State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, PR China.
State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, PR China.
Sci Total Environ. 2020 Jul 10;725:138091. doi: 10.1016/j.scitotenv.2020.138091. Epub 2020 Apr 2.
Optimizing long-term best management practices (BMPs) is of vital importance for water quality management, especially for nonpoint source (NPS) pollution. However, changes in the efficiency of BMPs over time have not been incorporated and a proper method for determining long-term BMP configuration strategies is still lacking. In this study, the long-term BMP optimization method (LBMP-OM) was developed for recommending the BMP maintenance-replacement strategies and optimizing the BMP configuration. This new method was then tested in the Daning Watershed, Three Gorges Reservoir Region, China. Based on the results, a 1-year maintenance period and a 3-year replacement period was recommended for a filter strip by considering a changing BMP effectiveness rather than a constant effectiveness and by discussing the rationality of experts' suggestions for maintenance and replacement strategies regarding the regulation of NPS pollution. At the watershed scale, the total cost dropped by 57.36% by introducing the LBMP-OM method compare to the original method. This new method extended the long-term management and configuration of BMPs.
优化长期最佳管理实践（BMP）对于水质管理至关重要，特别是对于非点源（NPS）污染。然而，BMP 效率随时间的变化尚未纳入其中，并且缺乏确定长期 BMP 配置策略的适当方法。在本研究中，开发了长期 BMP 优化方法（LBMP-OM），以推荐 BMP 维护-更换策略并优化 BMP 配置。然后，该新方法在中国三峡库区大宁流域进行了测试。基于结果，建议考虑到 BMP 效果随时间的变化而不是恒定效果，并讨论了专家对维护和更换策略的合理性，建议采用过滤带的 1 年维护期和 3 年更换期来调节 NPS 污染。在流域尺度上，与原始方法相比，引入 LBMP-OM 方法可将总成本降低 57.36%。这种新方法扩展了 BMP 的长期管理和配置。
