1. 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. 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 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. 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. Conclusions Literature Cited Results and Discussion Methods 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. 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 R 2 value. This indicates that there is biogeochemical activity in the marsh that affects phosphate levels. Wetland Diagram 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. 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. 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). 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. 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. 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. [Cl - ] (mg/l)