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Water 2018, 10(7), 894; https://doi.org/10.3390/w10070894

Approach for Evaluating LID Measure Layout Scenarios Based on Random Forest: Case of Guangzhou—China

1
School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China
2
Department of Mathematics, the College of William and Mary, Williamsburg, VA 23185, USA
3
State Key Laboratory of Subtropical Building Science, School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China
4
Guangdong Engineering Technology Research Center of Safety and Greenization for Water Conservancy Project, Guangzhou 510640, China
*
Author to whom correspondence should be addressed.
Received: 24 May 2018 / Revised: 1 July 2018 / Accepted: 1 July 2018 / Published: 4 July 2018
(This article belongs to the Section Urban Water Management)
View Full-Text   |   Download PDF [2812 KB, uploaded 4 July 2018]   |  

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. View Full-Text
Keywords: sponge city; optimal low impact development measure layout scenario; random forest sponge city; optimal low impact development measure layout scenario; random forest
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Liao, X.; Zheng, J.; Huang, C.; Huang, G. Approach for Evaluating LID Measure Layout Scenarios Based on Random Forest: Case of Guangzhou—China. Water 2018, 10, 894.

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