Hydrodynamic modelling and vulnerability analysis to assess flood risk in a dense Indian city using geospatial techniques

Sutapa Bhattacharjee (), Pramod Kumar, Praveen K. Thakur and Kshama Gupta
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Sutapa Bhattacharjee: Indian Institute of Technology
Pramod Kumar: Indian Institute of Remote Sensing
Praveen K. Thakur: Indian Institute of Remote Sensing
Kshama Gupta: Indian Institute of Remote Sensing

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 105, issue 2, No 43, 2117-2145

Abstract: Abstract Urban flooding and waterlogging are causing menace in many cities around the world from the perspective of day-to-day functioning, health and hygiene, communication, and the consequent damages they cause to urban environment. The present study is an attempt to understand the urban flood risks in parts of Bhubaneswar City, India, based on its hydrodynamic set-up and level of urbanisation. The Storm Water Management Model is used for peak flow analysis, and the flooding extent has been assessed while taking into consideration the elevation, slope, land use/land cover (LULC) and design Storm Water Drain (SWD) infrastructure of the city. The micro-watersheds for each SWD are delineated using digital surface model derived from airborne Light Detection and Ranging (LiDAR) data (1 m), and the LULC information is obtained from high-resolution optical remote sensing data. After the model simulation, it is estimated that peak runoff is relatively higher, i.e. 0.1–0.5 cumecs for a large number of micro-watersheds, even rising to more than 1.5 cumecs for some, indicating the severity of urban floods in the city. After integrating the simulated flooding pattern with the vulnerability associated with socio-economic characteristics of urban dwellers, the flood risk has been assessed. The study suggests that capacity of design SWD systems needs augmentation according to present and predicted flooding conditions for the city.

Keywords: Urban flood; SWMM; Hazard; Risk assessment (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11069-020-04392-z

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