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

机译:估算日本Tone河大洪水情景下的保险住宅损失-数据集成方法

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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 largescale 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.
机译:通河上的洪水泛滥了日本最大的集水区,现在有1200万人居住,对大东京地区构成了重大风险。 2010年4月,日本中央防灾委员会的专家小组审查了大规模洪灾的可能性,并概述了大东京地区可能采取的缓解措施。所考虑的其中一种情况与1947年台风凯瑟琳(Kathleen)逝世时发生的洪水模式极为相似,可能会淹没地面以上约68万户家庭。在该报告的基础上,本研究提出了一种基于地理信息系统(GIS)的数据集成方法,以估算住宅建筑物和财物的保险损失,只是潜在财务成本的一个组成部分。使用一系列公开可用的数据(人口普查信息,位置参考数据,保险市场信息和洪水高程数据),该分析发现仅住宅物业的保险损失就可能达到约1万亿日元(125亿美元)。包括商业和工业业务在内的总保险损失可能至少是这一数字的两倍,而总经济成本又要高得多。结果对假设的洪水情况,堤防故障位置,当地洪水深度和范围,人口和建筑物高度很敏感。据估计,台风凯瑟琳之后的降雨的平均复发间隔(ARI)约为200年。但是,由于目前我们还不知道不同洪水情景的相对或联合概率,因此无法在模拟损失上加上ARI。这些情况有可能同时发生多个,或者某一地点的堤防故障可能降低下游的水位,并避免其他所有地点的故障。除保险申请外,此处介绍的空间分析对应急管理,缓解工作的成本效益和土地利用规划也有影响。

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