chen box model study 2013-2014
TRANSCRIPT
NORWICH UNIVERSITY DEPARTMENT OF EARTH AND ENVIROMENTAL SCIENCE
A Palustrine Box Model Study of Water Quality and
Chemistry at Railroad Branch Senior Research Seminar Project
Chen, A. Z. X. and Dunn, R.H.
4/29/2014 Unpublished
Presented at the 2013 Senior Seminar Presentation, 2014 Sigma Xi Induction Dinner
and 2014 Student Scholarship Celebration at Norwich University
Biophysical activity and a changing line of impoundments by beavers have presented a unique
opportunity to study a changing wetland and its effects on stream chemistry. Research on
Railroad Branch, a mountain stream in central Vermont, was conducted using a box model
approach to analyze the fluctuations in cation concentration, temperature, pH, alkalinity,
dissolved oxygen, and PO43-
/NO3.These observations included water sampled from the stream
and associated pond and wetland system. The YSI probe was used in the field to collect
temperature, pH, and conductivity. Samples of water from the pond substrate were taken using a
peat corer. In the laboratory, the Inductively Coupled Argon Plasma Spectrophotometer and
HACH kit were used to measure major and trace constituents and PO43-
/NO3, turbidity, and
alkalinity, respectively. Samples were obtained under various hydrologic conditions such as
baseflow and high flow. No previous study was done on Railroad Branch so this project and the
collected data provides insight into the biochemistry of the area and opens this system to further
study. Results show that wetlands have the ability to regulate cationic flow, showing patterns
between the inlet and outlet that cannot be seen in the pond. This data also suggests that organic
constituents in the pond/wetland play a role in the acidity.
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Table of Contents
Table of Contents .................................................................................................................. 1
List of Tables ......................................................................................................................... 2
List of Graphs ........................................................................................................................ 3
Introduction .......................................................................................................................... 4
Background ........................................................................................................................... 5
Physical Setting ..................................................................................................................... 6
Method ................................................................................................................................. 7
Results .................................................................................................................................. 8
Discussion ........................................................................................................................... 15
Conclusion ........................................................................................................................... 18
Acknowledgements ............................................................................................................. 19
Works Cited......................................................................................................................... 20
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List of Tables Table 1. Range of Data collected and tabulated ..................................................................... 8
Table 2. Sample day # and their corresponding data .............................................................. 9
Table 3.Range of Values used to calculate the percent change ............................................. 12
Table 4. Table of percent change in cation concentration (ppm) of inlet vs outlet of all
sampling days ................................................................................................................. 12
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Table of Figures Vermont Center for Geographic Information (VCGI) Map of field site ..................................... 6
Schematic map of site area. ................................................................................................... 6
Plot of temperature over three sample days at outlet (site 1) and inlet (site 2) ....................... 9
Plot of pH over three sample days at outlet (site 1) vs inlet (site 2)......................................... 9
Plot of Temperature vs. dissolved Oxygen of the 5 samples found within the pond system
after four sampling periods (n=14) ....................................................................................... 10
Plot of Temperature vs. dissolved Oxygen of the 6 samples taken at the inlet and out after
three sampling periods (n=6) ............................................................................................... 10
Plot of NO₃- vs. PO₄ for inlet and outlet day 3 and 4.............................................................. 11
Plot of NO₃- vs. PO₄ for sample sites within the pond (n=10) ................................................ 11
Plot of Alkalinity vs. pH for sample sites 1 and 2 within the pond system for day 3 and 4 ..... 11
Plot of Alkalinity vs. pH for all sample sites within the pond system for day 3 and 4 ............. 11
Plot of Fe vs Ca for all sites within the pond system during all sample days (n=20) ............... 13
Plot of Al vs. Si for all sites within the pond system and all days (n=20) ................................ 13
Plot of Mg vs. Ca for all sites within the pond system and all days (n=20) ............................. 14
Plot of Ca vs. Sr for all sites within the pond system and all days (n=20) ............................... 14
Percent change in elemental concentration over all days between site 1 and site 2 .............. 15
Percent change in elemental concentration over all days between site 3 and site 6 (positions
within the pond in proximity to the inlet and outlet) ........................................................... 16
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Introduction
The water quality and chemistry of streams and wetlands are a fundamental component
of the ecology and hydrology of a watershed. Biophysical activity and a dynamic and changing
line of impoundments by beavers have presented a unique opportunity to study a changing
wetland and its effects on a stream. Research on the Railroad Branch at Mount Paine in
Northfield, VT was conducted using a box model approach to analyze the fluctuations in cation
concentration, the temperature, pH, alkalinity, dissolved oxygen and the PO₄3⁻/NOx in the stream
and the associated pond/wetland. The concept of a box model is that during idealized conditions,
what goes into the system will come out of the system. In the case of the project, the “box” was
to be a wetland pond. In the idealized system, a pond/wetland system will have no effect on
stream water chemistry or quality because there should be no noticeable pattern in terms of
cation concentration variation following the flow of water. Samples were taken at seven
established sites that accurately represented the layout of the area.
Samples from each site were analyzed via Inductively Coupled Argon Plasma
spectrophotometer (ICAP) & HACH to get water quality in terms of the organic and inorganic
qualities in the water such as cations, dissolved oxygen and pH. Samples were obtained under
various hydrologic conditions such as baseflow, and high flow. Conditions that dictate the status
of baseflow are periods of “drought” (i.e. long durations without rain). Conditions that dictated
the status of high flow is consecutive days/periods of rain. No previous study has been done on
this creek and wetland/pond system so this project and data would give some insight into the
water chemistry variability of the area.
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Background
Wetlands have a positive impact on streams by affecting the very character of the water
in terms of its biogeochemistry (Cirmo and Driscoll 1993). The ground water chemistry along
with the history of the area (Wayland et al. 2002), the vegetation (Jabłońska et al. 2011) and
prior nutrient enrichment due to possible agricultural activity (Wang et al. 2013) all play a role in
the water’s character in the area in terms of its quality and chemistry. These marshlands are
beneficial to the environment as they have the ability to improve water quality by the dilution of
pollutants (Dosskey et al. 2010) and the suspension of abundant nutrients to ions present in the
water that could come from upstream and serve to control the flow of stream water and the
transportation of sediment (Cheng et al. 2011). The wetland can also create and maintain riparian
wetlands, decrease the velocity of a stream (increasing the water’s residence time), cause
changes in water tables, and creating microhabitats that favors bacterial growth (Cirmo et al.
1993). Areas with abundant bacteria can have sediment with low bulk density (an indicator of
soil porosity), and high organic carbon (Adame, et al 2012). The water chemistry of a wetland
can range from from low pH and low minerals to ranges of highly alkaline with high
accumulation of calcium and magnesium because they acquire their water from precipitation as
well as ground water (Vitt, et al 1990). In addition, factors such as the amount of oxidized
organic or inorganic matter containing reduced forms of sulfur and nitrogen, and the amount of
atmospheric gases such as CO₂, H₂SO₄, or HNO₃ can play a role in effecting the pH of the
wetland (Cirmo, et al 1993). Wetlands such as beaver ponds, through biological activity, can be a
source of Fe and dissolved organic carbon, with the latter being able to increase the acidity of
through the dissociation of organic acid function groups (Cirmo, et al 1993) such as carbonic
acid, uric acid and humic acid, all that could be easily found in a biologically active system.
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Fig 1. Vermont Center for Geographic Fig. 2 Schematic map of site area. The water flowed
Information (VCGI) Map of field site. from site 2 to site 1. Site 1 and site 2 were the outlet,
respectively, while sites 3-7 were sites within the pond.
Physical Setting Railroad Branch is located on the magnetic north side of Mount Paine in Northfield,
Vermont. The bedrock is the Wait’s River Formation (Fig. 1) which is characterized by
calcareous sandstone and phylitic sandstone (Westerman, 1994). The area is located in the New
England temperate climate and the study was done during late summer into fall. According to
NOAA, The region falls under a temperate climate. Railroad branch is a part of the Dog River
drainage basin. A pond/wetland was formed due to beaver activity in the area and the resulting
impoundment slowed down the water flow. The gradient of the stream goes from east to west.
Periodic and historical maps of the area reveal that the area was used for agricultural purposes
along with use by the transportation industry in the form of a railroad that went through the area
during the 18th
and 19th
century. Colonies of iron fixing bacteria and other micro-organisms
along with dragonflies and beavers inhabit the area along with passing deer, coyotes and a beaver.
Vegetation is dominated by deciduous trees with scattered coniferous trees along with reeds,
sedges, and grasses. The deciduous trees found in the area consisting of birch and maple while
the coniferous trees are dominated by spruces.
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Method
-Fieldwork
Field Sites were established to represent inflow (1), outflow (1), and in-pond (5) settings. These
sites were then plotted on a map using Northing/Easting coordinates recorded using a standard
hiking GPS. To determine dO₂, T°C, pH, and alkalinity, a YSI probe was used at each sample
site. The YSI probe was calibrated before each sampling period using pre-established
instructions. Upon arrival, samples were initially taken in both 75 ml bottles and the 475 ml
bottles respectively at the inlet and outlet of the stream (sites 1 and 2) for HACH kit tests, ICAP
measurements and bulk sediment testing. YSI readings were also taken and recorded on site. The
steps were repeated for the in pond settings (sites 3-7). Groundwater was taken by using a Dutch
Auger to core out a hole in the ground and dipping a sample bottle into the hole. The systematic
filtering of the water and collection by gravitation drainage of the water from the soil to a water
sample bottle was used to prevent machine trouble. This was done using a vacuumed beaker in
conjunction with filter paper.
-Lab work
Elemental concentration was determined with a Thermo Jarrell Ash Inductively Coupled Argon
Plasma Spectrometer (ICAP) system. Tests using the HACH kit were used in conjunction with
water quality testing with the samples in the 475 mL bottles. Using the Cadmium Reduction
method, the amount of PO₄3- was determined. The amount of NO₃⁻ was determined using the
Ascorbic Acid Method with predetermined amounts of solute were used in both NO₃⁻. Alkalinity
was measured by titrating sulfuric acid into the sample until an effect in the form of a color
change. The turbidity was measured using a 2100p Turbidimeter. Data was input into an Excel
sheet.
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Results
-Temperature, pH, dO₂, Conductivity The data for temperature, pH, dO₂, and conductivity was tabulated and inputted into a chart. Day
1 data was not collected due to the day being used to scout and mark out potential sites.
Site 1 Site 2
Spl Day 2 3 4 Spl Day 2 3 4
Temperature (C°) 16.29 13.53 4.92 Temperature(C°) 12.69 11.18 5.09
pH 7.13 7.56 7.3 pH 7.6 7.73 7.77
Conductivity 0.195 0.191 0.18 Conductivity 0.199 0.198 0.192
DO₂ 92.5 103.6 139 DO₂ 100.2 114.1 132.3
Spl Day
Site 3
Spl Day
Site 4
2 3 4 2 3 4
Temperature(C°) 16.78 13.71 5.21
Temperature(C°) 20.31 17.17 3.12
pH 6.98 7.01 7.08
pH 6.8 6.82 7
Conductivity 0.203 0.197 0.184
Conductivity 0.286 0.236 0.13
DO₂ 117 112.1 112.3
DO₂ 66 89.3 68.1
Site 5
Site 6
Spl Day 2 3 4
Spl Day 2 3 4
Temperature(C°) 18.54 15.85 3.12
Temperature(C°) 14.12 4.45
pH 7.03 7.14 7
pH 7.2 7.2
Conductivity 0.195 0.194 0.134
Conductivity 0.194 0.186
DO₂ 98.4 116.1 105.2
DO₂ 95.8 108.8
Site 7
2 3 4
Temperature(C°) 14.45 11.64 4.08
pH 6.88 7.17 7.28
Conductivity 0.177 0.181 0.186
DO₂ 92.9 92.9 114.3
Table 1.Range of data collected and tabulated.
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The relationship between temperature will be explored first as it can play a large role in its
influence of other chemistry and quality factors. The data in figure 1 were collected with the YSI
Sample Day # 1 2 3 4
Date 9/16/13 9/20/13 9/28/13 11/8/13
probe on five separate days. During the course of the study, water temperature in both outlet and
inlet decreased (Fig-3). The inlet is a lower temperature initially, but by the final sampling day,
the inlet and outlet are equal in temperature. On day 2, there was a difference of 3.6 °C while
there was a difference of 2.35 °C on day 3. There was a gain of 0.17 °C on day 4.
Figure 3. Plot of temperature over three sample Figure 4. Plot of pH over three sample days at
days at Outlet (Site 1) vs Inlet (Site 2) (n=6). Outlet (Site 1) vs Inlet (Site 2) (n=6). The
Outlet waters are slightly warmer than inlet on waters stayed consistent in that the outlet is
days 2 and 3. Temperature at the outlet and slightly more acidic while the inlet was more
inlet on day 4 was equal. basic.
pH was only measured on sample day 2-4 (Fig. 4). At the inlet, the highest pH occurred on
sample day 3. pH remained above 7.1or slightly basic on all days. Note that inlet pH values are
consistently higher than outlet values. The pH keeps increasing at site 2. Day 3 has the least
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variability between the inlet and outlet. Day 2 and 3 both have a similar range. As the inlet
temperature drops, the pH goes up. There is no relationship between the temperature and dO₂
found within the system as the data is all spread out with outliers from sites 5 and 7(Fig. 5).
However, the clusters indicate that a site that that had a measured low temperature has large
amounts of dO₂ while sites that had a measured high temperature had lower amounts of dO₂. In
contrast, there is a strong relationship in the temperature-dO₂ measured in the inlet and outlet
(Fig. 6). As the water temperature increased, the amount of dissolved oxygen decreased. This
trend was consistent with all days.
y = -3 . 9 1 9 1 x + 1 5 5 . 2 2R ² = 0 . 9 6 7 1
0
20
40
60
80
1 0 0
1 2 0
1 4 0
1 6 0
0 5 10 15 20
dO
₂
Figure 5. Plot of Temperature vs. dissolved Figure 6. Plot of Temperature vs. dissolved Oxygen of
the 5 samples found within the Oxygen of the 6 samples taken at the inlet and
pond system after four sampling periods (n=14) after three sampling periods (n=6)
-NO₃⁻ ,PO₄3-, Alkalinity, pH
A number of bivariate plots are presented to explore the relationships among variables. Samples
for nitrate and phosphate readings were taking on sample day 3 and 4. The nitrate and
orthophosphate were measured in the lab (Fig. 7 and 8). There is no relationship whatsoever on
Temperature (°C)
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sample day 3 or 4 within the pond. Site 7 remains constantly high while site 6 remains constantly
low. However, there is a trend found when comparing the inlet and outlet (Fig. 7). On day 3,
there was no difference in nitrate between the amounts of nitrate found. There was a difference
of 0.056 mg/l was found comparing the orthophosphate from the samples of the two sites. By
day 4, there was pattern in the NO₃⁻and the PO43-. There was a difference of 0.15mg/l in the
nitrate found and a difference of 0.014 mg/l in the phosphate found in the sample.
Figure 7. Plot of NO₃-
vs. PO₄3- for inlet and Figure 8. Plot of NO₃- vs. PO₄3- for pond samples
outlet day 3 and 4 (n=4). There is a gradual day 3 and 4. (n=10)
decrease in both orthophosphate and nitrate.
In addition, the water gradually gets much more alkaline and slightly acidic (Fig. 9) as the water
move from the inlet to the outlet. As alkalinity increased, the pH becomes more acidic. The sites
within the pond however do not show any relationship. Site 6 and 7 consistently has a slightly
more acidic pH while sites 3, 4, and 5 had a relatively basic pH. The data from table 4 was used
to graph bivariate graphs (fig. 11-14).Figure 11 indicates a trend where most samples have a
consistently high amount of Ca but low in Fe with two outliers from site 3. Between the Al and
Si (Fig. 12), the trend seems to be low Al and high Si with one outlier from site 5. There is
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however, a relationship between the Mg and Ca (Fig. 13) and between the Ca and Sr (Fig. 14). In
figure 11, samples from locations 4,5,6,7 all show minimum variation in
Figure 9. Plot of Alkalinity vs pH for sample sites 1&2 Figure 10.Plot of Alkalinity vs pH for all sample sites within the pond system for day3 &4. The water gets within the pond system for day 3 and 4.
more basic.
-Elemental Analysis
The data used in table 1 was used to calculate percent change (Table 2).
Outlet Inlet Spl Day 1 2 3 4 1 2 3 4
Si 3.73 2.39 2.27 2.17 2.503 2.39 4.60 2.31
Al 0.015 0.0061 0.015 0.008 0.013 0.0054 0.012 0.008
Mn 0.0084 0.0027 0.0009 0.0189 0.0001 0.00001 0.00001 0.002
Mg 3.00 3.64 3.75 3.51 3.70 4.10 4.14 4.17
Ca 31.53 35.98 36.6 31.85 35.4 37.3 36.88 34.8
Na 0.48 0.589 0.55 0.526 0.414 0.43 0.425 0.41
K 0.27 0.174 0.18 0.208 0.105 0.057 0.073 0.095
Rb 0.014 0.0085 0.014 0.032 0.031 0.026 0.00001 0.00001
Sr 0.087 0.099 0.098 0.087 0.088 0.094 0.089 0.087
Zn 0.00 0.00001 0.00001 0.00001 0.00 0.00001 0.00001 0.0001
Fe 0.25 0.116 0.18 0.194 0.0008 0.0013 0.0005 0.0037
P 0.00 0.00001 0.033 0.00001 0.00 0.013 0.014 0.00001
Se 0.023 0.00001 0.017 0.02 0.021 0.016 0.00001 0.013 Table 3.Range of Values used to calculate the percent change.
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Key number Day 1 Day 2 Day 3 Day 4
Si 1 48.82 -0.334 -50.70 -5.89
Al 2 16.923077 12.96296 26.44628099 7.79
Mn 3 8300 26900 8900 950
Mg 4 -18.79 -11.19 -9.517 -15.74
Ca 5 -10.93 -3.54 -0.76 -8.50
Na 6 15.23 35.92 29.17 28.53
K 7 157.48 206.53 146.621 118.76
Rb 8 -55.44872 -67.6806 140900 314900
Sr 9 -1.25 5.224 9.609 0.229
Zn 10 0 0 0 -90
Fe 11 30775 8853.846 35380 5140.5405
P 12 0 -99.92 131.94 0
Se 13 10.95 -99.94 0 63.2 Table 4.Table of percent change in cation concentration (ppm) of inlet vs. outlet and all sampling days.
Figure 11. Plot of Fe vs Ca for all sites within the pond Figure 12. Plot of Al vs Si for all sites within the
system during all sample days (n=20). pond system and all days (n=20)
Ca content in excess of 15 ppm. However, samples from site 3 show less than 5 ppm variation in
Ca. Site 3 samples do show more significant spread in Fe content, suggesting that metallic
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constituents at site 3 are not the same as other sites within the pond. Figure 13 shows a
correlation between the amounts of Ca and Mg. Samples are, for the most part, grouped
relatively together but it can be argued that there are two groups forming that split the data.
Figure 14 shows a temporal relationship in that the data was different each time a sample was
taken but demonstrated a strong linear relationship.
Figure 13. Plot of Ca vs Mg for all sites within the Figure 14. Plot of Ca vs. Sr for all sites
pond system and all days (n=20) pond system and all days (n=20)
Figure 15. Percent change in elemental concentration over all days between site 1 and site 2. The fluctuations reflect
changes in the concentration of the cations. The outline over the graph reflects the general trend the data follows.
Outliers for Rb on days 3 and 4 may be attributed to the presence of small amounts of Na and K and the constant ion
exchange between Rb and other aqueous compounds.
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Figure 15 shows the percentage calculated the change in the concentration of a cation found at
the inflow (site 2) and outflow (site 1) and was reported as a percentage. The data was
normalized by absoluting of all the numbers number and placed on a logarithmic scale.
Figure 16. Percent change in elemental concentration over all days between site 3 and site 6 (positions within the
pond in proximity to the inlet and outlet). The graph illustrates unique geochemical processes occurring within the
pond system. The fluctuations may represent the concentration of cations before they flowed through the dam and
after running through the stream connecting site 2 to site 3. The pattern illustrated by data collected on day four does
not fit the overall trend. This may be related to temperature induced conductions.
Figure 16 was calculated using the same methodology as figure 15, difference being the sites.
The sites were determined by analyzing sites would exhibit a similar relationship.
Discussion
The trends seen in temperature, pH, and dO₂ are consistent with the physical setting of
the entire wetland/pond system, particularly the variety of microclimates found at each site. As
the water goes from upstream to downstream from inlet to outlet, it encounters cover at both the
outlet and the inlet, which keeps the water relatively cool (fig. 3). However, at a certain point, the
water at any site remains constant through the water body if the air temperature is cold (fig.3).
The temperature also played a factor when it came to the amount of cations (fig. 16) in the sense
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that as the temperature drops, there is a decrease in biological activity even though the lack of
trend attributed to day 4 between 3 and 6 could be attributed to the lack of order between the
sites. Instead, it could indicate a flow pattern that shows a normalization of the concentrations
before the water reaches the impoundment. Conversely, there is variable cover at the sites within
the pond wetland. It is reasonable to believe using observations of each site that as the water
flows down, it enters the pond itself which has little to no leaf cover which would cause the
water to be warmer. In addition, as water warms up, it gradually releases the dO₂, which occurs
at the pond as the water runs downstream. Because of the lack of cover or a dominant current,
the data of temperature or dO₂ would be scattered due to the pre-existing variable condition of
each sample site, whether it was no shade or it was water that had not been influenced by the
water coming from the inlet. Once it reaches site 6 which is the impoundment, it reaches more
shade which cools the water down and capture O₂ and would result in high amounts of dO₂. It
can be reasoned that during cold seasons, water is very well oxygenated due to its ability to
better absorb oxygen when it is cold. Conversely, during the summer, it isn’t as oxygenated due
to the relatively warm waters but it relies on biological processes such as photosynthesis to
produce oxygen.
Much of the data obtained for nitrate and phosphate seem to indicate that as the water
flows downstream from the inlet to the outlet, the water loses phosphate (Fig. 7-8). This makes
sense because it was used up by the biotic life as it isn’t a common nutrient to find (Molles Jr.
2010). It can be reasoned that variations in the amount of phosphate and nitrate would vary
greatly when seasonal change cause change in the temperature. This was seen in the temperature
data (fig 3), and the amount of orthophosphate and nitrate found during the fall and early winter
(fig. 7-10). Because of the wide pond, the lack of a pattern in regards to the nitrate and phosphate
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levels in the pond is indicative of the lack of a direct current. In addition, due to the high
residence time, some of it could have gotten taken as it infiltrate through the pond sediment and
through the beaver impoundment. In addition, when the water gets cold, most if not all biological
processes stop, which prevents the utilization of the nutrients and allows abundance (fig 7
pH and alkalinity didn’t seem to make much sense as it is one of those factors that should
have a direct correlation: as pH goes up, alkalinity should go up. Instead, the wetland pond gets
more acidic as alkalinity rises. This could be due to the decomposition of organic acids such as
humic acids, uric acid and carbonic acid that drives up the production of amount of CO₂ and H+
from the bedrock and the production of acidity, respectively, inside the pond, and as a result
causes the acidity of the water downstream to go up. (Cirmo, et al 1993).
Residence time played a role in shaping the chemistry of the wetland system. Initially, the
constituents of the water consist of inflow from groundwater, and low if any biological activity.
In addition, no obstructions of any kind exist that prevents the water from flowing from the
headwater springs down to the pond. This however could change with the seasons and cause
naturally induced obstructions (such as ice, or fallen leaves). Water will still flow due to the
property of water to freeze from the surface downward. However, residence time increases as it
flows into the pond. Once it reaches the pond, it slowly seeps into the pond sediment as it slowly
reaches the groundwater and flows down. As it moves from the mouth of the inlet to the beaver
impoundment, it can either pick up pre-existing ions or drop off some ions that will get picked up
at a later point in time. The same process occurs as it reaches the beaver impoundment and
infiltrate down toward the outflow. Once it reaches the outlet, the water has components of the
inlet, groundwater and the much higher amounts of biological activity that seeped through.
Groundwater plays a big role during times of low baseflow or during the water cycle when the
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water infiltrates through the pond sediment or through the beaver impoundment because of the
lack of water upstream. This phenomenon happens often in Vermont as the water evaporates
during the summer and is replenished during the fall.
From the graph, the dominant cations in the wetland pond are clearly influenced by the
bedrock because of the copious amounts of calcium that exists in the samples that ended up
sinking into the pond sediment, possibly due either the effect of oversaturation, or the loss of the
cations as it seeps through the sediment. The source of Al, Mn, Na, K, and Fe could be due to the
oxidation of pond sediment, the hydration/hydrolysis of nearby rocks or leeching of minerals that
the dam, the nearby exposed slate outcrop, or the bedrock. The sinking of cations into the pond
could be due to saturation levels. In addition, similar chemical properties as in the case with Ca
and Sr, could lead to the pond have equaling amounts of elemental cations that have similar
properties such as being in the same group. Ca and Sr both belong to Group 2 and both occur in
carbonate reactions and can be used to indicate the abundance of or the depletion of, respectively.
In addition, Sr substitutes for Ca+ in marine calcite which could be the reason why they have a
strong correlation (fig. 14). The excessive amount of Fe along with the outliers in figure 11 and
the lack of correlation with the bedrock cation Ca suggest a biological source. The cations that
had no data points indicate that either there wasn’t enough to be detected or it was a detection
limit that was reached.
Conclusion
The wetland’s ability to control sediment and preferentially remove certain constituents is
possibly related to residence time shown by the fluctuations in the spider diagrams. Wetlands
have the ability to regulate cationic flow, showing patterns between the inlet and outlet that
cannot be seen in the pond. Additionally, stored organic matter plays a role in the acidity. As a
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constituent goes through the sediment it can be either sequestered or mobilized due to either
oxidation/reduction or the process of seeping through the sediment, as the sediment acts as a
natural filter. Biological activity must be accounted for when comparing the inflow and outflow
of the water (Cirmo et al. 1993) due to their effect on water quality and chemistry and the ability
to absorb water. It can be fairly reasoned that the manipulation of the biological activity would
allow greater control of nutrient flow in areas that excess of nutrients.
Acknowledgement
This research would not been possible if it wasn’t for the guidance and mentorship of
both Professor R.K. Dunn, and Professor G.C. Koteas , both of whom I owe my deepest gratitude
for the many hours devoted to invaluable critiques and advice instrumental to the entirety of the
research along with the members of the Norwich University Department of Earth and
Environmental Science for the help and support.
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References Cited:
Adame, María, Reef, Ruth,Herrera-Silveira, Jorge, Lovelock, Catherine, 2012, Sensitivity of
dissolved organic carbon exchange and sediment bacteria to water quality in mangrove forests,
Hydrobiologia., v. 691, p. 239-253.
Cheng, B.-Y., Chang, T.-K., Liu, T.-C., Shyu, G.-S., Fang, W.-T. 2011, Analysis of trends in
water quality: constructed wetlands in metropolitan Taipei., Water Science & Technology, v. 64,
p. 2143-2150.
Cirmo, C.P., Driscoll, C.T., 1993, Beaver Pond Biogeochemistry: acid neutralizing capacity
generation in a headwater wetland, Wetlands, v. 13, p. 277-292.
Dosskey, M., Vidon, P., Gurwick, N. P., Allan, C. J., Duval, T. P., Lowrance, R., 2010, The
Role of Riparian Vegetation in Protecting and Improving Chemical Water Quality in Streams,
Journal of the American Water Resources Association, v. 46, p. 261-277.
Hill, A.R., 1993, Base Cation Chemistry of Storm Runoff in a Forested Headwater Wetland. v.
29, p. 2663-2673.
Jabłońska, E., Pawlikowski, P., Jarzombkowski, F., Chormański, J., Okruszko, T., Kłosowski, S.,
2011, Importance of water level dynamics for vegetation patterns in a natural percolation mire,
Hydrobiologia. v. 674, p. 105-117.
Molles, M. C. Jr. 2010, Ecology: Concepts and Applications, New York, The McGraw-Hill
Companies, 565.
Vitt, D.H., Chee, Wai-Lee, 1990, The relationships of vegetation to surface water chemistry and
peat chemistry in fens of Alberta, Canada, Plant Ecology, v. 89, p. 87-106.
Wang, ZhaoDe, Li, Shuai, Zhu, Jun, Zhang, ZhiJian, 2013, Phosphorus partitioning between
sediment and water in the riparian wetland in response to the hydrological regimes,
Chemosphere, v. 90, p.2288-2296.
Wayland, K.G, D.W. Hyndman, D.F. Boutt, B.C. Pijanowski, D.T. Long, Modeling The Impact
Of Historical Land Uses On Surface Water Quality Using Ground Water Flow And Solute
Transport Models, Lakes and Reservoirs, 7(3), p. 189-199, 2002