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The evacuation of the population from flood-affected regions is a non-structural measure to mitigate flood hazards. Shelters used for this purpose usually accommodate a large number of flood evacuees for a temporary period. Floods during a pandemic result in a compound hazard. Evacuations under such situations are difficult to plan as social distancing is nearly impossible in the highly crowded shelters. This results in a multi-objective problem with conflicting objectives of maximizing the number of evacuees from flood-prone regions and minimizing the number of infections at the end of the shelter’s stay. To the best of our knowledge, such a problem is yet to be explored in literature. Here we develop a simulation-optimization framework, where multiple objectives are handled with a max–min approach. The simulation model consists of an extended Susceptible—Exposed—Infectious—Recovered—Susceptible model. We apply the proposed model to the flood-prone Jagatsinghpur district in the state of Odisha, India. We find that the proposed approach can provide an estimate of people required to be evacuated from individual flood-prone villages to reduce flood hazards during the pandemic. At the same time, this does not result in an uncontrolled number of new infections. The proposed approach can generalize to different regions and can provide a framework to stakeholders to manage conflicting objectives in disaster management planning and to handle compound hazards.

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It is undeniable that coastal regions worldwide are facing unprecedented damages from catastrophic floods attributable to storm-tide (tidal) and extreme rainfall (pluvial). For flood-risk assessment, although recognizing compound impact of these drivers is a conventional practice, the marginal/individual impacts cannot be overlooked. In this letter, we propose a new measure, Tide-Rainfall Flood Quotient (TRFQ), to quantify the driver-specific flood potential of a coastal region arising from storm-tide or rainfall. A set of inundation and hazard maps are derived through a series of numerical and hydrodynamic flood model simulations comprising of design rainfall and design storm-tide. These experiments are demonstrated on three different geographically diverse flood-affected coastal regions in India. The new measure throws light on existing knowledge gaps on the propensity of coastal flooding induced by the marginal/individual contribution of storm-tide and rainfall. It shall prove useful in rationalizing long-term flood management strategies customizable for storm-tide and pluvial dominated global coastal regions.

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