Urban flood-bearing vulnerability evaluation based on the moment estimate weighting and improved gray target model

Author:

Yan Dengming12,Su Liu1,Liu Simin3,Lv Hong12,Lin Jin3,Yu Zhilei4,Cao Lucong3

Affiliation:

1. a Yellow River Engineering Consulting Co., Ltd, Zhengzhou 450003, China

2. b Key Laboratory of Water Management and Water Security for Yellow River Basin, Ministry of Water Resources (Under Construction), Zhengzhou 450003, China

3. c Development Research Center, National Forestry and Grassland Administration, Beijing 100714, China

4. d School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China

Abstract

ABSTRACT Increasingly severe flooding seriously threatens urban safety. A scientific urban flood-bearing vulnerability assessment model is significant to improve urban risk management capacity. The gray target model (GTM) has advantages in urban flood-bearing vulnerability assessment. However, indicator correlation and single bull's-eye are commonly neglected, leading to defective evaluation results. By integrating the four base weights, an improved weighting method based on the moment estimate was proposed. Then, the marginal distance was used to quantify the indicator correlation, and the TOPSIS model was introduced to define the relative bull's-eye distance. Thus, an improved gray target evaluation method was established. Finally, an urban flood-bearing vulnerability evaluation model was presented based on the moment estimate weighting-improved GTM. In this study, Zhengzhou City, China, was taken as an example. The spatial and temporal changing characteristics of the flood-bearing vulnerability of Zhengzhou from 2006 to 2020 were investigated. The results show that: (1) On the temporal scale, the disaster-bearing vulnerability of Zhengzhou City showed an upward trend during the 15 years; (2) On the spatial scale, Guancheng District of Zhengzhou City had the relatively highest vulnerability to urban flooding. This study is expected to provide a scientific reference for urban flood risk management.

Funder

National Natural Science Foundation of China

Chongqing Municipal Key Research and Development Program of China

Publisher

IWA Publishing

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