4.8 Article

Incorporating receiving waters responses into the framework of spatial optimization of LID-BMPs in plain river network region

期刊

WATER RESEARCH
卷 224, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.watres.2022.119036

关键词

LID-BMPs; Simulation -optimization; Spatial optimization; Receiving waters responses

资金

  1. China Postdoctoral Science Foundation [2021M691769]
  2. National Natural Science Foundation of China [52070112, 41890823, 7181101209]

向作者/读者索取更多资源

This study emphasizes the significance of incorporating receiving waters responses into the spatial allocation optimization of LID-BMPs. By integrating a coupling model and an algorithm, a general simulation-optimization framework for LID-BMPs layout was proposed, leading to cost savings and more efficient solutions. The results highlight the importance of considering receiving waters responses and refined spatial allocation for optimal design of LID-BMPs.
Deep insights into the receiving waters responses to optimal spatial allocation of LID-BMPs are considered extremely important. This study addressed the urgent need to incorporate receiving waters responses into the spatial allocation optimization of LID-BMPs and demonstrated the efficiency of the approach to guide watershed management. The integration of an overland-river coupling model and the NSGA-III algorithm resulted in the proposal of a general simulation-optimization framework for the optimal layout of LID-BMPs. The coupled model was swapped out for the surrogates to increase computational efficiency. When 40.71%, 36.06%, and 61.80% reductions in runoff volume, flood volume, and TP concentration are achieved, the newly proposed framework can save 34.44% and 16.31% cost compared to the approach that does not consider receiving waters responses and refined spatial allocation, respectively. Results indicate that the incorporation of receiving waters responses and refined spatial allocation are essential for the optimal design of LID-BMPs. This new framework offers the potential for more cost-effective high-cost solutions. The results of spatial optimization are significantly influenced by imperviousness.

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