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Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

机译:法国保险市场遭受洪水影响的分析:将河流溢流和地表径流结合在一起的随机模型

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摘要

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible (but which have not yet occurred) flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2010 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90 % of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff, due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of the CCR (Caisse Centrale de Reassurance) claim database have shown that approximately 45 % of the insured flood losses are located inside the floodplains and 45% outside. Another 10% is due to sea surge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: a generation of fictive river flows based on the historical records of the river gauge network and a generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (Macif) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).
机译:对法国保险市场在全国范围内的洪水风险进行分析,必须将所有可能(但尚未发生)洪水情况的概率事件集的生成与危害和破坏模型结合起来。在这项研究中,危害和损害模型是根据1995-2010年的历史事件集进行校准的,包括危害结果(河流流量,水灾地区)和损失估算。因此,在模拟概率事件集之前已知单个事件损失的确定性估计中的不确定性。要考虑至少90%的保险洪水损失,概率事件集必须将流域斜坡上的河流溢流(大小集水区)与由于强降雨造成的地表径流结合起来。确实,对CCR(放心中央储蓄银行)索赔数据库的内部研究表明,大约45%的保险洪水损失位于洪泛区内部,而45%位于外部。另外10%是由于海浪洪水和地下水位上升。在这种方法中,两种独立的概率方法相结合以创建一个单一的洪灾损失分布:基于河流水位网络的历史记录生成的虚拟河流流量,以及在小流域校准的1958- 2010年法国法兰西岛降雨数据库SAFRAN。用确定性模型模拟概率事件集中的所有事件。此危害和破坏分布用于模拟保险公司(Macif)在全国范围内的洪水损失,并生成与危害返回期相关的洪水区域。洪水地图涉及河流溢流和地表水径流。这些地图的验证是通过与位于小流域(下游Argens)上的索赔数据的地址进行比较来进行的。

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