School of Environment, Tsinghua University, Beijing 100084, China.
College of Engineering, China Agricultural University, Beijing 100083, China.
J Environ Manage. 2015 Feb 1;149:65-76. doi: 10.1016/j.jenvman.2014.10.003. Epub 2014 Nov 1.
Low Impact Development Best Management Practices (LID-BMPs) have in recent years received much recognition as cost-effective measures for mitigating urban runoff impacts. In the present paper, a procedure for LID-BMPs planning and analysis using a comprehensive decision support tool was proposed. A case study was conducted to the planning of an LID-BMPs implementation effort at a college campus in Foshan, Guangdong Province, China. By examining information obtained, potential LID-BMPs were first selected. SUSTAIN was then used to analyze four runoff control scenarios, namely: pre-development scenario; basic scenario (existing campus development plan without BMP control); Scenario 1 (least-cost BMPs implementation); and, Scenario 2 (maximized BMPs performance). A sensitivity analysis was also performed to assess the impact of the hydrologic and water quality parameters. The optimal solution for each of the two LID-BMPs scenarios was obtained by using the non-dominated sorting genetic algorithm-II (NSGA-II). Finally, the cost-effectiveness of the LID-BMPs implementation scenarios was examined by determining the incremental cost for a unit improvement of control.
近年来，低影响开发最佳管理实践（LID-BMPs）作为减轻城市径流影响的经济有效措施得到了广泛认可。本研究提出了一种使用综合决策支持工具进行 LID-BMP 规划和分析的方法。以中国广东省佛山市某大学校园的 LID-BMPs 实施规划为例，首先通过查阅相关资料，筛选出潜在的 LID-BMPs。然后，使用 SUSTAIN 分析了四个径流控制情景，分别为：未开发情景、基础情景（无 BMP 控制的现有校园发展规划）、情景 1（成本最低的 BMPs 实施）和情景 2（BMPs 性能最大化）。还进行了敏感性分析，以评估水文和水质参数的影响。使用非支配排序遗传算法-II（NSGA-II）获得了每个 LID-BMPs 情景的最优解。最后，通过确定控制效果每提高一个单位的增量成本，来检验 LID-BMPs 实施情景的成本效益。
