Estimating insured residential losses from large flood scenarios on the Tone River, Japan – a data integration approach

摘要

Flooding on the Tone River, which drains the largest catchment area in Japan and is now home to 12 million people, poses significant risk to the Greater Tokyo Area. In April 2010, an expert panel in Japan, the Central Disaster Prevention Council, examined the potential for large-scale flooding and outlined possible mitigation measures in the Greater Tokyo Area. One of the scenarios considered closely mimics the pattern of flooding that occurred with the passage of Typhoon Kathleen in 1947 and would potentially flood some 680 000 households above floor level. Building upon that report, this study presents a Geographical Information System (GIS)-based data integration approach to estimate the insurance losses for residential buildings and contents as just one component of the potential financial cost. Using a range of publicly available data – census information, location reference data, insurance market information and flood water elevation data – this analysis finds that insurance losses for residential property alone could reach approximately 1 trillion JPY (US$ 12.5 billion). Total insurance losses, including commercial and industrial lines of business, are likely to be at least double this figure with total economic costs being much greater again. The results are sensitive to the flood scenario assumed, position of levee failures, local flood depths and extents, population and building heights. The Average Recurrence Interval (ARI) of the rainfall following Typhoon Kathleen has been estimated to be on the order of 200 yr; however, at this juncture it is not possible to put an ARI on the modelled loss since we cannot know the relative or joint probability of the different flooding scenarios. It is possible that more than one of these scenarios could occur simultaneously or that levee failure at one point might lower water levels downstream and avoid a failure at all other points. In addition to insurance applications, spatial analyses like that presented here have implications for emergency management, the cost-benefit of mitigation efforts and land-use planning.