流域不同尺度非点源污染的最佳管理措施配置研究

The effort to manage non-point source pollution at the watershed scale is an ongoing challenge that needs to take into account trade-offs between environmental and economic objectives. Best management practices (BMPs) have been shown to be effective at reducing nutrient and sediment inputs to surface waters. Many studies have focused on a single type or a single spatial scale of the BMPs configuration and benefit evaluation. Nevertheless, the effectiveness in improving water quality at different scale is not clear. And also very little information is currently available demonstrating if a suite of BMPs, when implemented simultaneously, work synergistically or whether some BMPs cancel the NPS pollution reduction benefits of others. The present study attempts to develop a geographical implementation framework for NPS pollution control. This framework is meant to suggest the optimal location for placing multiple BMPs at different spatial scales in watershed, by determining the trade-off among economic and multiple environmental objectives. Chaohe River, one of the drainage watersheds of Miyun Reservoir, is chosen for evaluation of the technique proposed here. This optimization technique incorporates three existing methods：a critical source areas identifier integrated with PI and HSPF model, an aggregated/targeted allocation approach, which serves as the optimisation engine for the selection and placement of BMPs, and an integrated benefit indices for the estimation of the BMP implementation levels. The methods developed here could provide a theoretical basis and technical guidance for conducting NPS pollution management in a large watershed, and there will be important scientific significance and wide application value for promoting water conservation and watershed health.

流域尺度的非点源污染控制管理需要综合考虑社会、经济、环境与生态效益等多目标间的权衡，也是目前研究中的难点。最佳管理措施（Best management practices, BMPs）是当前预防和削减农业非点源污染有效手段。以往对BMPs的研究多集中于单一类型或单一空间尺度上的BMPs配置和效益评价，而对不同BMPs组合的综合效益和多尺度BMPs空间配置模式研究缺乏探讨。本项目拟以密云水库上游的潮河流域为研究区，从关键源区识别、BMPs组合优化、BMPs空间配置、费用效益分析等方面着手，应用风险评价、模型模拟和统计学方法，探讨地块、子流域、流域不同尺度上BMPs组合的优化配置模式，构建适合区域特点的非点源污染控制BMPs体系。本项目的研究成果为有效控制非点源污染提供理论依据和技术指导，促进水源地保护和流域健康，有十分重要的科学意义和广泛的应用价值。

非点源污染具有广泛的时空差异性，在污染控制管理中，还需综合考虑社会、经济、环境生态效益等多目标的权衡，这是目前非点源污染研究中的难点和控制治理的重点。最佳管理措施（Best management practices, BMPs）是预防和削减农业非点源污染有效手段。本项目以密云水库上游潮河流域为研究区，从关键源区识别、BMPs组合优化、空间配置、费用效益分析等方面着手，采用野外监测、风险评价、模型模拟和统计学方法，从提升BMPs （Best management practices）实施效率的角度出发，基于ArcSWAT模型和多元统计分析方法识别不同空间尺度非点源污染物负荷分布特征并进行污染分区，探讨地块、子流域、流域不同尺度上BMPs组合的优化配置模式，提出基于尺度收缩和尺度扩展过程的多尺度非点源污染特征识别-地块尺度优化方案获取-流域尺度成本效益分析的BMPs优化配置技术，建立兼顾流域水质显著提升以及最佳管理措施可执行性的流域非点源污染控制方案，提出能够兼顾流域水环境质量明显改善与尺度效应对最佳管理措施配置影响的污染控制技术体系。研究成果为非点源污染的有效控制提供理论依据和技术指导；在促进水源地保护和流域健康方面，具有重要的科学意义和广泛的应用价值。