Risk Assessment of Flood Disaster in the Mid-lower Reaches of the Yangtze

Bian Jie; Li Shuanglin; He Jinhai

Vol.22, NO.5, 2011

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Article Navigation > Journal of Applied Meteorological Science > 2011 > 22(5): 604-611

Bian Jie, Li Shuanglin, He Jinhai. Risk assessment of flood disaster in the Mid-lower Reaches of the Yangtze. J Appl Meteor Sci, 2011, 22(5): 604-611.

Citation:

Bian Jie, Li Shuanglin, He Jinhai. Risk assessment of flood disaster in the Mid-lower Reaches of the Yangtze. J Appl Meteor Sci, 2011, 22(5): 604-611.

Bian Jie, Li Shuanglin, He Jinhai. Risk assessment of flood disaster in the Mid-lower Reaches of the Yangtze. J Appl Meteor Sci, 2011, 22(5): 604-611.

Citation:

Bian Jie, Li Shuanglin, He Jinhai. Risk assessment of flood disaster in the Mid-lower Reaches of the Yangtze. J Appl Meteor Sci, 2011, 22(5): 604-611.

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Risk Assessment of Flood Disaster in the Mid-lower Reaches of the Yangtze

Bian Jie^{1,2
,
,},
Li Shuanglin¹,
He Jinhai²

1.
Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
2.
College of Atmospheric Science, Nanjing University of Information Science & Technology, Nanjing 210044

Received Date: 2010-11-29
Rev Recd Date: 2011-06-24
Publish Date: 2011-10-31

Abstract

Abstract

Flood disasters caused by heavy rain events occur frequently in the mid-lower reaches of the Yangtze in monsoonal rainy season. The risk of heavy rain events is an important topic in meteorological research in China. Therefore, risk rank of flood disaster in six provinces in the mid-lower reaches of the Yangtze (Hubei, Hunan, Anhui, Jiangxi, Jiangsu and Zhejiang) are assessed based on most recently updated meteorological disaster losses dataset collected by the Ministry of Civil Affairs, National Disaster Reduction Centre of China from 2000 to 2008.First, losses due to flood disasters are classified and quantified by using the method of grey association analysis. The results show that the grey association method is reasonable in disaster situation grading and loss ranking, and the results are basically in agreement with the actual situation. Then an integrated index series in the recent 9 years is established. In addition, the model is very practical and flexible because the numbers of the grade indexes are not limited. Second, since there are not enough integrated historical disaster indexes, an information diffusion based fuzzy method is introduced to optimize the historical disaster data and then the risk in each province is assessed individually. The risk rank results show substantial difference in these provinces. Although medium risk is universal in all the provinces with the occurrence probability of once in one to two years, high risk is relatively more frequent in three provinces, Anhui, Hubei and Hunan, which approximately tallies with the practical situation. This also suggests an efficiency of the present risk-assessment model in processing inadequately long records and deserves extensive use.
- the mid-lower reaches of the Yangtze;
- grey association;
- integrated indexes of flood disaster;
- information diffusion;
- risk assessment

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References(22)

Figures and Tables

Fig. 1 The probability density curve of synthetic disaster index in the mid-lower Reaches of the Yangtze

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Table 1 Flood grades and standard of classification for individual index

灾害等级	受灾人口/人	农作物受灾面积/hm²	直接经济损失/元
巨灾	(1×10⁷，+∞)	(6.667×10⁶，+∞)	(1×10¹⁰，+∞)
大灾	(1×10⁶，1×10⁷)	(6.667×10⁵，6.667×10⁶)	(1×10⁹，1×10¹⁰)
中灾	(1×10⁵，1×10⁶)	(6.667×10⁴，6.667×10⁵)	(1×10⁸，1×10⁹)
小灾	(1×10⁴，1×10⁵)	(6.667×10³，6.667×10⁴)	(1×10⁷，1×10⁸)
微灾	(1×10³，1×10⁴)	(6.667×10²，6.667×10³)	(1×10⁶，1×10⁷)

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Table 2 The relationship between individual conversion function and flood grades

灾情等级	转换函数值
巨灾	0.8~1
大灾	0.6~0.8
中灾	0.4~0.6
小灾	0.2~0.4
微灾	0~0.2

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Table 3 The corresponding relationship between the correlation degree and flood grades

灾害等级	关联度
巨灾	0.9~1
大灾	0.8~0.9
中灾	0.7~0.8
小灾	0.6~0.7
微灾	0.5~0.6

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Table 4 The synthetic disaster index and afflicted grades for flood disaster of each province

年份	江苏		浙江		安徽		江西		湖北		湖南
年份	灾情指数	灾害等级	灾情指数	灾害等级	灾情指数	灾害等级	灾情指数	灾害等级	灾情指数	灾害等级	灾情指数	灾害等级
2000	0.7802	中灾	0.7779	中灾	0.7299	中灾	0.7447	中灾	0.7599	中灾	0.7447	中灾
2001	0.7159	中灾	0.7519	中灾	0.6867	小灾	0.7140	中灾	0.7366	中灾	0.7642	中灾
2002	0.7225	中灾	0.7676	中灾	0.7703	中灾	0.7799	中灾	0.7959	中灾	0.8323	大灾
2003	0.7107	中灾	0.6855	小灾	0.8517	大灾	0.7735	中灾	0.8090	大灾	0.7947	中灾
2004	0.6806	小灾	0.6403	小灾	0.7059	中灾	0.7300	中灾	0.7718	中灾	0.7890	中灾
2005	0.6687	小灾	0.6775	小灾	0.8009	大灾	0.7659	中灾	0.7854	中灾	0.7799	中灾
2006	0.7928	中灾	0.6809	小灾	0.7480	中灾	0.7579	中灾	0.7165	中灾	0.7898	中灾
2007	0.7720	中灾	0.6490	小灾	0.8194	大灾	0.7108	中灾	0.8040	大灾	0.7729	中灾
2008	0.6900	小灾	0.7427	中灾	0.7444	中灾	0.7815	中灾	0.8053	大灾	0.7977	中灾

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Table 5 The risk level of six provinces in the mid-lower Reaches of the Yangtze

省份	巨灾	大灾	中灾	小灾	微灾
江苏	0	0.0537	0.5583	0.3878	0.0002
浙江	0	0.0238	0.4675	0.4964	0.0123
安徽	0.004	0.2455	0.5736	0.1765	0.0003
江西	0	0.0059	0.9307	0.0633	0
湖北	0	0.2226	0.7480	0.0294	0
湖南	0	0.2123	0.7871	0.0005	0

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Table 6 The flooding frequency of each province along the mid-lower Reaches of the Yangtze during 2000—2008

省份	巨灾	大灾	中灾	小灾	微灾
江苏	0	0	0.67	0.33	0
浙江	0	0	0.44	0.56	0
安徽	0	0.33	0.56	0.11	0
江西	0	0	1.00	0	0
湖北	0	0.33	0.67	0	0
湖南	0	0.11	0.89	0	0

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