贾海峰, 姚海蓉, 唐颖, YU Shawlei. 城市降雨径流控制LID BMPs规划方法及案例[J]. 水科学进展, 2014, 25(2): 260-267.
引用本文: 贾海峰, 姚海蓉, 唐颖, YU Shawlei. 城市降雨径流控制LID BMPs规划方法及案例[J]. 水科学进展, 2014, 25(2): 260-267.
JIA Haifeng, YAO Hairong, TANG Ying, YU Shawlei. LID-BMPs planning for urban runoff control and case study[J]. Advances in Water Science, 2014, 25(2): 260-267.
Citation: JIA Haifeng, YAO Hairong, TANG Ying, YU Shawlei. LID-BMPs planning for urban runoff control and case study[J]. Advances in Water Science, 2014, 25(2): 260-267.

城市降雨径流控制LID BMPs规划方法及案例

LID-BMPs planning for urban runoff control and case study

  • 摘要: 借鉴国外城市降雨径流控制的理念和实践,通过对国内外城市降雨径流低影响开发型最佳管理措施(LID BMPs)研究和分析,提出了城市降雨径流控制LID BMPs规划方法体系。选择广东省环境保护职业技术学院佛山校区为研究区域,以SUSTAIN系统作为规划支持工具,在适用LID BMPs措施筛选的基础上,进行了LID BMPs措施的选址、布局研究。设计了开发前情景、开发基础情景、经济适用型BMPs情景(情景1)和功效最大化BMPs情景(情景2)4种不同的情景方案,进行降雨径流量(总径流量和峰值流量)和径流水质(SS、COD、TN、TP)的模拟,得到了情景1和情景2的径流量和水质的控制效益。以年径流量削减比作为优化目标,对情景1和情景2两种情景方案进行了优化,给出了最具成本-效益的规划情景方案。

     

    Abstract: Low Impact Development type's Best Management Practices (LID-BMPs) have been regarded as cost-effective measures for mitigating urban runoff impacts. However, as the implementations of LID-BMPs are interacted with many factors, the research on LID-BMPs planning is still lag behind expectations. Based on the survey of LID-BMPs research and practices, a novel method for LID-BMPs planning is proposed to meet the needs of LID-BMPs implementations to China. A college campus in the Foshan city of China is chosen as a case study site to test the proposed method. Four planning scenarios for the college development are proposed, which are the natural condition before development, the existing campus development plan without LID BMPs, a least-cost LID BMPs implementation scenario (i.e., scenario 1) and a maximized LID BMPs performance scenario (i.e., scenario 2). System for Urban Stormwater Treatment and Analysis Integration (SUSTAIN) is a decision-support GIS tool developed by the U.S. Environmental Protection Agency for strategically placing BMPs in urban watersheds. SUSTAIN is used in this study to support the scenario optimization. The scenarios analysis emphasizes on the effects of runoff quantity (runoff volume and peak flow) and quality (SS, COD, TN, TP) controls. The scenario optimization uses the reduction rate of annual runoff volume as the objective. Scenario 1 and scenario 2 are further optimized by SUSTAIN, and the best cost-effective scenario is obtained.

     

/

返回文章
返回