Author(s): Chao Dai, Xiaosheng Qin, Huai Cheng Guo

Linked Author(s): Xiaosheng Qin

Keywords: Best management practices, SWAT, agricultural nonpoint sources, genetic algorithm

Abstract: Excessive agricultural non-point source (ANPS) loads such as nitrogen and phosphorus have aroused serious concern around the world due to their stimulation effects on lake eutrophication. The best management practices (BMPs) are deemed effective approaches in mitigating the ANPS pollutions. However, identification of BMP placement schemes is a challenging task and involves many considerations, like cost benefits, hydrological processes, landscape condition, and water quality responses. In this study, we attempt to rely on the soil and water assessment tool (SWAT) and the genetic algorithm (GA) to find out the optimal allocations of BMPs for controlling ANPS at a watershed level. Methodology wise, the SWAT model help forecasting nutrient dynamics under different BMPs scenarios and the GA tool aided solving the optimization model to explore the best spatial placement of BMPs. The objective of the optimization model is to minimize the overall system cost of deploying the BMPs, and its constraints comprised control of exceedance frequencies for both total nitrogen (TN) and total phosphorus (TP). This study investigated the feasibility of combing different BMPs cost-effectively by using an optimization model and shed some lights for watershed managers on how to conduct a scientific decision-making under complex conditions

DOI:

Year: 2017