A probabilistic approach of assessing rainstorm-induced flood loss risk based on historical event records-case study in Hunan Province, China

作者：Du Juan; Wang Ming; Shi Peijun^*

来源：Journal of Basic Science and Engineering, 2014, 22(5): 916-927.

DOI：10.3969/j.issn.1005-0930.2014.05.008

• Business development strategy
• Direct economic loss
• Exceedance probability
• Flood disaster
• Hunan province
• Hunan province , China
• Probabilistic approaches
• Probabilistic modeling

The economic losses caused by rainstorm floods are tremendous every year in China. Flood risk is increasingly being recognized as a concern in both government and insurance company. This article employs the probabilistic model to assess the risk of direct economic losses caused by rainstorm floods in Hunan province based on historical event records from 1978 to 2007. The Monte Carlo simulation is carried out to generate the flood event table and develop exceedance probability curves for flood losses, including Occurrence Loss Exceedance Probability(OEP)and Aggregate Loss Exceedance Probability(AEP)curves. The article finally utilizes these curves to calculate the Probable Maximum Loss(PML)and Total Losses at different return periods, and to estimate Average Annual Loss(AAL)of every city in Hunan province. The study reveals that the intensity of hazards is not necessarily proportional to the magnitude of disasters. AEP curves can provide more accurate information for flood-prone areas. Meanwhile, the results indicate that the spatial distribution of flood losses is nonuniform at different return periods. For the 1000-year return period, Yiyang will become the highest risk city of flood losses;for the 100-year return period, Huaihua and Chenzhou will have largest losses among all cities, the total losses will both exceed 6 billion RMB;for the 50-year and 10-year return periods, Huaihua will remain the highest risk city of flood losses. Conversely, Zhangjiajie is the city of lightest economic losses at various risk levels. The assessment results are the data foundation for risk mapping. It can be used as a reference for policy-makers to make effective flood risk management plan. It could also serve the insurance industry for business development strategies.

• 出版日期2014