Approach for evaluating LID measure layout scenarios based on random forest: Case of Guangzhou-China

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.