Transcript Document

Nutrient Concentrations in a Constructed Wetland at Oberlin College
are Dependant on Depth and the Presence of Physical Barriers
Greta Bradford, Kate Coury, & Emily Minerath
Systems Ecology (ENVS316) Fall 2008
Methods
We attempted to quantify spatial nutrient patterns in water through a one-time collection of data
from multiple locations. We used an existing grid of sampling ports for water sample collections
that breaks the marsh into numbered columns and lettered rows (see diagram below and to left)
in square meters. Column 10 is closest to the influent; 1 is closest to the effluent. Rows lettered
A to E describe the width. Each intersection, 27 total, contains 3 PVC pipes cut to 7.62 cm
(shallow), 76.2 cm (medium), and 91.4 cm (long) inserted into the marsh to sample varying
depths (McConaghie, 2008).
Background
Natural and constructed wetlands process and remove nutrients and labile organic
matter that might damage downstream ecosystems through eutrophication. The
Living Machine (LM) is an engineered wetland ecosystem designed to the treat and
internally recycle toilet water in the Lewis Center at Oberlin College. Water travels
through a series of anaerobic and aerobic tanks to remove organic matter and
convert nitrogen into nitrate. Water then flows through a gravel marsh designed to
remove phosphorous through gravel adsorption. Prior studies suggest that only a
small amount of nitrate is removed in the marsh, because denitrification is limited
due to low levels of organic matter (Haineswood and Morse, 2003). Although the
quality of water flowing into and out of the marsh is periodically analyzed, only a few
studies have examined how water quality varies within the LM marsh with depth, with
distance from the influent, and in response to barriers to flow (McConaghie, 2008).
Knowledge of spatial heterogeneity could help us predict the phosphorus saturation
point of the gravel and help us better understand the effect of impermeable bodies,
such as the tanks that block flow pathways, on phosphorus and nitrogen processing.
This understanding could lead to more effective designs in future constructed
wetlands. Our goal is to assess patterns in phosphate, nitrate and dissolved oxygen
concentrations horizontally and vertically by sampling water at different points and
depths throughout the marsh.
Before gathering samples we pumped out stagnant water sitting in the port tubing. We gathered
samples from each port depth and the influent and effluent. Using a Dionex DX500 Ion
Chromatograph and standard procedure (Petersen, 2008), we ran the samples to determine the
ion concentrations.
We collected additional samples from Columns 1, 5, and 9 in rows B and C and the influent and
effluent sumps to test for dissolved oxygen (DO) and ammonia. We collected DO samples by
vacuum pumping to prevent oxygenation. Subsequently we tested DO using a YSI BOD Probe
procedure (Petersen, 2008). We tested ammonium using an Orion ammonium probe and
standard procedure (Petersen, 2008).
To analyze for spatial patterns in ion concentration, we used a T-test. To test nutrient
concentration variability from influent to effluent, we averaged all lengths and ports for each
column and conducted T-tests to compare the values. To test for a relationship between depth
and nutrient concentration we ran a T-test comparing all shallow values to all medium values,
medium to long, and long to shallow.
[Cl-] (mg/l)
There is a significant correlation of nitrate concentration with chloride concentration, a
passive tracer. Because organic material is negligible, it is logical that there is no
significant nitrate decrease throughout the marsh. Phosphate has almost no correlation
with chloride, as shown by the very small R2 value. This indicates that there is
biogeochemical activity in the marsh that affects phosphate levels.
Results and Discussion
Wetland Diagram
Finally, when comparing sulfate, nitrate, phosphate, chloride, and DO we found that all
nutrients except for phosphate have statistically the same concentrations at all depths.
The marsh is a rectangular basin of gravel (11.58m x 5.16m x 0.98cm deep) with gravel
size ranging from 40mm-100mm (McConaghie, 2003). The water drains with gravity
down a 2.0% grade.
Goal and Hypothesis
Because phosphate is adsorbed by gravel we hypothesized levels would decrease as
water moves from inflow to outflow. We expected low flow marsh areas to have lower
phosphate concentrations than high flow areas, since phosphate has more time to be
adsorbed by gravel (Mitsch et al. 1995). Gravel at the bottom of the marsh is larger
and therefore allows for faster flow, has smaller surface area to volume ratio, and may
reach phosphate saturation faster than the smaller gravel at shallower depths (Cernac
et al. 2004). Since water velocity increases with depth, phosphate concentration will
also increase with depth since faster flow rates reduce contact time for adsorption. We
also expected nitrogen levels to decrease from influent to effluent because inflowing
oxygenated water from the open aerobic tanks is not conducive to denitrification, but
we expected anaerobic conditions toward the end of the marsh.
Phosphate statistically differs by depth but not horizontally. Trends that seem to show higher
phosphate concentrations closer to the effluent are likely due to the fact that this system is
unevenly loaded with waste nutrients, and there could have been a bump in phosphate entering
shortly before we sampled. Consistent with our hypothesis, there is significantly more phosphate
in the long ports of the marsh than the middle and shallow ports (see above graph). The higher
flow at the bottom of the marsh could lead to a lower phosphate residence time. This combined
with decreased surface area in the larger gravel explain these findings.
Physical barriers to flow seemed to inconsistently affect
the phosphate concentration. In port 4A (area of high
flow), we found higher phosphate concentrations than in
4D and 4E (areas of low flow). However, we could not
find clear patterns elsewhere. We attribute this to
limited data samples.
Shallow ports were not sufficiently below water surface
to prevent aeration during sampling, so those data were
omitted from dissolved oxygen analysis. Subsurface
conditions in the marsh were overall anoxic, consistently
conducive to denitrification. A trend of increasing DO
with depth was evident, though differences between
medium and deep samples were not significant.
Conclusions
In our snapshot of the spatial nutrient dynamics of the Living Machine marsh, we found
that nitrate strongly correlates with chloride, a passive tracer, indicating that it is not
being processed by the marsh. However, phosphate is dynamic with depth and seems to
be partially affected by physical barriers. We determined that sulfate and DO seem
relatively unaffected by the marsh. Our experiment was limited in determining the affects
of physical barriers to flow on nutrient concentrations due to insufficient sampling ports,
and in future research we would recommend installing more ports around the tanks to
accurately measure their effect. Additionally, we recommend that future studies measure
the varied input of nutrients to the system and attempt to add a temporal layer to our
findings on spatial dynamics.
Literature Cited
Cernac, Pennino and Dyankov. 2004. Measuring Phosphorus Retention Capacity in the Marsh Substrate of an
Ecologically Engineered Wastewater Treatment Facility at Oberlin College. ENVS316 Research Project.
Haineswood and Morse. 2003. Low Organic Carbon Limits Denitrification in the Marsh of an Ecologically
Engineered Wastewater Treatment Facility at Oberlin College. ENVS316 Research Project.
McConaghie. 2003. Biotic regulation of water flow and nutrient dynamics in a constructed wastewater treatment
wetland. Senior honors thesis.
Mitsch, W.J., Cronk, J.K, Wu, X.Y. et al. Phosphorus retention in constructed fresh-water riparian marshes.
Ecological Applications 5 (3) 830-845 AUG 1995.
Petersen. 2008. Methods for Analyzing Aquatic Ecosystems. ENVS316 Manual.