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    Performance Analysis of an Urban Stormwater Best Management Practice Retrofit

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    Simko_AJ_T_2014.pdf (8.505Mb)
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    Date
    2014-09-22
    Author
    Simko, Andrew Jack
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    Abstract
    Historically, the primary objective of traditional stormwater best management practices (BMPs) was to attenuate peak runoff discharges from urban areas. There has been growing demand to construct BMPs that improve stormwater runoff quality to reduce pollutant loading into downstream water bodies. A BMP located in Herndon, Virginia was retrofitted in 2009. Previously a dry detention pond, the new BMP design contains permanent wet pools as well as elements of Low Impact Development practices. A performance analysis was conducted on the retrofit to determine if the BMP was removing pollutants from stormwater runoff. Two mass-based methods were utilized for the performance analysis: the Summation of Loads Method and Effluent Probability Method. The Kaplan-Meier method and Robust Regression on ordered statistics (ROS) were used to make it possible to include censored datasets in the analysis. Analysis with the SOL method showed removal of suspended sediment, nitrogen, iron, and copper. Export of dissolved solids, phosphorus, organic carbon, and manganese was observed. The results of the Effluent Probability Method showed statistically significant reductions of sediment, iron, and copper across the entire range of monitored storm event sizes (p-value≤0.05). There was no statistical difference between the influent and effluent loads of nitrogen. Negative performance of dissolved solids, phosphorus, organic carbon, and manganese were observed for the entire range of monitored storm event sizes. The results of both methods indicated that the BMP retrofit is effectively removing sediment but failing to achieve significant nutrient reductions. This may be due to the creation of anoxic conditions from the oxygen demand of the micropool sediments and microbial degradation of vegetation within the BMP. Removal of the sediment bed and harvesting of the vegetation would likely improve the performance of the BMP.
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    http://hdl.handle.net/10919/64931
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