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Changing of flood risk due to climate and development in Huaihe River basin, China.

Authors :
Wu, Yenan
Zhong, Ping-an
Xu, Bin
Zhu, Feilin
Ma, Biao
Source :
Stochastic Environmental Research & Risk Assessment; May2017, Vol. 31 Issue 4, p935-948, 14p
Publication Year :
2017

Abstract

Assessing the response of flood risk caused by climate change and social development is very important in terms of determining high risk areas in different periods as well as making disaster mitigating plans. We establish a flood risk assessment model based on geographic information system and natural disaster risk assessment theory. In order to compare the index value in different periods and spaces, we utilize the spatial and temporal standardization method to standardized index. To avoid one-sidedness caused by using one weight calibration method only, we employ the least square method to synthesize weights determine by the Analytic Hierarchy Process (AHP) method and the Entropy weight method. We adopt the observed data of the Huaihe River basin from 1960 to 2010 to assess the changing of flood risk between period I (1960-1980) and period II (1980-2010). After pre-processing the atmosphere-ocean coupled global circulation models (AOGCM) data, including bias correction and downscaling, we use the corrected data to predict the flood risk during future period III (2010-2040). The results show that high risk areas and moderate to high risk areas during period I take up 17.68 and 33.88 % of the total area of the Huaihe River basin, respectively. During period II, the high risk areas show an increasing percent change of 1.93 % and a decreasing trend in moderate to high risk areas of 3.8 %. Compared with period II, the high risk areas and the moderate to high risk areas during period III show an increasing trend of 8.02 and 0.77 %, which is the result of the combined effects of climate change and social development. The results presented here can provide useful information for decision-makers. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14363240
Volume :
31
Issue :
4
Database :
Complementary Index
Journal :
Stochastic Environmental Research & Risk Assessment
Publication Type :
Academic Journal
Accession number :
122540779
Full Text :
https://doi.org/10.1007/s00477-016-1262-2