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Characterization of Phosphorus Adsorption in a Constructed Wetland Receiving Agricultural Wastewater

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Paper number  052231,  2005 ASAE Annual Meeting . (doi: 10.13031/2013.19038) @2005
Authors:   G.W. Stratton, D. Gorman, A. Madani, R. Gordon
Keywords:   Constructed wetlands, phosphorus sorption, dairy wastewater, PSI, Langmuir, phosphorus

Dairy operations produce wastewater with high levels of phosphorus, which is present in both the runoff from manure storage pads and milkhouse wash water. Constructed wetlands are effective in removing nutrients and pathogens from this type of wastewater. However, wetlands are susceptible to P saturation, since P removal is limited to sedimentation and adsorption phenomena. This research examined the spatial and temporal P sorption characteristics of two constructed wetlands, one on a dairy farm and the other at a research facility. Both were monitored over two years using the Phosphorus Sorption Index (PSI) and Langmuir Isotherms. PSI values provided reliable data on P sorption profiles within the wetlands, indicating that this method is useful for determining spatial differences in P treatment capacity. P sorption capacity generally decreased as the distance from the inlet increased, although there were exceptions to this trend within selected cells. This likely resulted from short circuiting within these systems. There was conflicting information on the effect of time, as both increases and decreases in PSI values from one year to the next were documented. This indicates that the PSI model may not be appropriate for examining temporal trends or for predicting wetland longevity. Langmuir adsorption data from pooled wetland samples showed similar variability within the wetlands and adsorption maxima did not differ substantially from one year to the next. Langmuir data would be most useful for determining long term trends in wetland treatment capabilities, however, year to year variations means that data taken over longer time periods may be required to accurately determine treatment trends.

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