Flood disaster risk assessment of rural housings--a case study of Kouqian Town in China.
Floods are a devastating kind of natural disaster. About half of the population in China lives in rural areas. Therefore, it is necessary to assess the flood disaster risk of rural housings. The results are valuable for guiding the rescue and relief goods layout. In this study, we take the severe flood disaster that happened at Kouqian Town in Jilin, China in 2010 as an example to build an risk assessment system for flood disaster on rural housings. Based on the theory of natural disaster risk formation and "3S" technology (remote sensing, geography information systems and global positioning systems), taking the rural housing as the bearing body, we assess the flood disaster risk from three aspects: hazard, exposure and vulnerability. The hazard presented as the flood submerging range and depth. The exposure presented as the values of the housing and the property in it. The vulnerability presented as the relationship between the losses caused by flood and flood depth. We validate the model by the field survey after the flood disaster. The risk assessment results highly coincide with the field survey losses. This model can be used to assess the risk of other flood events in this area.
School of Environment, Northeast Normal University, Changchun 130024, China. zhangq941@nenu.edu.cn.
Qi
Q
Zhang
School of Environment, Northeast Normal University, Changchun 130024, China. zhangjq022@nenu.edu.cn.
Jiquan
J
Zhang
School of Environment, Northeast Normal University, Changchun 130024, China. jack860614@sina.com.
Liupeng
L
Jiang
School of Environment, Northeast Normal University, Changchun 130024, China. liuxp912@nenu.edu.cn.
Xingpeng
X
Liu
School of Environment, Northeast Normal University, Changchun 130024, China. gis@nenu.edu.cn.
Zhijun
Z
Tong
D002681:China; D004190:Disasters; D055868:Floods; D040362:Geographic Information Systems; D006798:Housing; D008962:Models, Theoretical; D058998:Remote Sensing Technology; D018570:Risk Assessment; D012424:Rural Population