CN 11-5366/S     ISSN 1673-1530
“风景园林,不只是一本期刊。”

基于 NSGA-II 算法的集雨型绿地低影响开发设施规模优化计算方法及应用 ——以南阳院士小镇为例

Optimal Calculation Method of Size of LID Facilities for Rainwater Harvesting Green Space Based on NSGA-II Algorithm and Application: A Case Study of Nanyang Academician Town

  • 摘要: 目前,在集雨型绿地设计过程中,进行低影响开发(low impact development,简称LID)设施规模设计时存在目标单一、缺乏可量化规模依据等现象,且布设效率低下,雨洪模拟和设计流程衔接不畅。在参数化设计平台Grasshopper中建立多目标优化平台,以雨洪控制效果和建设成本为目标,运用NSGA-II算法对LID设施规模变量进行优化求解,从而在设计前期为LID设施规模设计提供定量依据。在此基础上,将研究成果应用于南阳院士小镇集雨型绿地设计项目,并与传统开发方法进行比较,结果表明该优化计算方法可高效地为LID设施规模设计提供科学的定量依据。根据计算结果,发现在研究区选用的LID设施组合条件下,LID设施的建设成本和雨洪控制效益符合边际递减规律,因此LID设施规模须与海绵规划要求匹配,在一定条件下,适当提升透水铺装和生物滞留设施的比例有利于提升LID设施的性价比。研究成果可以为今后集雨型绿地设计提供新思路。

     

    Abstract: In the process of designing rainwater harvesting green space, the present method of determining the scale of low impact development (LID) facilities is based on single objective, which is lack of evidence and inefficient, hence the connection between rain flood simulation and design process is poor. This study attempts to establish a multi-objective optimization platform in the parameterized design platform Grasshopper, setting the effect of stormwater control and construction cost as the objective functions, and using NSGA-II algorithm to determine the scale of LID facilities. The results serve as a quantitative basis for the scale design of LID facilities in the early stage of design. In addition, the new platform is applied to the rainwater harvesting green space design project of Nanyang Academician Town, and compared with traditional development methods. The results show that in the study area, properly increasing the proportion of permeable pavement and bio-retention cell is conducive to improving the performance price ratio of LID facilities. The more cost input of LID facilities would not lead to a better result, so it is necessary to select an appropriate one according to the requirements of sponge-city documents. The research results can provide new ideas for the design of rainwater harvesting green space in the future.

     

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