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Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework
Citation:
Yang, G. AND Elly Best. Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework. JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, 161:252-260, (2015).
Impact/Purpose:
Public
Description:
Best management practices (BMPs) are perceived as being effective in reducing nutrient loads transported from non-point sources (NPS) to receiving water bodies. The objective of this study was to develop a modeling-optimization framework that can be used by watershed management planners to find cost-effective solutions of BMP placement to attain nutrient load reduction targets, by integrating a GIS-based BMP siting method, a WQM-TMDL-N modeling approach to estimate total nitrogen (TN) loading, and a multi-objective optimization tool. This framework can be expanded to a regional scale conveniently because NHDPlus catchment served as its spatial computational unit, enabling us to maximize the usage of publicly available data. Wetland restoration and buffer strip implementation were used as two BMP categories, with different complexities of spatial analysis for site identification, to explore the performance of this framework. The two objective functions were to minimize both TN loading and BMP cost during the optimization process. In the Pareto-optimal front of wetland placement, results of the maximum load reduction scenario indicated a TN load reduction by 10% through wetland restoration covering merely 1% of the watershed, while the minimum scenario results indicated a load reduction by 4% covering about 20% of the maximum scenario area. Optimization can provide a range of trade-offs between the two objective functions. The present study demonstrates the potential of this modeling-optimization framework to find cost-effective solutions to solve water quality issues at various spatial scales, and to meet a water quality target, e.g., 20% TN load reduction, under different conditions.
