
in situ organic carbon remineralization in controlling dissolution rates and magnitudes of
dissolution.
Both the mixed and measured models show trends toward equilibrium during the
2010 and 2012 floods (Fig. 2-7 A and B). The measured model Ca2+ concentrations are
always greater than mixed model Ca2+ concentrations, indicating that in situ dissolution
has released Ca2+ in excess of that derived from mixing. Subtracting the mixed Ca2+
concentrations from the measured Ca2+ concentrations yields the Ca2+ contributed from
dissolution This Ca2+ is ~59% and 8% of the mixed Ca2+ concentrations during the
2010 and 2012 floods, respectively. The greater Ca2+ contributed in 2010 and 2012
likely derives from the length of intrusion and differences in the hydrology of the springs.
Intruded river water stopped draining from Peacock Springs after the water table
dropped below 8 m above sea level and thus remained in the aquifer longer than at
Madison Blue Spring.
Because the mixed water samples contain less Ca2+ than the measured water
samples, they gain more total Ca2+ when equilibrated with calcite to SIcal = 0 than the
measured water samples. Even when equilibrating to SIcal = 0, the total Ca2+
concentration of the mixed SI 0 remains less than the measured SI 0. The difference
between these two estimates represents chemical reactions other than carbonate
dissolution that affect ability of water to dissolve calcite, most likely from the
remineralization of DOC. Subtracting the value of the mixed SI 0 from the measured SI
0 indicates that DOC remineralization adds ~8% and ~4% more Ca2+ in the measured
model SI 0 than the mixed model SI 0 during the Peacock 2010 flood and Madison Blue
2012 flood. The addition of CO2 through DOC remineralization continues to drive
38
undersaturation until the DOC is gone or the remaining fraction is completely
recalcitrant. This prolonged addition of CO2 may allow further dissolution in areas
where water remains trapped longer, such as Peacock Springs, than in areas that
discharge intruded waters quickly, such as Madison Blue Springs. The sill that prevents
Peacock Springs from reversing as frequently as Madison Blue Springs may have
contributed, in part, to Peacock Springs reaching a greater length than Madison Blue by
retaining river water longer in the system, thereby driving greater dissolution.
2.5 Conclusions
This study presents the first estimates of dissolution rates in karst aquifers
caused by changes in water chemistry during intrusions caused by flooding. Estimates
of rates based on two models with distinct assumptions and with data collected during
four floods indicate dissolution rates increase by up to 17 orders of magnitude during
floods compared to rates at baseflow, indicating that most dissolution in these systems
is episodic. The two models yielded different estimates of dissolution during floods.
Highest dissolution rates occurred during the first 20% of the flood, when more than
80% of the dissolution occurred. Dissolution rates are elevated at the start of intrusions
because of the undersaturated state of the intruding river water with respect to calcite,
which is enhanced by remineralization of DOC that intrudes with the floodwater.
Dissolution rates slow near the end of intrusions as the intruded river water begins to
discharge. Diffuse recharge of rainfall through the land surface, although also
undersaturated with respect to calcite, causes little dissolution of the conduits, which
expand episodically during intrusion events. At the beginning of a flood, dissolution is
almost the exclusive source of Ca2+ added to intruding river water, but when the flood
39
recession begins, simple mixing adds Ca2+ to conduit waters and is primarily
responsible for slowing dissolution rates.
40
Table 2-1. Karst dissolution rates.
Analysis Type Method Rate (mm/yr) Authors
Theoretical (Laboratory
Based)
Peak Rates using linear Dissolution Rate
Equations (varying CO2 concentrations)
2.3 – 16.3a Plummer et al., 1978
Peak Rates from Dissolution Rate
Equations similar to this study (open system varying water film
thickness)
0.09 - 0.5 Buhmann and
Dreybrodt, 1985 a
Peak Rates from Dissolution Rate
Equations similar to this study (closed system
varying water film thickness)
0.3 -1.45 Buhmann and
Dreybrodt, 1985 b
Atomic Force Microscopy 8.54 x 10-8 - 8.54
x 10-4 Dove and Platt 1996
Atomic Force Microscopy 4.2 x 10-4 - 1.6 x
10-3 Shiraki et al., 1999
Observational (Field Based)
Measuring Post Glaciation Pedestals
0.015-0.040 Jennings 1985
Measured Ca2+ Concentrations in
Mountain Drainage Basins 0.075-0.083 Pitty 1968
Estimated Ca2+ Concentrations in Springs
0.03 Opdyke et al., 1984
Geomorphic estimations of denudation
0.09 Adams et al., 2010
Baseflow Conditions 1 x 10-16 This study
Flood Conditions 0.000019 – 0.08b This study aRates are taken from the greatest potential values from linear rate calculations and may not be representative of most natural systems. bRates are based solely on the SD equation and do not account for DOC remineralization (see text for explanation).
41
Table 2-2. DOC concentrations, SI values, and dissolution rates for the four sampled floods.
Location Year
Peak Intruding DOC mg C/L
Lowest SIcal Value
SD Maximum Dissolution Rate (mmol/cm2/day)
SD Total Dissolution during Flood (mmol/cm2)
PWP Maximum Dissolution Rate (mmol/cm2/day)
PWP Total Dissolution during Flood (mmol/cm2)
Peacock 2009 28.39 -6.43 0.15 1.60 0.20 2.01
Peacock 2010 24.3 -5.27 0.007 0.10 0.02 0.75
Madison 2011 2.07 -1.19 4.1x10-4 4.3X10-4 0.01 0.37
Madison 2012 19.11 -4.73 0.14 0.60 0.02 0.81
42
Figure 2-1. Maps of river and cave systems. A) Map of the Suwannee River Basin showing locations of Peacock and Madison Blue Springs cave systems and stage gauges on the Suwannee River. B) Map of Peacock Springs cave system. C) Map of Madison Blue Spring cave system in relation to the Withlacoochee River. Modified from Gulley et al. (2011).
43
Figure 2-2. Conductivity and temperature through time at spring vents for reversals: A) Peacock 2009, B) Peacock 2010, C) Madison Blue 2011, D) Madison Blue 2012. The y axes are fixed at the same range, but have different values, to emphasize differences in magnitudes between the events. Arrows at the top of graphs indicate sampling times. The sharp drop in temperature and specific conductivity marks the initial intrusion of river water into the system followed by a recession to base flow.
44
Figure 2-3. Concentrations of calcium and calcite saturation indices through time for A) Peacock 2009, B) Peacock 2010, C) Madison Blue 2011, and D) Madison Blue 2012. Concentrations of calcium are laboratory measured values of grab samples and saturation indices were calculated in PHREEQc.
45
Figure 2-4. Time variations in the river stage, dissolution rates for reversals, and cumulative dissolution at A) Peacock 2009, B) Peacock 2010, C) Madison Blue 2011, D) Madison Blue 2012. Estimated dissolution rates are shown for the spring vent (solid points) and the river adjacent to the springs (open points). Plotted rates are estimated based on the SD model only (see text for discussion). Cumulative dissolution is shown as a dashed black line. River stages are daily averages shown as a solid grey line. Sample points indicate dissolution rates at that time; dissolution likely started before the first samples were collected. Vertical black lines through a point indicate that the ρCO2 of the sample was larger than 0.005 atm (the atm at which the SD equation was tested). Cumulative dissolution incrementally sums the area under the curve plotted for daily dissolution rates through an event.
46
Figure 2-5. Total calcite dissolution as measured by Ca2+ for each event by the SD equation (black) and the PWP equation (Gray). The river value represents values at Withlacoochee River for Madison Blue Spring and Suwannee River for Peacock Spring. The letter P represents Peacock and MB represents Madison Blue Spring.
47
Figure 2-6. Predicted calcite dissolution values and SI range durations. A) Dissolution rates using the PWP and SD equations at a range of saturation indices with respect to calcite. B) Cumulative fraction of time that each flood spent in a given range of saturation indices with respect to calcite. Ranges cover saturation index 0 to -4 in 0.5 saturation index units each and all samples under -4 are labeled as “under 4.”
48
Figure 2-7. Measured and mixed Ca2+ concentrations and measured SI 0 and mixed SI 0 Ca2+ concentrations through time. A) Peacock 2010 and B) Madison Blue 2012. Estimates of Ca2+ added by carbonate dissolution from measured Ca2+ concentrations minus mixed Ca2+ concentrations through time at C) Peacock 2010 and D) Madison Blue 2012. Estimates of potential Ca2+ additions from organic carbon remineralization based on measured SI 0 Ca2+ concentrations minus mixed SI 0 concentrations through time at E) Peacock 2010 and F) Madison Blue 2012.
49
CHAPTER 3 RELATIVE AMOUNTS OF DISSOLUTION IN CARBONATE TERRAINS FROM RIVER
LOSSES AND DIRECT RAINFALL
3.1 Introduction
Landscape evolution is determined by uplift, physical and chemical weathering,
bedrock lithology, climate, soil type and thickness, and vegetation (Ford et al., 1988;
Hoorn et al, 2010; Huggett, 2007; Mann, 2002). Landscape evolution tends to be more
rapid in carbonate than ice-free siliciclastic landscapes because dissolution, rather than
physical erosion, provides the major control (Huggett, 2007). Carbonate dissolution
forms karst landscapes, which are characterized by caves, sinking streams, and dolines
(White, 1988; Ford and Williams, 2007). This chemical erosion is especially prevalent in
middle to low latitudes where rainfall and vegetation are plentiful. Dissolution is
primarily driven by carbonic acid, though other naturally occurring acids, such as sulfuric
acid, can also cause dissolution (Botrell et al., 1991; Hercod et al., 1998; Johnson and
Hallberg, 2005; Spence and Telmer, 2005). Carbonic acid forms as CO2 in the
atmosphere and soils dissolves in rainwater,
𝐶𝑂2 + 𝐻2𝑂 ↔ 𝐻2𝐶𝑂3 (3-1)
which then dissolves soluble bedrock. Where calcite dissolves, calcium and
bicarbonate concentrations are elevated in surface water and groundwater
𝐻2𝐶𝑂3 + 𝐶𝑎𝐶𝑂3 ↔ 𝐶𝑎2+ + 2𝐻𝐶𝑂3− (3-2)
These elevated ion concentrations are then transported through the hydrologic systems.
The hydrologic system is important in determining where dissolution occurs by
controlling the locations of contact between limestone and carbonic acid (Fig. 3-1).
50
Hydrology also controls the magnitude of dissolution by altering flow rates, residence
times and the extent that reaction products are flushed from the aquifer. Flow through
the subsurface may concentrate dissolution in areas to form caves, referred to as
conduits when water filled. Concentrated dissolution occurs at preferential flow paths
because of water piracy/flow capture (Szymczak and Ladd 2011) and at aquitards and
geologic structures, such as bedding planes or joints (Palmer, 1991). Concentrated
dissolution also occurs at the water table (Florea et al. 2007, Gulley et al. 2013). As
rivers flood, undersaturated water may penetrate river banks and enter the aquifer and
cause dissolution (Chen and Chen, 2003). Such penetrating flow can occur at large
spatial scales in karst systems when elevated river hydraulic heads reverse spring flow,
forcing large volumes of undersaturated water into the aquifer (Gèze, 1987; Albéric and
Lepiller, 1998; Gulley et al., 2011). During these events, limestone dissolution rates in
phreatic conduits can be up to 16 orders of magnitude faster than rates under baseflow
(Fig. 2-4), and these reactions are spatially constrained by the penetration depth of river
water into the rock matrix. Dissolution may also be distributed regionally across the
land surface as rainfall (Fig. 3-1C), which derives CO2 from the atmosphere and soils, is
undersaturated with respect to carbonate minerals (eq. 3-2).
Estimates of the magnitude of dissolution can be converted to rates at which the
land surface is lowered (i.e., denudation rates) by normalizing the dissolution
magnitudes to defined areas. Estimates of denudation use a variety of methods
including measuring armored pedestal heights above the surrounding land (Jennings,
1985), calculating dissolution required to produce measured spring and river Ca2+
concentrations (Pitty, 1968; Opdyke et al., 1984) and calculating dissolution rates
51
necessary to yield uplift (Adams et al., 2010). Dissolution-driven denudation was
compared with stream erosion and found to occur at approximately the same rate in the
tectonically active Appalachian karst region (White, 2009). Similar to Appalachian karst
(Granger et al., 2001), caves occur at several different depths below the land surface in
the Florida karst (Florea et al., 2007). Dissolution in north-central Florida is
hypothesized to have caused isostatic uplift equal to ~36 m during the Pleistocene and
Holocene, resulting in denudation rates of between 0.03 and 0.09 mm/yr (Opdyke et al.
1984; Adams et al., 2010). In some areas, rivers have down cut sufficiently to bisect
phreatic caves that were previously unconnected to surface flow (Gulley et al. 2013).
What remains unknown is the relative magnitude of regional denudation from rainfall
across the land surface versus concentrated subsurface dissolution, processes that
gave rise to the modern Florida landscape.
We examined one rainfall event (Tropical Storm Debby) that passed through
north-central Florida in 2012 and was sufficient to cause flooding and trigger a spring
reversal. We estimated the amount of dissolution caused by rainfall recharge across
the land surface, along with recharge volumes from the spring intrusion and bank
penetration, which allowed us to estimate the relative magnitudes of these three
dissolution mechanisms for the first time. By comparing these magnitudes, we were
able to assess how these processes have shaped the hydrology and geomorphology of
the region.
3.2 Study Sites and Methods
3.2.1 Study Sites
Located in north Florida, Madison Blue Spring discharges to the Withlacoochee
River ~17 km downstream of the Pinetta gauging station and ~ 15 km upstream of the
52
Lee gauging station (Fig. 3-2). The region receives an average of 1334 mm of annual
rainfall (NCDC 2015), with approximately half falling in summer during localized
thunderstorms and tropical storms. Madison Blue Spring is located near the Cody
Scarp, a regional geomorphic feature that marks the erosional edge of the Miocene
Hawthorn Group (Fig. 3-2A), which confines the Upper Floridan aquifer. The river reach
from the Pinetta gauging station to Madison Blue Spring flows across the Hawthorn
Group, where it is sufficiently thin to allow water to be lost to the Upper Floridan aquifer
from the river. The river reach from Madison Blue Spring to the Lee gauging station
flows across the unconfined Upper Floridan aquifer and is a gaining river. The
Withlacoochee River is tannic and sourced primarily from wetlands, agricultural fields,
and forested land runoff.
Madison Blue Spring discharges from >7 km of mapped conduit system;
exploration is on-going (Fig. 3-2B). Madison Blue Spring is a first magnitude spring (>
2.3 m3/sec; Meinzer, 1927), discharging up to 6.3 m3/sec at velocities up to 0.90 m/s
(SJRWMD). Conduits that source Madison Blue Spring occur in the eogenetic (Vacher
and Mylroie, 2002) Upper Floridan aquifer, which has approximately 30% primary
porosity within the matrix rocks (Budd and Vacher, 2004). Madison Blue Spring
contributes about 30% of the Withlacoochee discharge (Farrell and Upchurch 2004).
Water at Madison Blue Spring reverses flow when hydraulic head gradients drive flow
toward the spring, as river stage rises more rapidly than the groundwater hydraulic head
(Brown et al., 2015), which is a function of antecedent groundwater levels, recharge
from infiltration, and lateral flow.
53
3.2.2 Methods
3.2.2.1 Monitoring data and historical reversal estimates
Several sets of monitoring data were used, including discharge of the
Withlacoochee River, rainfall amounts, and the chemical composition of rainfall. Daily
average river stage and discharge during the flood were obtained from three US
Geological Survey (USGS) gauging stations along the Withlacoochee River, including
Pinetta (USGS 02319000), near Madison (USGS 02319300), and Lee (USGS
02319394). Daily rainfall totals were downloaded from the Live Oak weather station
(Location 170), which is part of the Florida Automated Weather Network (FAWN)
(http://fawn.ifas.ufl.edu/) and located ~40 km ESE of Madison Blue Spring. Daily
average chemical composition of rainfall was downloaded from the Quincy weather
station (NTN site: FL 14), which is part of the National Atmospheric Deposition Program
(http://nadp.sws.uiuc.edu/data/NTN/) and located ~130 km west of Madison Blue
Spring.
Historic stage gauge data at Pinetta were used to identify when spring reversals
may have occurred at Madison Blue Spring over an ~80-year period of record. The
Pinetta gauging station was selected because it was near the Madison Blue spring
system, and the gauging station at Madison Blue spring run only has records for the last
~14 years. Stage data were evaluated to find periods when characteristics were similar
to those during four known reversals (Table 2-2), including the one described here.
These characteristics include stage increases at a rate > 0.45 m/d for three consecutive
days, reaching a stage in excess of any stage in the previous two weeks, and a stage at
least 150% greater than the average stage at base flow during the previous year.
Baseflow was established for the year preceding the events by averaging low flow
54
stage. One year should represent antecedent baseflow conditions because springs in
the area have been shown to respond to extreme weather events (e.g., tropical storms)
in approximately 6-8 months (White 2005; Florea and Vacher 2006).
3.2.2.2 Field methods and sample analyses
An In Situ Multi-Parameter Series TROLL 9500recorded specific conductance
and temperature at 30-minute intervals approximately 30 meters upstream of the
Madison Blue Spring vent. This logger was removed, maintained, recalibrated, and
immediately replaced approximately monthly during the study. Schlumberger
conductivity, temperature, and depth (CTD) diver loggers were placed in the
Withlacoochee River upstream of Madison Blue Spring as well as at various points in
the cave system. The CTDs logged approximately every 30 minutes and were
calibrated when the data were downloaded, approximately every six months.
Water samples were collected from the spring vent and Withlacoochee River 17
times between 5 March and 15 May 2012 using a peristaltic pump connected to flexible
PVC tubing extended with rigid PVC pipe from the edge of the water body (spring vent,
karst window, or river). Water was pumped into a flow-through cell that held a sonde
connected to a calibrated YSI 556MPS instrument that measured pH, dissolved oxygen
(DO), and specific conductance (SpC). Water was pumped over the sonde for at least
eight minutes until all values stabilized. Water samples were filtered through a 0.45-µm
trace-metal-grade canister filter and collected in acid-washed 20- mL plastic screw-top
bottles and preserved with trace-metal-grade nitric acid to pH < 2 for major cation
concentrations (Na+, K+, Mg2+, and Ca2+). Samples for major anion concentrations (Cl-,
SO42-) were collected unpreserved in new, but not acid-washed, 20- mL plastic screw-
top bottles. DOC samples were collected in pre-rinsed, 40- mL ashed amber glass
55
bottles and preserved with HCl. DIC samples were collected in 20- mL French square
glass bottles and treated with three drops of saturated HgCl2 to prevent microbial
activity. All samples were kept on ice in the field and refrigerated after returning to the
lab.
Cation and anion concentrations were measured with an automated Dionex
DX500 Ion Chromatograph. Of the 34 sets of ion samples collected in this study, 33 had
a charge balance error < 10%, 29 had a charge balance error <5%, and all but three
sample sets had errors that were positive. The five samples with charge balance errors
> 5% were collected near the peak of floods, resulting in low ion concentrations, and
had DOC concentrations in excess of 10 mg/L. Dissolved organic carbon
concentrations exceeding 10 mg/L contribute an unquantified negative charge to the
system waters (Cantrell et al., 1990; Hemond, 1990) which results in charge balance
errors increasing and becoming more positive. Dissolved inorganic carbon
concentrations were measured by acidifying water samples using an AutoMate Prep
Device plumbed to a UIC (Coulometrics) 5011 carbon coulometer, which measured
evolved CO2. The method was standardized with known quantities of dissolved KHCO3
and generated data accuracy better than 1% on all runs. Dissolved organic carbon
concentrations were measured with a Shimadzu TOC-5000A total organic carbon
analyzer by sparging samples for 2 minutes with C-free air to remove inorganic C. After
high-temperature combustion of the organic carbon, CO2 was measured by infrared
analysis. The coefficient of variance was <5% for replicate injections of each sample,
and values reported here are means of all DOC sample injections for individual
56
samples. All analyses were completed in the Department of Geological Sciences at the
University of Florida.
3.2.2.3 Recharge and dissolution modeling
We estimated dissolution potential in the three sub-regions where dissolution
may occur during flood events (Fig. 3-1). These include dissolution as water intrudes
conduits, dissolution longitudinally in river banks, and dissolution across the drainage
basin driven by rainfall which diffusely recharges the aquifer. These dissolution
estimates were made by first estimating the volume of water that enters each of these
sub-regions and then using water chemistry data to estimate the amount of dissolution.
Estimates of dissolution from each sub-region were compared to evaluate which area
contributes the most to dissolution overall, thereby altering and developing the karst
landscape and its hydrogeologic characteristics.
Three different approaches were used to estimate the volume of water flowing
into Madison Blue Spring during the 2012 reversal. 1) The first approach used the
Madison Blue Spring gauging station (USGS 02319302), which is located in the spring
run and recorded negative flow during the flood. 2) The second method used a
hydrologic model (Spellman, 2012) that utilized shifts in the hydraulic heads of the cave
system, wells, and the river to determine the volume of river water intrusion during the
spring reversal. The model simulated flow based on hydraulic gradients and estimated
hydraulic conductivities in the cave system and surrounding rock matrix by using the
finite difference model software package MODFLOW with the CFP extension. 3) The
third approach used a geochemical mixing model (Brown et al., 2015), which employs
Cl- concentrations and assumes conservative two-end-member mixing to calculate the
fractions of river water and groundwater contained in the post-reversal discharge. The
57
river water fraction was multiplied by the total discharge volume based on discharge
records at Madison Blue gauging station to determine the river water discharge volume.
We recognize that the three methods employed to quantify volume are estimates and
rely on comparing these independently derived estimates with one another to find the
closest approximation of intruded river volume. We estimated the total dissolution that
occurred during the 2012 reversal using the Cl- mixing model to estimate the Ca2+
concentrations expected in discharge water that would result from simple mixing.
Measured concentrations were always in excess of the modeled concentrations and the
difference between the two is assumed to represent Ca2+ derived from calcite
dissolution. By multiplying the excess Ca2+ concentrations with the river intrusion
volumes, we calculated the total dissolution in Madison Blue Spring system during the
2012 spring reversal. These estimates are based on ion concentrations from grab
samples collected through time and therefore are subject to the ~5% error associated
some of these samples.
After the dissolution occurring during the spring reversal was calculated, we
calculated the intruded volumes necessary to determine how much dissolution occurred
along the studied river reach. To determine channel storage changes, LIDAR data
(SRWMD) were used to estimate the average channel volume per m around each
gauging station at various river stages. A stretch 1680 m long was used for averaging.
These entries created an index table with stages and volumes for the river reach.
Linear interpolation of the values in this table was used, in conjunction with daily stage
data, to estimate the channel water volume for the river reach each day. The volume
per meter from one day was subtracted from the volume per meter for the next day to
58
establish the normalized change in volume per day. These estimates are limited by
small scale changes in channel geomorphology which will raise or lower channel
capacity at a given stage. While these variations are likely small, they do introduce
error into channel storage estimates.
This change in volume per meter was used as a “channel storage correction” to
account for daily water storage changes between the upper and lower gauging stations.
The gauging station discharge at the downstream gauging station was subtracted from
the upstream gauging station. The “channel storage correction” was subtracted
(assuming losses from the river to be positive) from the difference in gauge station
discharges to calculate the gain or loss of river water to the aquifer in the river reach per
day. The daily values were plotted and the area under the resulting curves was
computed to determine the volume of river water entering the aquifer in each reach as a
result of the storm. The volumes of river water that entered the aquifer (L) were
multiplied by the dissolution estimate used for the spring reversal (mmol/L) to calculate
the dissolution associated with bank penetration. River water loss estimates are
dependent on discharge calculations at the individual gauging stations; discharge is
based on a rating curve utilizing river stage and may actually vary due to changes in
channel geomorphology during the storm, which will introduce error into the
calculations.
Dissolution resulting from rainfall across the land surface was evaluated for the
drainage basin by estimating soil moisture from evapotranspiration (ET) and rainfall
data from the Live Oak station and neglecting runoff, which is assumed to be negligible
in this karst landscape. When rainfall sufficiently exceeded ET rates, water in the soil
59
surpassed the moisture capacity, and recharge was recorded. For comparisons with
dissolution during spring reversals and bank infiltration, diffuse recharge was
considered only for the week preceding the spring reversal, 25 February to 3 March
2012. This week-long diffuse recharge value was multiplied by the area of the
Withlacoochee River drainage basin bound by the Pinetta Station on the north and the
Lee Station at the south. The drainage basin shapefiles used to determine the drainage
basin area were obtained from the Suwannee River Water Management District website
(http://www.srwmd.state.fl.us/index.aspx?NID=319). Maximum potential dissolution was
calculated by multiplying the basin-wide diffuse recharge (L) by the amount of calcite
that could be dissolved by intruding rain water (mmol/L), which was calculated using
rainfall chemistry, soil CO2 concentrations (see 3.4). These dissolution estimates were
later applied to the drainage basin using the yearly average rainfall to account for the
frequent nature of dissolution driven by rainfall in the study area.
Estimates of diffuse recharge use rainfall values and ET rates assumed to be
spread evenly across the entire drainage basin which is unlikely. The dissolutional
capability of rainwater reacting with soil CO2 will also vary with in the drainage basin
with soil depth, but these values are also assumed to be distributed uniformly across the
study area. We recognize these assumptions, along with those stated earlier, as
simplifications of a complex natural system, but data limitations make it impossible to
account for changes at every location. We, therefore, proceed with our calculations in
an attempt to better quantify dissolution in this system.
60
3.3 Results
3.3.1 Rainfall and Recharge
On 3 March 2012, the Live Oak weather station recorded 37.3 mm of rainfall. In
the seven days preceding this event, the gauging station recorded 13.2 mm of rainfall,
for a total of about 50 mm. We estimate there was 20 mm of diffuse recharge during
this period. The drainage basin covers 7.8 x 108 m2 between the Pinetta and Lee
gauging stations and thus ~1.6 x 107 m3 of water recharged the aquifer, assuming
uniform rainfall across the basin and no runoff.
3.3.2 Hydrologic Responses
Pinetta and Madison Blue Spring river gauging stations show similar trends
through time, but the magnitude of changes in stage and discharge vary between the
gauging stations (Fig. 3-3). During the 2012 flood, from 2 to 9 March, the
Withlacoochee River rose 2.3 m at Pinetta, 2.4 m at Madison Blue, and 2.1 m at Lee.
Estimated discharge increased to a maximum of ~1.3 x 107 m3/day at Pinetta and ~1.2 x
107 m3/day at Lee (Fig. 3-4A). The gauging station at Madison Blue Spring run recorded
an increase in discharge up to ~3.4 x 105 m3/day until 2 March 2012, at which point
discharge declined rapidly, reaching a low of ~-2.6 x 105 m3/day during the reversal of
flow (Fig. 3-4A). These changes in river stage and discharge were sufficient to cause
intrusion to the spring that lasted 71 days before spring discharge returned to baseflow
water chemistry (Fig. 2-4).
3.3.3 Historic Record of High Water Events
The three methods used to estimate river intrusion were within an order of
magnitude of each other for this reversal. Gauging station data indicate ~7.2 x 105 m3,
whereas the groundwater flow model (Spellman 2012) and mixing model estimated ~2.2
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x 106 m3 and ~2 x 106 m3, respectively (Fig. 3-4B). We chose the hydrologic model
estimate for the remainder of the analyses (see 4-1).
Interactions between the river and surrounding aquifer differ in the two studied
river reaches (Pinetta-Madison Blue and Madison Blue-Lee). Immediately prior to the
2012 flood, the Pinetta-Madison Blue reach lost ~ 1.9 x 105 m3/day to the aquifer and
evapotranspiration. During the 2012 flood from 3 to 13 March 2012, the Pinetta-Madison
Blue reach lost an additional ~1.2 x 107 m3 over pre-event conditions, for a total input of
~1.4 x 107 m3 to the aquifer. Evapotranspiration for the area peaked at 3.3 mm/day
during the flood (FAWN), and since we are only concerned with evaporation, and not
transpiration, in the river, we consider any river losses, other than to the aquifer, to be
negligible. The Madison Blue-Lee reach is a gaining stream during baseflow and
received ~6.4 x 105 m3/day from the aquifer and surface runoff (Fig. 3-4C), but from 3 to
12 March 2012 the river gains slowed by ~4.6 x 106 m3 changing this river reach into a
losing river. Since these slowed gains are likely the result of river water entering the
aquifer, we add these decreases in aquifer discharge to the total river intrusion
calculation. From 3 to 22 March 2012, the river gains increased by ~1.3 x 107 m3 over
pre-flood levels. If we sum the losses from the Pinetta-Madison Blue river reach and
losses from Madison Blue-Lee river reach, excluding the Madison Blue reversal, we find
that ~1.4 x 107 m3 of additional river water above normal conditions entered the aquifer
during the 2012 flood.
Using the effective porosity and vertical and horizontal hydraulic conductivities of
the aquifer, we estimate the volume of matrix rock (e.g. Fig. 3-5) that the intruding river
water would occupy. We simplify the volume penetration shape assuming a cuboid
62
which will be 1.5x greater in width than height because of the anisotropy of the
respective hydraulic conductivities (Williams and Kuniansky, 2015) (Fig. 3-1). River
bank intrusions in the Pinetta-Madison Blue reach would occupy 4 x 107 m3 of rock
matrix. The resulting surface expression of this value is 5.5 x 105 m2. The smaller
volume of intruded water to the Madison Blue –Lee reach would occupy 8 x 106 m3
generating a surface expression of 2.3 x 105 m2. Combining the two regions would
occupy a volume of 4.8 x 107 m3 of rock matrix with a surface expression of 7.8 x 105 m2
which will be used later in comparative denudation calculations. River water would
have intruded further into the matrix in some areas over others because conduits (i.e.
Madison Blue Cave System) would transport water farther away from the main channel
than matrix porosity. Nonetheless, these estimates provide an approximation of the
volume of the aquifer that could be occupied by intruded water.
The Madison Blue 2012 spring reversal is one of 124 reversal events that are
estimated to have occurred over the past 82 years, based on river discharge records
(Fig. 3-6), which equates to ~1.5 reversals/year. The 2012 reversal is in the first quartile
of river stage for all estimated spring reversals, which had no statistical outliers, which
are defined as values more than two standard deviations from the smallest or largest
recorded values.
3.3.4 Dissolution Estimates
The average composition of water intruding Madison Blue Spring indicates it was
capable of dissolving 0.17 mmol/L of calcite, assuming it reacted to equilibrium with
calcite. Multiplying this average dissolution potential by the hydrologic model estimate of
intruded river water volume (L) yields a total estimated dissolution during the spring
reversal of ~3.8 x 108 mmol of calcite, which based on a molar density of calcite of 2.71,
63
with 30% porosity, represents a volume of ~1.4 x 107 cm3. Assuming the average
dissolution at Madison Blue Spring is similar to water loss to the river banks, an
additional ~2.4 x 109 mmol or ~9 x 107 cm3 of limestone would have dissolved along the
other portions of the river reaches.
Average rainfall chemistry in the region for March 2012 indicated rain water is
capable of dissolving ~0.42 mmol/L of calcite after soil CO2 concentrations of 10,000
ppm have reacted with infiltrating rain water. This concentration is frequently observed
(Karberg et al. 2005; Hasenmueller et al., 2015), and because of an increase in root
respiration following rainfall (Bouma and Bryla 2000), the soil pCO2 likely remains
elevated despite the fact that recharging water carries CO2 into the rock matrix. We
calculated that rainfall-driven diffuse recharge is capable of dissolving ~6.7 x 109 mmols
of calcite or ~2.6 x 108 cm3, but likely only dissolves 6 x 109 mmol or 2.3 x 108 cm3 (see
4.1). Combining dissolution values from all four sub-regions, we estimate a total of 8.8
x 109 mmol or 3.3 x 108 cm3 of calcite was dissolved during this event.
3.4 Discussion
The effects of spring reversals, river losses to the aquifer, and rainfall filtering
through the soil and rock matrix should impact the specific locations and extent of
dissolution across a landscape. Dissolution could be distributed widely across the
region, resulting in generally uniform denudation, or could be concentrated at point
sources, in conduits, or along river banks (Ritorto et al., 2009). The amount of
dissolution in each sub-region should also be modified by variations in the chemical
composition of the water. Spatial variations in dissolution should affect the regional
geomorphology and hydrogeology. Below, we report the relative amounts of dissolution
64
that resulted from these differing mechanisms and discuss how they influenced
development of the modern landscape.
3.4.1 Dissolution Estimates
Chemical composition of river water differs from composition of rainfall,
suggesting a chemical control on the amount of possible dissolution. River water is
allogenic, largely originating as runoff from the Hawthorn Group in the northern portion
of the watershed (Fig. 3-2). This water contains high concentrations of organic matter
derived from wetlands perched on the confining unit. This organic matter produces CO2
when remineralized, but reaches pCO2 values less than those derived from infiltration
through the soil because of degassing in the river (Khadka et al., 2014). These
variations in composition lead to differences in the dissolution potential of the recharging
water. We discuss below the details of dissolution in each sub-region (Fig. 3-1).
During the spring reversal, hydrologic and mixing models indicate 1.4 x 107 cm3
and 1.25 x 107 cm3 of calcite was dissolved, based on the chemical composition of the
intruding water. This volume represents ~5% of the total dissolution caused by the
storm. Dissolution likely occurs on the conduit wall as well as in a “dissolution halo”
(Moore et al., 2010) in the matrix surrounding the conduits. Therefore, not all
dissolution enlarges the conduits, but most of the enlargement of the conduit appears to
result from intrusion of river water under current hydrologic conditions (Ezell et al., in
prep).
Loss of river water between the Pinetta and Madison Blue Spring gauging
stations was greater than pre-flood conditions, and the decrease in river gains between
Madison Blue Spring and the Lee gauging station reflect penetration of river water into
the aquifer before increased aquifer discharge. The water intruding the Madison Blue
65
Cave system (~2.2 x 106 m3) represents ~44% of the reduced river water gains in the
Madison Blue-Lee reach (Fig. 3-4 B and C) and indicates that each river reach had
water penetrate into the aquifer despite transitioning from confined to unconfined
regions. Dissolution in this sub-region represents ~27% of the total dissolution caused
by the storm event. This dissolution is not distributed homogenously along both river
reaches, particularly considering the magnitude of water lost to Madison Blue Spring.
Other smaller conduits in the region likely also received some of the intruding water.
Nonetheless, assuming a homogenous penetration, based on vertical and horizontal
conductivities of river waters into the aquifer, allows us to estimate that the penetrated
portion of the matrix has a land surface expression area of ~7.8 x 105 m2 (Fig. 3-1).
Assuming the dissolution volume was evenly distributed over this area, a “denudation”
of 0.035 mm would have occurred by dissolution during the storm.
The chemical composition of recharged rainfall after reaction with soil CO2
indicates 0.42 mmol/L of calcite would dissolve, assuming a pCO2 of 10,000 ppm.
Diffuse recharge and estimated CO2 concentrations yield a total rainfall dissolution
value of 6.7 x 109 mmols of calcite or ~2.5 x 108 cm3, assuming the water reacted to
equilibrium. Because carbonate dissolution rates slow when waters approach
saturation with respect to calcite (Svensson and Dreybrodt 1992; White 2002), water is
unlikely to have completely equilibrated. Baseflow waters collected from the spring
were estimated to have recharged ~26 years prior to discharging according to CFC age
date estimates (Pers. Comm. Marie Kurz) and are still only 96-98% saturated with
respect to calcite. It is likely that at least a portion of diffuse recharge that occurred
during the storm discharged more rapidly than spring water flow during baseflow
66
conditions, thereby preventing this diffuse recharge from reaching a baseflow discharge
saturation with respect to calcite. For comparison purposes, we assumed the water
reaches only 90% of saturation with respect to calcite. With this assumption, ~6 x 109
mmol or ~2.3 x 108 cm3 would have dissolved during the event, which is ~68% of the
storm-driven dissolution.
The magnitude of dissolution resulting from diffuse recharge is ~2.6 times greater
than river water dissolution (~9 x 107 cm3). Because this dissolution would be distributed
across the entire drainage basin, this value would convert to a denudation of ~0.0003
mm, which is <1% of the denudation caused by loss of river water to the aquifer.
Because this storm represented only ~3.7% of yearly rainfall and not all rainfall events
result in loss of water to the aquifer, the relative amounts of denudation caused by
recharge through the land surface and from loss of river water are probably more
similar. Assuming dissolution due to diffuse recharge is similar for all rainfall events, this
dissolution mechanism would represent denudation of 0.008 mm/yr, which is about 15%
of the denudation from loss of river water to the nearby aquifer during the year. This
denudation value is 10-50% of the 0.03 to 0.09 mm/yr previously estimated (Opdyke et
al. 1984; Adams et al. 2010), perhaps reflecting the additional dissolution from loss of
flood water.
The storm that we studied was not an especially strong storm event and did not
trigger an especially large spring reversal. The Madison Blue 2012 reversal ranked in
the first quartile of estimated reversals based on stage, and we speculate that bank
infiltration volumes associated with this event would correspond to stage and be in the
first quartile. While we do not know exactly how many spring reversals and bank
67
infiltrations have occurred in the full ~80 year study record due to a lack of antecedent
moisture conditions/ground water level data, we can speculate that this storm triggered
a relatively small amount of dissolution compared to others in historical records (Fig. 3-
6).
3.4.2 Implications for Regional Geomorphology and Hydrology
Both loss of river water and diffuse recharge through the land surface (Fig. 3-1)
alter landscapes, but dissolution by these processes operates at different frequencies
and scales. Rainfall may occur without increasing river stage sufficiently to cause
spring intrusions or bank infiltration. Alternatively, rainfall outside the immediate
catchment area can flood the river, causing loss of water from the river to the aquifer
and dissolution, without having diffuse recharge to the aquifer through the land surface
(Brown, 2015). Although diffuse recharge associated with rainfall occurs more
frequently than spring reversals, loss of river water to the aquifer creates more focused
dissolution. Considering that intrusions occur ~1.5 times/yr (Fig. 3-6), this mechanism is
likely to be an important geomorphic control on the landscape.
Focused dissolution from loss of river water can enlarge previously created
voids. This dissolution pattern could produce the large spring/cave systems common to
north Florida. If regional denudation rates were higher, cave systems would be
exposed before they developed kilometers of passages (e.g. Madison Blue and
Peacock Springs), instead of opening only at rivers and sinkholes where dissolution is
more concentrated. Alternatively, if dissolution from loss of river water were greater
relative to dissolution from intrusion through the land surface, drainage would be
diverted underground, thereby limiting formation of rivers. This pattern of drainage is
seen on the Yucatan Peninsula, Mexico (Back and Hanshaw, 1970; Stringfield and
68
LeGrand, 1976). Maintaining the proper ratio of rainfall dissolution to river water
dissolution has resulted in the hydrology and geomorphology in north Florida today,
which includes both large-conduit/spring systems and surface rivers.
3.5 Conclusions
The balance between focused dissolution from loss of river water and regional
denudation results in north Florida’s current geomorphology and hydrology, specifically
including long phreatic caves along with surface rivers. To determine these dissolution
patterns, we evaluated of how dissolution is distributed across a carbonate landscape
during a recharge event. We estimated total carbonate dissolution driven by this single
storm was 8.8 x 109 mmol or 3.3 x 108 cm3. River reversal into a single first magnitude
spring caused ~5% of the total dissolution. Loss of river water to the aquifer resulted in
27% of dissolution. The remainder of the dissolution (68%) was a consequence of
diffuse recharge across the land surface. Dissolution differences caused by these
mechanisms are a consequence of differences in recharge volume and degree of
undersaturation of the recharge water with respect to calcite. These differences in
recharge patterns and dissolution capability led to focused dissolution during the spring
reversal and river bank penetration and more dispersed dissolution during diffuse
recharge across the land surface. Focused dissolution from loss of river water is
responsible for enlarging conduits and spring systems which govern much of the
regional hydrology. In contrast, dissolution from diffuse recharge across the land
surface results in regional denudation. Comparative denudation values based on
dissolution from loss of river water at 0.05 mm/yr are similar to previously calculated
denudation range at 0.03-0.09 mm/yr, but this mode of dissolution is less frequent than
regional dissolution through rainfall, which created denudation values that are about one
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order of magnitude lower than the previously calculated denudation range at 0.008
mm/yr. This finding has implications for karst landscapes around the globe which
should vary according to local geology and climate; past and future landscape evolution
can now be better understood by estimating dissolution location and volumes based on
rainfall and drainage patterns.
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Figure 3-1. Karst terrain under normal and storm conditions. A) Karst terrain under
normal conditions showing a gaining river and spring additions to the river. B) Karst terrain under normal conditions showing a losing river and conduit loss from the river. C) Karst terrain under storm conditions showing higher river stage, higher water tables, and dissolution occurring due to rainfall, bank intrusion, and a spring reversal. Bank intrusion is 1.5x greater horizontally than vertically. Surface expression of rainfall infiltration is truncated on this figure. Modified from Gulley et al. (2013).
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Figure 3-2. Maps of the drainage basin and cave. A) Map of the Suwannee River Basin showing location of Madison Blue Springs cave systems and stage gauges on the Suwannee River. B) Map of Madison Blue Spring cave system in relation to the Withlacoochee River. Modified from Gulley et al. (2011).
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Figure 3-3. Stage data for Pinetta (dashed red line) and Madison Blue (black solid line) sites from 2002 through 2013. All stage data were corrected to the NGVD 29 datum and are shown as meters above sea level.
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Figure 3-4. River and spring responses to rainfall. A) Discharge at Pinetta, Madison Blue, and Lee during the 2012 flood. The increase in discharge is first and largest at Pinetta. The Madison Blue spring gauge shows negative discharge during the peak discharge at Pinetta and Lee. The falling limb of the hydrograph at Lee is elongated compared to Pinetta. B) Model-simulated (dotted line) and gauge-station-measured (solid line) discharge at the Madison Blue Spring gauging station. During the 2012 flood, the hydrologic model and USGS gauge data both show negative discharge, reflecting loss of water to the spring. The hydrologic model shows a greater negative discharge than the USGS data. C) River losses through time from Pinetta to Madison Blue river gauges and Madison Blue to Lee river gauges. The Pinetta to Madison Blue (green line) reach experiences river loss to the aquifer under normal flow conditions and losses increase during March 2012. The Madison Blue to Lee (black line) reach is normally a gaining river and briefly becomes a losing river before a rapid and short-lived increase in gains following the storm.
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Figure 3-5. Limestone river bank along the Withlacoochee River in north Florida. Photo
courtesy of Amy Brown.
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Figure 3-6. Pinetta Gauge Station stage data from 1932 to 2013 (black solid line) with calculated reversals (red dots).
76
CHAPTER 4 BIOGEOCHEMICALLY DRIVEN CARBONATE DISSOLUTION AND FUTURE
CLIMATE IMPLICATIONS
4.1 Introduction
Because of the greenhouse effects of CO2, Earth’s temperature has fluctuated
between warm and cool periods that correspond to periods of elevated and depleted
atmospheric pCO2 (Shakun et al., 2012). Although strong ties exist between CO2 and
Earth’s temperature, the global carbon cycle remains poorly understood, especially with
regard to fluxes of CO2 to and from terrestrial carbonate reserves (Torres et al., 2014).
Because carbonate minerals represent the largest reservoir of C in the Earth,
dissolution and precipitation of these minerals should affect carbon cycling (Falkowski et
al. 2000; Martin et al., 2013; Liu and Dreybrodt, 2015).
Biogenically produced carbonate minerals form large carbonate platforms in
warm marine waters at low latitudes. These platforms dissolve when they react with
naturally produced acid, during which CO2 may be released to the atmosphere,
depending on the type of acid responsible for the dissolution (Torres et al., 2014). Two
types of acid, carbonic and sulfuric, are common in these settings, and both have been
identified as being capable of dissolution of carbonate platforms (Bottrell et al., 1991;
Gulley et al., 2013; Gulley et al., 2015; Stoessell et al., 1993). Net flux of CO2 to the
atmosphere from these dissolution reactions differs. When carbonic acid dissolves
limestone, two moles of bicarbonate are produced, with one mole of C from the
dissolution of solid carbonate and the other mole from atmospheric CO2 (Lerman et al.,
2007).
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𝐶𝑂2 + 𝐻2𝑂 ↔ 𝐻2𝐶𝑂3 (4-1)
𝐻2𝐶𝑂3 + 𝐶𝑎𝐶𝑂3 ↔ 𝐶𝑎2+ + 2𝐻𝐶𝑂3− (4-2)
The reverse of reactions 4-1 and 4-2 release CO2 back to the atmosphere that
previously had been sequestered as bicarbonate, and consequently, these coupled
reactions limit its impact on global carbon cycles over long periods of time (Berner et al.,
1983). In contrast, the coupling of oxidation of sulfide to sulfuric acid
𝐻2𝑆 + 2𝑂2 ↔ 𝐻2𝑆𝑂4 (4-3)
and the dissolution of carbonate minerals with that sulfuric acid
𝐻2𝑆𝑂4 + 𝐶𝑎𝐶𝑂3 ↔ 𝐶𝑎2+ + 𝐶𝑂2 + 𝐻2𝑂 + 𝑆𝑂42− (4-4)
generates a flux of CO2 to the environment that previously had been sequestered in the
solid phases.
Recent work suggests that burial of bicarbonate (produced in Reaction 4-2)
incorporated in organic matter represents a net sink of carbon from these systems (Liu
et al., 2011; Liu and Dreybrodt, 2015), at least on short time scales of a few hundred
years (De Vries et al. 2012). Understanding of the carbon cycle is further complicated
by detailed records of CO2 concentrations during the Cenozoic. In addition to carbonate
dissolution, silicate weathering can sequester atmospheric C, and during the Cenozoic,
uplift rates should have resulted in enough silicate weathering to remove all CO2 from
the atmosphere if a simultaneous source of CO2 did not exist. This proposed source
was CO2 released to the atmosphere as a result of carbonate dissolution by sulfuric
acid (Torres et al., 2014). With the understanding that carbonate mineral dissolution
may represent a sink, source, or have no impact on the global cycle, it becomes
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increasingly important to understand reaction mechanisms and how they relate to the
source of acid responsible for carbonate mineral dissolution.
The distributions and amounts of naturally occurring carbonic and sulfuric acid
vary widely. Carbonic acid is commonly formed from hydration of CO2 derived from
atmospheric CO2, plant respiration, and CO2 produced by microbial respiration during
the remineralization of organic matter (OM) (Adams and Swinnerton, 1937; Falkowski et
al., 1998). In contrast, sulfide distribution is more restricted because of its instability in
oxidizing systems, but it is common in and around marine systems because of the high
concentration of SO4 in seawater relative to other terminal electron acceptors (TEA) in
that environment (Stoessell et al., 1989, Schmitter-Soto, 2002). Sulfide is common at
haloclines that separate freshwater lenses that float isostatically on top of underlying
water with marine salinity (Socki, 1984; Stoessell et al., 1993). OM also accumulates at
the density interface of haloclines, where it is remineralized using the most energy-
efficient TEA. With O2 as a TEA, CO2 is released, but with SO4 as the less energetically
favorable, but more abundant TEA, both H2S and CO2 are formed. The result of these
reactions is that haloclines have low O2 concentrations and high concentrations of CO2
and H2S. Consequently, carbonate minerals may be dissolved at haloclines, which are
therefore ideal locations to study reaction mechanisms for carbonate mineral
dissolution.
Haloclines can be accessed through water-filled sinkholes; these features are
referred to as blueholes in the Bahamian carbonate platform and cenotes in the
Yucatan carbonate platform. Blueholes form by three processes: vadose dissolution
when sea levels are sufficiently low, bank margin failure, and progradational collapse of
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a subsurface void (Larson 2012). After blueholes form, they may expand at the land
surface to form a wide, circular surface expression (referred to here as the bowl) where
the conduit walls have been more extensively dissolved, and a narrower, more vertical
opening near the center of the structure (referred to here as the well). Processes that
could lead to this morphology have never been described, but we hypothesize that they
may relate to variations in water chemistry across the halocline.
Oxidation of H2S may occur through diffusion of atmospheric oxygen into the
water column or in situ production of O2 during photosynthesis. Diffusion of
atmospheric oxygen may restrict formation of sulfuric acid to near the water surface.
However, at greater depths in the water column, benthic plant photosynthesis would be
a more likely source of oxygen, provided that water depth and clarity permit sufficient
sunlight for primary production. Photosynthesis also consumes CO2, thereby increasing
pH. Diel patterns of changing pH values have been found in streams, rivers, and lakes
(Clark, 2002; Cicerone et al., 1999; de Montety et al., 2011; Kurz et al., 2013; Nimick et
al., 2003), but have never been measured at the interface of salt and fresh water of
carbonate platforms and evaluated in relationship to the potential for carbonate mineral
dissolution.
We estimated the relative magnitudes of dissolution caused by carbonic and
sulfuric acid to assess their potential for carbonate mineral dissolution and their roles in
CO2 transport to and from the atmosphere. This assessment was made using water
chemistry analyses logged at high frequency (1/min) and by direct sampling at lower
frequencies through tidal cycles and at various light intensities. The data were used to
address the role that tidal and solar radiation cycles have in controlling dissolution
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reactions. We used these data to evaluate how variations in dissolution of carbonate
minerals may influence the global carbon cycle.
4.2 Study Site and Methods
4.2.1 Study Site
This study focused on Inkwell Bluehole on San Salvador Island, The Bahamas
(24.1° N 74.48° W) (Fig. 4-1). San Salvador Island is the easternmost island in The
Bahamas and sits on an isolated carbonate platform. The island receives an average of
100.7 cm of annual rainfall (Shaklee, 1966). Approximately half of the island is covered
by lakes, most of which are either of marine salinity or hypersaline because of conduit
connections to the ocean and the negative water balance. Inkwell Bluehole, which is
located in the southwestern portion of the island (Fig. 4-1), is approximately circular in
shape and has a surface diameter of about 16 m and a depth of approximately 8 m (Fig.
4-2). No conduit has been found linking Inkwell directly to the ocean, but its tidal
amplitudes are usually within 15 cm of local ocean tide amplitude and its tides lag ocean
tides by only about 10 minutes, reflecting a high-permeability connection to the ocean
(Martin et al., 2012; Samson and Guilbeault, 2013). The water column is stratified, with
a halocline located at approximately 3 m depth. Overlying tannic surface water
attenuates light quickly as shown by Secchi disk readings of approximately 140 cm, but
water below 3 m is clear (Sampson and Gauilbeault, 2013).
4.2.2 Field Methods and Sample Analyses
Tidal fluctuations in the water level in Inkwell Bluehole were measured from 10 to
14 October 2012 by suspending a conductivity, temperature, and depth (CTD) sensor in
the bluehole water column at a fixed elevation through eight tidal cycles. Although the
absolute elevation of the logger is unknown, the difference from the mean elevation
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during the study provides tidal amplitudes and periodicity. The sampling period
occurred during three days leading up to a spring tide. During that time, three buoys
were secured in a transect across the top of the blue hole, with one buoy ~1 m from the
edge of the blue hole (nearshore), one in the center of the blue hole ~7 m from the
shore (center), and the third halfway between the other two, ~4 m from shore
(intermediate). Three logging instruments, including two InSitu Troll 9500s and one YSI
6600 multi-parameter logging instrument, were suspended from the buoys at 0.75 m
below the water surface. These instruments measured pH, temperature, specific
conductance (SpC), and dissolved oxygen (DO). The DO probe is optical, which
minimized interferences with sulfide and provided more accurate measurements at low
DO concentrations. Measurements were taken every minute throughout the experiment.
Since the buoys rose and fell with the tide, the instruments logged the water
composition at a fixed depth in the water column.
Water samples were collected three times from Inkwell Bluehole in October
2012, corresponding with the logging data, and twice in May 2012, when no logging
instruments were available. During both trips, samples were collected using a peristaltic
pump connected to flexible PVC tubing that extended from the shore to the center of the
bluehole in May 2012, and to each of the three buoys in October 2012. In May 2012,
samples were collected in a vertical profile through the water column while the PVC
tubing was hand-lowered at increments of 0.75 m at the center of the bluehole (Fig. 4-
3). During the October 2012 sampling, PVC tubing was suspended from each of the
three buoys at depths 2 m below the water surface. Samples were collected from just
prior to low tide to high tide on 11 October, from mid ebb tide to just after low tide on 12
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October, and from high tide to low tide on 14 October. Water was pumped into an open,
flow-through cell that held a sonde connected to a calibrated YSI 556MPS instrument
that measured specific conductance, DO, pH and temperature. Water was pumped
over the sonde for at least eight minutes until values stabilized. The DO concentrations
only show gross relationships with depth because the cup is open to the atmosphere,
and elevated sulfide concentrations can interfere with the sensor membrane, resulting in
an overestimate of DO concentrations.
Water samples for the measurement of major cations (Na+, K+, Mg2+, and Ca2+)
were filtered through a 0.45-µm trace-metal-grade high-capacity canister filter, collected
in acid-washed 20- mL plastic screw-top bottles, and preserved with trace-metal-grade
nitric acid to pH < 2. Water samples for measurements of anion concentrations (Cl-,
SO42-) were also filtered and collected unpreserved in new, but not acid-washed, 20- mL
plastic screw-top bottles. Water samples were collected in 60- mL pre-rinsed screw-top
plastic bottles and measured immediately in the field for hydrogen sulfide
concentrations using a HACH DR/890 Colorimeter using the Methylene Blue Method
(HACH Company 2013). Water samples for the measurement of dissolved inorganic
carbon (DIC) and δ 13C values of the DIC were collected in pre-rinsed 20- mL French
square vials and treated with HgCl2 to limit microbial alteration of the samples. Samples
were kept chilled on ice in the field and in refrigerators after returning to the lab at the
University of Florida, where major element, DIC concentrations, and δ 13C ratios were
measured.
Cation and anion values were measured on an automated Dionex DX500 Ion
Chromatograph. The samples had an average charge balance error of 1.6% with only
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one sample exceeding 5%. The sulfide concentrations were measured with an
accuracy of ±0.02 mg S/L. The DIC samples were measured by acidifying water
samples using an AutoMate Prep Device and the resultant CO2 was measured with a
UIC (Coulometrics) 5011 carbon coulometer. The method was standardized with
dissolved KHCO3 and yielded samples with an average accuracy of ±0.5%. Carbon
isotope ratios of DIC in water were measured with a Thermo Finnigan DeltaPlus XL
isotope ratio mass spectrometer with a GasBench inlet system. Water was injected into
septum-top vials that contained 0.5 mL phosphoric acid and were filled with helium.
This acidification released all DIC into the headspace and the gas mixture of CO2 and
He was sampled by the GasBench II and CO2 was separated by a GC column prior to
being measured on the mass spec. Carbon isotope measurements had a standard
deviation of 0.05.
4.2.3 Estimates of Potential Dissolution and Chemical Species
PHREEQc, a geochemical software package, was used to construct models to
estimate the production of CO2 and O2 needed to cause the observed decreases in pH
based on the reaction stoichiometry shown in reactions 4-1 and 4-3. The decrease in
pH was defined as the difference between the highest and lowest pH, i.e. between
shortly after the afternoon solar radiation maximum and when the sun rose (Fig. 4-4).
Water samples used to model these changes in pH were collected within a few hours of
the pH change (Fig. 4-4) and had pH values similar to those of the water column at the
start of the pH change as measured by the suspended loggers (Table 4-1). Grab
samples used in the pH models were taken from different times in the day to track the
changing water column chemistry through the day (Table 4-1).
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Water samples collected near the start of the pre-dawn pH decrease were
modeled by increasing the concentration of CO2 in PHREEQc until the pH of the
modeled water decreased by the same amount measured by the suspended loggers.
Similarly, water collected prior to the afternoon decrease in pH was modeled in
PHREEQc by reacting O2 and H2S until pH decreased to the observed range. Once pH
was decreased through either CO2 production or O2 and sulfide reactions, the water
was equilibrated with calcite in PHREEQc to assess its dissolution potential. The
differences in dissolution potential of the two acids represent their relative abilities to
dissolve calcite in the bluehole. These modeled changes in pH using sulfuric acid are
minima because consumption of CO2 and production of O2 during photosynthesis raises
pH, though we were unable to determine how much CO2 was taken up during
photosynthesis.
4.3 Results
Specific conductance shows haloclines at 3.75 m and 5.25 m below the water
surface in May 2012 at high and low tide, respectively, although the change in SpC
values at the halocline at high tide is sharper than at low tide (Fig. 4-3). Dissolved
organic carbon (DOC) concentrations were highest near the surface and decreased with
depth. DOC concentrations decreased more at high than low tide. Dissolved oxygen
percentages were highest at the surface during high tide and at 0.75 m depth during low
tide with nearly constant values of ~4% below 2.25 m depth, though some small portion
of this percentage may be an unquantifiable error resulting from the measurement
technique. Sulfide concentrations increased at the halocline at both high and low tides,
and the concentrations decreased sharply during high tide, but less sharply during low
tide (Fig. 4-3). Sulfide concentrations were near zero at the surface during both low and
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high tide and peaked at 3.75 meters below the water surface during low tide and 2.25
meters below the water surface during high tide.
Tidal amplitudes increased from 27 cm on 12 October to 65 cm on 14 October
and would have continued gaining amplitude until the spring tide, which occurred on 15
October (Fig. 4-4). Dissolved oxygen concentrations did not correspond to variations in
the water elevation and peaked only during late afternoon (Fig. 4-4). These values
cannot be compared with the DO depth profiles shown in Fig. 4-3 because of the
different measurement methods. For most of the record, oxygen saturation states were
below the detection limit, but display sharp maxima of up to 3.3% around 17:00 hrs
each day.
Water elevation varied inversely with several variables including pH, sulfide
concentration, δ 13C and DIC concentrations. pH decreased during high tide as shown
on both the in situ logger and the grab samples, with larger decreases occurring during
the day than at night. The in situ logger showed an average decrease in pH from high
to low tide of 0.24 during the day and 0.14 during the night (Fig. 4-4), whereas both the
in situ logger and the grab samples showed pH to be inversely correlated with tide
(Figs. 4-4 and 4-5). The grab samples show the same general trends in response to
tidal fluctuations at all three sites, but the variation in pH was diminished at the
nearshore site compared with other sites. Water elevation also correlated with sulfide
concentrations, which ranged from 1.3 mg/L during low tide to 17 mg/L during high tide
(Fig. 4-6). Water from the nearshore site contained more sulfide than the other sites at
low tide, occasionally by more than a factor of two, but the concentrations were similar
at all sites during high tide. Carbon isotope ratios showed the strongest inverse relation
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with water level in grab samples collected on 11 October, moving from low to high tide.
Values maintained the same general trend at all three sites (Fig. 4-7). All sites showed
similar trends of DIC concentrations through time relative to the tidal cycle, including a
plateau during high-tide conditions (Fig. 4-8).
Waters selected to model acid production and dissolution had pH values that
decreased by 0.07 to 0.18 pH units during the night and 0.2 to 0.31 pH units during the
day. The daytime decreases corresponded to increases in DO saturation states.
Assuming the nighttime pH changes resulted from increasing CO2 concentrations
caused by respiration, 0.2 to 0.4 mmol/L of CO2 was respired. Assuming the daytime
decrease in pH resulted only from oxidation of sulfide, between 0.5 and 0.8 mmol/L of
DO was reduced during the day (reaction 4-3). The DO would have been produced by
photosynthesis, which consumes CO2, and thus the observed decrease in pH must
represent only a minimum of sulfide oxidation. Prior to the production of CO2 at night,
the water had an SI of -0.02 and was capable of dissolving 0.017 mmol/L calcite. After
production of CO2, the SI decreased to -0.19, and the water was then capable of
dissolving 0.25 mmol/L. Prior to the oxidation of the sulfide, the water had an SI = -0.02
and was capable of dissolving 0.018 mmol/L calcite, but after the oxidation of sulfide the
SI decreased to -0.47 and the water was then capable of dissolving 0.62 mmol/L calcite.
4.4 Discussion
4.4.1 Relative Impact of Tidal and Solar Radiation Cycles on Dissolution Potential
Daily variations in both solar insolation and water level altered the saturation
state of the water with respect to calcite. Solar insolation is an important variable
through its control on photosynthesis and the consumption of CO2, production of
oxygen, and oxidation of sulfide to sulfuric acid. Tidal variations in water level influence
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the saturation state by raising and lowering the halocline relative to the water surface,
thereby bringing sulfide trapped at the halocline closer to atmospheric oxygen. The
amount the halocline moves through a tidal cycle relative to the water surface is a
function of the shape of the blue hole (Fig. 4-2). Movement of the halocline within the
water column, and diel cycles, change the pH of the water column at and above the
halocline. Daily changes in pH were also found in a United Kingdom stream where pH
varied from 7.68 to 8.48 during diel cycles (Spiro and Pentecost, 1991), and changes in
pH from 8.3 to 9.1, 6.9 to 7.3, and 8.1 to 8.3 were measured in three different Montana
streams by Nimick et al. (2003). All of these pH measurements showed lower values
during night than the day because of increasing CO2 concentrations, but this study
showed decreases in pH during the night and day. Whereas in both systems plants
respire CO2 leading to decreases in pH, this system also has sulfide, which oxidizes
and serves as an even more important control on pH.
In non-tidal freshwater systems, which contain no sulfide, pH values typically
reach minima at night as a result of respired CO2 and maxima during the day, as a
consequence of CO2 consumption during photosynthesis (Spiro and Pentecost, 1991;
Nimick et al., 2003). The variations in pH are particularly strong in freshwater systems
with abundant flora that are poorly buffered by carbonate minerals (Kurz et al., 2013),
and dissolution likely dampens decreases in pH in Inkwell associated with high tide (Fig.
4-4) through buffering before pH levels return to slightly basic conditions during low tide.
In contrast, the semi-diurnal variations of pH values at Inkwell Bluehole are impacted by
sulfur reactions as well as CO2 production and consumption, so that respiration of CO2
at night and oxidation of sulfide during the day regulate the water-column pH. Sulfuric
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acid is stronger than carbonic acid (pKH2SO4 = 2; pKH2CO3 = 10.3) (Krauskopf and
Bird, 2003), which indicates that at the same concentrations, sulfuric acid will generate
more H+ than carbonic acid and lower the pH more, leading to a greater amount of
carbonate dissolution.
During the three tidal cycles observed, the magnitude of the pH decrease during
the day correlates with the amount of O2 produced. Maximum recorded values indicate
a greater amount of sulfuric acid is produced through sulfide oxidation (0.8 mmol/L) than
carbonic acid by respiration (0.4 mmol/L). The daytime drop in pH from sulfuric acid
production would be even greater than that observed from CO2 consumption during
photosynthesis. Although we cannot know how much CO2 is taken up during
photosynthesis, theoretical calculations are possible. If even half of the greatest oxygen
production measured corresponded to an equal uptake of CO2, removing this uptake
would yield an additional 0.4 mmol/L of CO2 in the water. This is the same amount of
CO2 produced during the greatest nighttime pH drop recorded.
The maximum sulfide concentrations are 1.5 m closer to the water surface at
high tide than at low tide because of the upper portion of the water column spreading
across the wider bowl (Fig. 4-3D). As a result, sulfide at the halocline during high tide
has a greater potential for conversion to sulfuric acid by reaction with atmospheric and
photosynthetic oxygen. This observation is supported by Bottrell et al. (1991), who
noted that sulfide concentrations in cenotes are maximal at the halocline and are
oxidized to sulfate at shallower depths where carbonates are dissolved. Variations in δ
13C values and DIC concentrations also reflect fluctuations in the position of the
halocline. The δ 13C values are more negative during high than low tide, likely reflecting
89
more δ 13C value control by remineralization of OM, generating CO2 byproducts than
with dissolution of CaCO3. The DIC concentrations vary with tide. This variation, the
inverse of δ 13C patterns, likely results from the same combination of solid carbonate
dissolving in water near the halocline and production of CO2 from remineralization. The
DIC concentrations and δ 13C values suggest that O2 produced through photosynthesis
and from the atmosphere is being used both as a TEA for microbes and oxidizer of H2S.
4.4.2 Implications for Platform Dissolution
The larger decrease in pH during the daytime than nighttime suggests that
sulfuric acid is the dominant driver of dissolution at Inkwell Bluehole. What remains
unknown is whether sulfuric acid could also represent an important cause of dissolution
in locations on carbonate platforms other than terrestrial blueholes. Dissolution occurs
throughout modern carbonate platforms as a result of multiple processes, including
mineral undersaturation caused by fresh and saltwater mixing (Mylroie and Carew,
1990; Plummer, 1975) and bacteria-produced CO2 from the remineralization of DOC in
the soil and rock matrix near the water table (Schwabe et al., 2008; Gulley et al., 2015).
To date, studies have not fully explored dissolution in carbonate platforms resulting from
generation of sulfuric acid outside of blueholes or cenotes.
Nonetheless, sulfuric acid should cause dissolution within the phreatic zone of
carbonate platforms when oxygen is available to drive the reaction. The question is
whether sulfide is generated in situ within the platform or if it is transported into the
matrix. Both possibilities exist. Water is exchanged between blueholes and the aquifer
matrix through tidal pumping (Martin et al., 2012). Tidal pumping results from
differences in phase and amplitude at the bluehole relative to the aquifer matrix as a
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result of differences in hydraulic conductivity of the aquifer and conduits connecting
blueholes with the ocean (Martin et al., 2012). This water exchange would allow sulfide
to enter the platform aquifer. Tidal variations of the water table will also allow
penetration of O2 from the water column as the vadose zone floods with rising tide. This
O2 would oxidize the sulfide in the aquifer, generating sulfuric acid (Brown et al., 2014).
Alternatively, DOC could be carried to the water table in the matrix, akin to the
input of particulate organic carbon in the blueholes. Similar to the porosity development
described in Schwabe et al. (2008) and Gulley et al. (2015), microbial remineralization
would generate byproducts leading to carbonate dissolution. In this case, microbial
remineralization would occur in anoxic environments at depth and the byproducts
generated would include H2S instead of solely CO2. When tidal pulses (near the shore)
or rainfall transport O2 into the aquifer, sulfuric acid would form and dissolve the
carbonate. The by-products would be transported away from the reaction site by the
regional groundwater flow, generating increased porosity. This hypothesis is supported
by sulfide measurements made in two well fields on San Salvador. One well in the
Linehole well field had a sulfide concentration of 1.7 mgS/L and one well in the Sandy
Point wellfield had a sulfide concentration of 8.5 mgS/L. These two wellfields are
located on opposite ends of the island, and whereas the maximum concentrations in the
wells vary, sulfide is likely present at depth across the entirety of the island, potentially
facilitating sulfuric acid dissolution of local rock.
4.4.3 Quantifying Dissolution Driven by Carbonic vs. Sulfuric Acid and C Flux to the Atmosphere
Carbonate mineral dissolution by sulfuric and carbonic acid results in different
potential fluxes of C to the atmosphere (reactions 4-1 – 4-4), indicating that
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differentiating the relative amount of dissolution by these different acids is important to
determine C exchange between the lithosphere and atmosphere. We differentiate
these fluxes by evaluating the potential amount of calcite dissolution from each acid.
Approximately 0.25 mmol/L calcite would dissolve if water with a pH acidified through
the addition of CO2 at dawn was equilibrated with calcite. In contrast, approximately
0.62 mmol/L calcite would dissolve, due to oxidation of sulfide decreasing pH in the
afternoon, or approximately 2.5 times more calcite than the estimated carbonic acid
dissolution. Dissolution by sulfuric acid is more than twice the dissolution by carbonic
acid though maximum acid production of sulfuric acid was only two times more than
carbonic acid (0.8 vrs. 0.4 mmol/L, respectively). This discrepancy in dissolution
volumes potentially stems from the tendency toward back-reactions associated with
bicarbonate in solutions and changing pH, whereas sulfate is more stable. Each of
these reaction products (Reactions 4-2 and 4-4) offsets the positive charge associated
with calcium ions, and if the offsetting charges of bicarbonate are removed, the solution
may not be able to dissolve as much calcite. The difference in sulfuric and carbonic
acid dissolution potential also extends to atmospheric carbon interactions; sulfuric acid
could add up to 0.8 mmol C/L/tidal cycle to the atmosphere if the waters reached
complete equilibrium with calcite, whereas carbonic acid dissolution would not source C
to the atmosphere.
The morphology of the bluehole also suggests that sulfuric acid drives most of its
dissolution. When Inkwell was originally formed, it likely did not have the nearly circular
surface expression seen today, but instead would have had an irregularly shaped
surface opening caused by dissolution along a preferential flow path in the vadose zone
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or collapse of a subsurface void. The flat bowl that occurs at the level of the high-tide
halocline (Fig. 4-2) suggests that the majority of Inkwell expansion through dissolution
has occurred in this portion of the water column, long enough to give the bluehole its
distinctive shape today. We do not know how long Inkwell has been dissolving, but the
morphology suggests that the majority of its formation occurred when sea levels were
high enough that it was at least partially water-filled.
Dissolution patterns in Inkwell under current sea levels have been established,
but sea levels vary, and here we speculate on the impact of sea levels rising and falling
from their current position. When sea levels rise, a mix of fresh and salt water will
persist in Inkwell until the saltwater completely inundates the feature after an ~6m rise
from its current position. The number of land-based blueholes will continue to decline
as the ocean overtops the platform containing them. Aerial exposure of the carbonate
platform will continue shrinking until the entire island will theoretically be overtopped.
Rising sea levels will limit sulfuric acid dissolution because of the greater distance
between the photic zone, which produces O2, and the majority of the carbonate
platform, until the process stops completely when no land is left above the sea. A
shrinking platform exposure will mean less dissolution driven by carbonic acid and
terrestrial OM production, but shallow sea productivity will likely increase as the majority
of the carbonate platform is covered by a shallow ocean.
The surface area of San Salvador Island, The Bahamas, is smaller than the
isolated carbonate platform it sits atop, but the Bahamas Banks contain several other
Bahamian islands and many would be connected by land if sea levels dropped 25 m
from present levels. During falling sea levels more blueholes would be present on the
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larger exposed platform, which should increase surface water/groundwater interactions.
These increased interactions would allow O2 to penetrate into the platform matrix and
react with hydrogen sulfide to form sulfuric acid (Reaction 4-3), increasing this type of
dissolution across the platform. The lower sea levels would also shift the freshwater/salt
water interface lower with respect to the carbonate platform and away from the current
surface exposure of San Salvador. This shift would remove the sulfur source from the
current exposure of San Salvador which would severely limit any further dissolution of
the current island by sulfuric acid. Dissolution driven by carbonic acid should increase
with more sub-aerial reaction sites on the larger exposed platform, which would also
support more terrestrial OM production. With steep-sided edges of the platform
exposed, shallow sea productivity would be limited during lower sea levels.
In addition to the impacts of sea level variation on island systems, sources and
sinks of atmospheric carbon will also vary. During high sea levels there is diminished
sourcing of C to the atmosphere from sulfuric acid dissolution, but there is also less
carbonic acid dissolution and terrestrial OM burial, which interact to serve as a C sink.
During low sea levels, C sources and sinks will increase with surface water/groundwater
interaction. Although it is difficult to predict the impact of changing sea levels on C
cycling in island settings, we can make general assumptions about the expected trends,
and in this paper, we identified more sulfuric acid dissolution than carbonic acid
dissolution at surface water/groundwater interaction sites. If at lower sea levels more of
these interaction sites are present, lower sea levels should generate a greater source of
C to the atmosphere via the processes described in this paper. This greater source of
C to the atmosphere may serve as a negative feedback loop through warming the
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atmosphere as a greenhouse gas, which would ultimately raise sea levels (Shakun et
al., 2012). More extensive research is needed in locations other than surficial openings
to the water table, but given the data presented in this paper, carbonate dissolution
should not be discounted when attempting to balance the global C cycle.
4.5 Conclusions
Tidal and diel cycles impact the potential for carbonate dissolution in Inkwell
Bluehole, The Bahamas, by influencing carbonic and sulfuric acid concentrations.
Dissolution potential resulting from the production of sulfuric acid is more than twice that
of carbonic acid. The geomorphology of Inkwell supports sulfuric acid as the dominant
dissolution driver with a wide upper dissolved zone that corresponds to the high sulfide
halocline. Carbonate dissolution driven by carbonic acid is understood to occur across
carbonate platforms, but we propose that sulfuric acid may also dissolve carbonate
platforms at depth. Dissolution driven by sulfuric acid represents a net C flux to the
atmosphere, and carbonic acid dissolution tied to plant burial represents a C sink.
Sulfuric acid dissolution of carbonate is greater than that of carbonic acid, which means
that Inkwell serves as a net source of C to the atmosphere. This study identifies
changes in dissolution potential that are greatest during the day; in most studies
dissolution potential is greatest at night, and this dissolution pattern in Inkwell reflects
the presence of sulfuric acid, which is not present in most continental study sites.
Dissolution in island systems on carbonate platforms needs to be better quantified in
locations other than surficial openings to the groundwater. These dissolution
assessments would better define the role of dissolution on a carbonate platform as a net
C sources or sinks to the atmosphere, but this role would be subject to change with
variations in sea level. Studies in blueholes, such as Inkwell, provide windows to
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aquifers in carbonate platforms that allow a better understanding of processes that
dissolve carbonate platforms in tropical settings around the world.
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Table 4-1. Water chemistry and parameters for grab samples used to model changes in water column pH recorded by loggers.
Inkwell Nearshore
YSI Readings Ions (mmol/L)
Date and Time Temp C SpC
uS/cm DO %
pH Cl- SO42- Ca2+ Na+ Mg2+ K+
Sulfide mgS/L
Alkalinity HCO3
10/11/12 14:27 28.36 17363 3.8 6.93 157.5251 7.2377 5.7748 141.2618 15.2957 3.0952 10.75 6.20
10/12/12 8:47 28.2 17068 4.40 6.99 153.5319 7.0493 5.5895 134.8571 14.7919 2.9504 10 6.20
10/12/12 13:45 29.02 15953 3.80 7.02 142.7423 6.6667 5.2278 123.9348 13.741 2.7184 6.3 5.43
10/14/12 8:10 27.77 19229 2.5 6.88 176.8657 8.0489 5.7787 158.4971 17.3446 3.4238 17 6.19
10/14/12 13:10 28.92 15957 3 7.09 136.5011 6.4208 5.0555 117.3618 13.1235 2.5547 5.4 5.06
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Figure 4-1. Map of The Bahamas and San Salvador. A) Map showing location of The Bahamas in relation to Florida with San Salvador Island boxed. B) San Salvador Island, indicating the location of Inkwell Bluehole, Linehole wellfield, and Sandy Point wellfield. Modified from Gulley et al. (2015).
98
Figure 4-2. Conceptual model of a cross section of Inkwell Bluehole during high and low tide. The halocline is located further down the well during low tide and at the top of the well during high tide. The fresh water is thicker during low tide and thinner during high tide. Red circles represent hydrogen sulfide distribution in the water column. Figure modified from Samson and Guilbeault (2013).
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Figure 4-3. Depth profiles collected on 6 May 2012 showing A) specific conductance, B) dissolved organic carbon concentrations, C) dissolved oxygen, and D) sulfide at high and low tide. Collection depths are relative to the high tide water elevation.
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Figure 4-4. Dissolved oxygen percent saturation, water depth, and pH plotted through time at the nearshore site in Inkwell. Gray bars indicate night, white bars indicate daytime, and yellow bars indicate periods when grab samples were collected.
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Figure 4-5. pH values and variation from mean water level near shore, intermediate,
and center sites in Inkwell occurring on A) 11 Oct 2012 B) 12 Oct 2012 and C) 14 Oct 2012.
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Figure 4-6 Sulfide concentrations and variation from mean water level for near shore, intermediate, and center sites in Inkwell occurring on A) 11 Oct 2012 B) 12 Oct 2012 and C) 14 Oct 2012.
103
Figure 4-7. δ 13C values and variation from mean water level for near shore, intermediate, and center sites in Inkwell occurring on A) 11 Oct 2012 B) 12 Oct 2012 and C) 14 Oct 2012.
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Figure 4-8 Dissolved inorganic carbon concentrations and variation from mean water
level for near shore, intermediate, and center sites in Inkwell occurring on A) 11 Oct 2012 B) 12 Oct 2012 and C) 14 Oct 2012.
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CHAPTER 5 SUMMARY
Carbonate dissolution has been studied in both laboratory and field settings.
Dissolution rates have been calculated under a variety of conditions, including flowing
and stagnant waters, changing pCO2, a range of pH, in the presence of different ions,
and several more. This research, however, was one of the first investigations to link
natural time series data sets and observed biogeochemistry of waters to study
carbonate dissolution rates and volumes.
Carbonate dissolution in karst settings is driven by rainfall that reacts with the
land surface and can force river water into river banks and spring systems. The
dissolution driven by rainfall was found to be greater than dissolution driven by river
water intruding into the river banks and springs. River water dissolution also occurred
less frequently than rainfall dissolution, but river water dissolution is more intensely
concentrated than rainfall-driven dissolution, which is spread more evenly over the
drainage basin. The balance between the two dissolution drivers is important because
it results in north Florida’s current geomorphology and hydrology. If rainfall dissolution,
considered denudation here, were much greater, conduits would not reach the size
seen today and subsurface hydrology would be affected. If river water dissolution were
much greater, virtually all landscape drainage in north Florida might go underground
resulting in a loss of surface rivers. The balance seen today is the reason north Florida
currently has long phreatic caves, while retaining surface rivers.
Dissolution driven by river water forced into spring systems can be up to 17
orders of magnitude faster than rates seen at baseflow. This makes dissolution in these
systems episodic. Approximately 80% of dissolution during the spring reversals
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occurred in the first 20% of the flood, before rates slowed almost to baseflow rates near
the end of the intrusion. Initial dissolution was driven by undersaturation with respect to
calcite of the intruding river water. Undersaturation is prolonged during the reversal by
remineralization of dissolved organic carbon that intrudes with the flood water. Diffuse
recharge of rainfall through the land surface is slightly undersaturated by the time it
reaches the conduits, but results in little dissolution of the conduits because of
exponential slowing of dissolution rates near saturation. At the beginning of a flood,
dissolution alone adds Ca2+ to intruding river water, but when the flood recession
begins, simple mixing adds more Ca2+ to conduit waters and is primarily responsible for
slowing dissolution rates.
Carbonate dissolution can also be driven by tidal and diel cycles in blueholes.
The biogeochemical shifts introduced by these cycles alter H2CO3 and H2SO4
concentrations, which in turn control carbonate dissolution rates and volume.
Dissolution potential resulting from the production of H2SO4 was more than twice the
dissolution driven by H2CO3. This pattern is the reverse of what is seen in most karst
systems with biological control. Normally, the majority of dissolution occurs during the
night when CO2 is respired by plants, but in this system, dissolution occurs primarily
during the day when plants are photosynthesizing. This dissolution pattern is further
supported by bluehole morphology, which has a wide upper bowl formation near the
surface as a result of increased dissolution. The lower edge of this bowl aligns well with
the lowest position of the halocline, which is the source of the H2S reacting to form
H2SO4. Dissolution driven by H2SO4 represents a net C flux to the atmosphere, unlike
dissolution by carbonic acid. Blueholes provide windows to aquifers in carbonate
107
platforms that allow a better understanding of processes that dissolve carbonate
platforms in tropical settings around the world.
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BIOGRAPHICAL SKETCH
John Eric Ezell was born in Tifton, Georgia. He moved to Mississippi and spent
most of his time in the woods or on a sports field. Along the way he met a few people
who encouraged him before finishing high school including Ms. Williams who had a little
extra time to help a forgetful elementary student, Ms. Huber who showed that some
teachers really were friends, and Dr. Padgett who embodied everything a teacher could
hope to be. He next attended Mississippi State University for a BS in Forestry, a BS in
Environmental Geosciences, and a MS in Geology. While at Mississippi State he
worked with one of the smartest minimum wage crews in history, had the chance to
learn from and joke with some of his favorite professors (Drs. Ezell, Grebner, McNeal,
and Mylroie come to mind), participate in a 36 hour sampling extravaganza, and
receive, possibly his greatest accomplishment, a shirt for winning the intramural softball
league. He then moved to Florida where he received his PhD in Geology and met a lot
of great friends. He, very slowly, got smarter about his research sites progressing from
briar covered clear cuts, to muddy estuaries, and finally to crystal clear springs. He had
many great instructors and friends along the way. He actively looks forward to spending
more time with family and finding a nice comfortable cave.