Probabilistic Modeling of Flood Hazard and its Risk Assessment for Eastern Region of India
Pratyay Manna,
Mohammed Zafar Anis,
Prasun Das and
Soumya Banerjee
Risk Analysis, 2019, vol. 39, issue 7, 1615-1633
Abstract:
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 (VS), vulnerability to property (VP), and vulnerability to the location in terms of awareness (VA). 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.
Date: 2019
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https://doi.org/10.1111/risa.13333
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Persistent link: https://EconPapers.repec.org/RePEc:wly:riskan:v:39:y:2019:i:7:p:1615-1633
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