Abstract
Currently, with the rapid development of many cities, water problems, such as water logging and water quality deterioration, occur inevitably. Thus, sponge city construction and low impact development (LID) utilization have become more important worldwide. However, previous works have failed to address the problem of selecting an optimal LID measure layout scenario by simultaneously considering various evaluation indices without subjective factors. In this study, we applied a new and outstanding statistical classifier, random forest, to aid in addressing this conundrum. It was tested on a case study in LiWan district, Guangzhou city. The following conclusions were drawn. (1) To some extent, LID measures are capable of reducing water discharge and generation of pollutants. (2) Excluding subjective factors, random forest can select an optimal LID measure layout scenario when simultaneously considering multiple indices. This study proposed a novel and effective means to evaluate the hydrologic effects of LID measures when constructing sponge cities and provided a guide for optimizing LID layouts.
Highlights
Studies addressing water problems have a long tradition
Evaluated the benefits of low impact development-best management practices (LID-BMPs) in terms of water quantity and quality based on the storm water management model (SWMM) via a case study conducted in Suzhou, China
We tentatively explored the hydrologic effects of LID measures via a case study in
Summary
Studies addressing water problems have a long tradition. During the past decades, people across the world have been threatened by various ecological disasters, causing heavy economic losses and widespread fatalities. China and precedents of other countries, it is of great significance for China to put forward new policies suitable to its own realities, known as integrated urban water management [2]. This is the very reason the concept of sponge city in China was proposed. Evaluated the benefits of low impact development-best management practices (LID-BMPs) in terms of water quantity and quality based on the storm water management model (SWMM) via a case study conducted in Suzhou, China. Eight indices were selected as assessment criteria for each scenario Apart from these measures, random forest algorithm based on Python was applied to evaluate the comprehensive performance of each scenario. Some recommendations for sponge city construction are given at the end of this paper based on the simulation results
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