A GIS-Based Support Vector Machine Model for Flash Flood Vulnerability Assessment and Mapping in China

Junnan Xiong,Jin Li,Liang Guo,Weiming Cheng,Nan Wang

doi:10.3390/ijgi8070297

Abstract

Flash floods are one of the natural disasters that threaten the lives of many people all over the world every year. Flash floods are significantly affected by the intensification of extreme climate events and interactions with exposed and vulnerable socio-economic systems impede regional development processes. Hence, it is important to estimate the loss due to flash floods before the disaster occurs. However, there are no comprehensive vulnerability assessment results for flash floods in China. Fortunately, the National Mountain Flood Disaster Investigation Project provided a foundation to develop this proposed assessment. In this study, an index system was established from the exposure and disaster reduction capability categories, and is based on analytic hierarchy process (AHP) methods. We evaluated flash flood vulnerability by adopting the support vector machine (SVM) model. Our results showed 439 counties with high and extremely high vulnerability (accounting for 10.5% of the land area and corresponding to approximately 100 million hectares (ha)), 571 counties with moderate vulnerability (accounting for 19.18% of the land area and corresponding to approximately 180 million ha), and 1128 counties with low and extremely low vulnerability (accounting for 39.43% of the land area and corresponding to approximately 370 million ha). The highly-vulnerable counties were mainly concentrated in the south and southeast regions of China, moderately-vulnerable counties were primarily concentrated in the central, northern, and southwestern regions of China, and low-vulnerability counties chiefly occurred in the northwest regions of China. Additionally, the results of the spatial autocorrelation suggested that the “High-High” values of spatial agglomeration areas mainly occurred in the Zhejiang, Fujian, Jiangxi, Hunan, Guangxi, Chongqing, and Beijing areas. On the basis of these results, our study can be used as a proposal for population and building distribution readjustments, and the management of flash floods in China.

Highlights

Worldwide mountain communities have continuously suffered from flash floods, which have regularly caused losses of agricultural land, buildings, infrastructure, and life
The exposure assessment factors (ENI, roads, Flood control project (FCP), and buildings) were expressed as vector maps, with the exception of the human activity factors (POD, gross domestic product (GDP), and Land use type (LUT)), which were expressed in a raster format
A new vulnerability model was proposed based on previous studies that have investigated flash flood vulnerability

Summary

Introduction

Worldwide mountain communities have continuously suffered from flash floods, which have regularly caused losses of agricultural land, buildings, infrastructure, and life. A statistic from the National Mountain Flood Disaster Investigation Project shows that approximately 60,000 flash floods occurred in China from 1950 to 2015. These disasters caused more than 230,000 deaths, damaged 36.3 million houses, transferred more than 43.2 million people, and resulted in 250 million yuan in direct economic losses [5]. To alleviate the adverse effects of flash floods on society, it is necessary to quantitatively evaluate community vulnerability and analyze various reduction measures of vulnerability. Such studies can strengthen our understanding of the community vulnerabilities resulting from flash floods, and such an endeavor will contribute to the development of prevention and control measures of flash floods

Methods

Results

Discussion

Conclusion