Indian Statistical Institute, Kolkata, India.
Statistical Quality Control and Operations Research Unit, Indian Statistical Institute, Kolkata, India.
Risk Anal. 2019 Jul;39(7):1615-1633. doi: 10.1111/risa.13333. Epub 2019 May 28.
This article models flood occurrence probabilistically and its risk assessment. It incorporates atmospheric parameters to forecast rainfall in an area. This measure of precipitation, together with river and ground parameters, serve as parameters in the model to predict runoff and subsequently inundation depth of an area. The inundation depth acts as a guide for predicting flood proneness and associated hazard. The vulnerability owing to flood has been analyzed as social vulnerability , vulnerability to property , and vulnerability to the location in terms of awareness . The associated risk has been estimated for each area. The distribution of risk values can be used to classify every area into one of the six risk zones-namely, very low risk, low risk, moderately low risk, medium risk, high risk, and very high risk. The prioritization regarding preparedness, evacuation planning, or distribution of relief items should be guided by the range on the risk scale within which the area under study falls. The flood risk assessment model framework has been tested on a real-life case study. The flood risk indices for each of the municipalities in the area under study have been calculated. The risk indices and hence the flood risk zone under which a municipality is expected to lie would alter every day. The appropriate authorities can then plan ahead in terms of preparedness to combat the impending flood situation in the most critical and vulnerable areas.
本文通过概率模型预测洪水的发生及其风险评估。该模型将大气参数纳入其中，以预测特定区域的降雨情况。该降雨量测量值与河流和地面参数相结合，作为模型的参数，用于预测径流量，进而预测区域的洪水淹没深度。洪水淹没深度可作为预测洪水易发程度和相关危害的指标。洪水的脆弱性已从社会脆弱性、财产脆弱性和位置感知脆弱性三个方面进行了分析。对每个区域的相关风险进行了评估。风险值的分布可用于将每个区域划分为六个风险区之一，即极低风险、低风险、中低风险、中风险、高风险和极高风险。根据风险范围，应针对准备情况、疏散计划或救灾物资分配进行优先级排序，研究区域属于风险范围内的哪个区域。洪水风险评估模型框架已在实际案例研究中进行了测试。已计算出研究区域内每个直辖市的洪水风险指数。风险指数，进而预期的直辖市所属洪水风险区，每天都会发生变化。然后，相关当局可以提前做好准备，在最关键和最脆弱的地区应对即将发生的洪水情况。
