A grey fuzzy analytic hierarchy process-based flash flood vulnerability assessment in an ungauged Himalayan watershed

Dibyandu Roy (), Anirban Dhar () and Venkappayya R. Desai ()
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Dibyandu Roy: Indian Institute of Technology, Kharagpur
Anirban Dhar: Indian Institute of Technology, Kharagpur
Venkappayya R. Desai: Indian Institute of Technology, Kharagpur

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 7, No 73, 18206 pages

Abstract: Abstract Flash flood is the most recurrent natural threat in northeastern India, especially during the peak of the monsoon season. In recent decades, the frequency of flash floods has considerably increased in the Himalayan watersheds, causing enormous human suffering, infrastructure damage, ecosystem disruption, and economic losses. Considering the exponential rise in the frequency of flash flood events, identifying the Flash Flood Vulnerable Zones (FFVZs) is one of the most crucial findings to limit their negative consequences. In this study, grey fuzzy analytic hierarchy process-based model integrated with the geographic information system is implemented to assess the flash flood vulnerability in the Ranikhola watershed, East Sikkim, India. Additionally, a novel Flash Flood Vulnerability Index (FFVI) is proposed to determine the flash flood vulnerability that takes into account twelve natural and anthropogenic parameters. Further, the FFVI map is classified into three FFVZs: low, moderate, and high. The effectiveness of the methodology implemented is judged by the high EV value (6.4286) and the comparison parameter. The harshest conclusion of this analysis, the major cities, such as Gangtok, Ranipool, and Singtam, are designated high FFVZ. The sensitivity analysis results show the LULC has the maximum positive influence on high FFVZ.

Keywords: Flash flood vulnerability index (FFVI); Analytic hierarchy process (AHP); Grey clustering; Fuzzy analytic hierarchy process (FAHP); Geographic information systems (GIS) (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-023-03385-9

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