Liu Yaoze, Guo Tian, Wang Ruoyu, Engel Bernard A, Flanagan Dennis C, Li Siyu, Pijanowski Bryan C, Collingsworth Paris D, Lee John G, Wallace Carlington W
Department of Environmental and Sustainable Engineering, University at Albany, State University of New York, 1400 Washington Avenue, Albany, NY 12222, USA.
National Center for Water Quality Research, Heidelberg University, 310 E Market Street, Tiffin, OH 44883, USA.
Sci Total Environ. 2019 Nov 15;691:685-696. doi: 10.1016/j.scitotenv.2019.07.175. Epub 2019 Jul 12.
To address the harmful algal blooms problem in Lake Erie, one solution is to determine the most cost-effective strategies for implementing agricultural best management practices (BMPs) in the Maumee River watershed. An optimization tool, which combines multi-objective optimization algorithms, SWAT (Soil and Water Assessment Tool), and a computational efficient framework, was created to optimally identify agricultural BMPs at watershed scales. The optimization tool was demonstrated in the Matson Ditch watershed, an agricultural watershed in the Maumee River basin considering critical areas (25% of the watershed with the greatest pollutant loadings per area) and the entire watershed. The initial implementation of BMPs with low expenditures greatly reduced pollutant loadings; beyond certain levels of pollutant reductions, additional expenditures resulted in less significant reductions in pollutant loadings. Compared to optimization for the entire watershed, optimization in critical areas can greatly reduce computational time and obtain similar optimization results for initial reductions in pollutant loadings, which were 10% for Dissolved Reactive Phosphorus (DRP) and 38% for Total Phosphorus (TP); however, for greater reductions in pollutant loadings, critical area optimization was less cost-effective. With the target of simultaneously reducing March-July DRP/TP losses by 40%, the optimized scenario that reduced DRP losses by 40% was found to reduce 51.1% of TP; however, the optimized scenario that reduced TP losses by 40% can only decrease 11.3% of DRP. The optimization tool can help stakeholders identify optimal types, quantities, and spatial locations of BMPs that can maximize reductions in pollutant loadings with the lowest BMP costs.
为解决伊利湖有害藻华问题，一种解决方案是确定在莫米河流域实施农业最佳管理实践（BMPs）的最具成本效益的策略。创建了一种优化工具，该工具结合了多目标优化算法、SWAT（土壤和水资源评估工具）以及一个计算效率高的框架，以在流域尺度上最优地识别农业BMPs。该优化工具在马特森沟渠流域进行了演示，马特森沟渠流域是莫米河流域的一个农业流域，考虑了关键区域（流域中每单位面积污染物负荷最大的25%区域）和整个流域。以低支出初步实施BMPs可大幅减少污染物负荷；在污染物减少达到一定水平后，额外支出导致污染物负荷减少的幅度较小。与对整个流域进行优化相比，在关键区域进行优化可大幅减少计算时间，并在污染物负荷的初步减少方面获得类似的优化结果，溶解活性磷（DRP）的初步减少量为10%，总磷（TP）的初步减少量为38%；然而，对于更大幅度的污染物负荷减少，关键区域优化的成本效益较低。以同时将3月至7月的DRP/TP损失减少40%为目标，发现将DRP损失减少40%的优化方案可使TP减少51.1%；然而，将TP损失减少40%的优化方案只能使DRP减少11.3%。该优化工具可帮助利益相关者识别BMPs的最优类型、数量和空间位置，从而以最低的BMP成本最大限度地减少污染物负荷。
