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非点源污染最佳管理措施及模拟优化研究进展 被引量:5

Best Management Practices,Simulation and Optimization for Non-point Source Pollution Control
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摘要 最佳管理措施(BMPs)是非点源污染控制和管理的重要途径,现已成功应用于多个国家和地区,而我国对BMPs的研究尚处于起步阶段。采用模型方法实现区域及流域尺度BMPs的有效实施是目前发展的必然趋势,而对单项BMP的结构、处理效果、影响因素及所需费用等的研究是BMPs模拟和优化的基础。从单项BMP的技术发展和BMPs的模拟、优化方法研究两个方面对BMPs的研究进展进行系统分析和评价:①选取滞留式、生物式、渗透式和过滤式4种类型BMPs中的典型代表性措施进行分析和评价;②从模拟预测模型、优化算法和集成技术3个方面系统分析和介绍相关的模型进展。上述研究认为,我国目前应广泛开展BMPs的基本信息研究和数据积累,在此基础上加大对模型方法的研究和应用,提高决策效率,以实现流域尺度BMPs的有效实施及非点源污染的有效控制。 Best management practices (BMPs) are an important way for non-point source pollution control and management. The BMPs have been successfully applied worldwide. However, they are still in the beginning stage in China. Model-based simulation and optimization methods are the future trend for effective implementation of BMPs at the regional and watershed scale. Therefore, it is essential to conduct a systematic survey of the structure, cost, removal efficiency of pollutant and driving factors for individual BMP. The technology development of individual BMP and the development of simulation and optimization methods of BMPs were discussed. The typical BMP was selected, analyzed and evaluated, one from de- tention type, vegetation type, infiltration type and filter type of BMPs. Systematic analysis and review were then conducted on the relative models development, including simulation and prediction models, op- timization algorithm and integration technology. It is recommended that the basic studies and data collec- tion should be conducted for BMPs development in China, and the research and application of model- based simulation and optimization methods should be enhanced to improve decision-making efficiency and achieve effective implementation of BMPs and effective control of non-point source pollution at the water- shed scale.
出处 《中国给水排水》 CAS CSCD 北大核心 2013年第12期5-10,共6页 China Water & Wastewater
基金 国家水体污染控制与治理科技重大专项(2010ZX07102-006) 教育部博士点新教师基金资助项目(20100001120020) 云南省社会发展科技计划(2010CA001)
关键词 最佳管理措施 模拟预测模型 优化算法 集成模型 best management practice simulation and prediction model optimization algorithm integrated model
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参考文献25

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