Assessment of flood susceptibility in Cachar district of Assam, India using GIS-based multi-criteria decision-making and analytical hierarchy process

Preeti Barsha Borah (), Arpana Handique, Chandra Kumar Dutta, Diram Bori, Shukla Acharjee and Lanusashi Longkumer
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Preeti Barsha Borah: Nagaland University
Arpana Handique: Dibrugarh University
Chandra Kumar Dutta: Dibrugarh University
Diram Bori: Dibrugarh University
Shukla Acharjee: Dibrugarh University
Lanusashi Longkumer: Nagaland University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 6, No 53, 7625-7648

Abstract: Abstract Flood is a recurring natural hazard in many parts of the state of Assam causing severe damage to both people and infrastructure. Situating in the southern part of the state; Cachar district poses an annual flood challenge due to natural and anthropogenic factors which impact the socio-economic condition of the region. Drained by the Barak River, Cachar faces severe floods during monsoon season. Despite recurring floods, the area lacks proper mitigation measures and an effective flood prediction and mapping system. Integration of GIS and Remote Sensing techniques and analysis of various hydrological parameters can contribute to the flood management efforts and planning. This paper used an integrated approach utilizing GIS based Analytical Hierarchy Process (AHP) and Multi Criteria Decision Making (MCDM) methods to assess the flood risk. Ten contributing factors including elevation, slope, precipitation, Land Use Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), Topographic Wetness Index (TWI), distance from the road, distance from the river, drainage density and population density were analyzed. The result reveals five flood susceptibility zones; very low (− 9.12–− 5.58), low (− 5.57–− 3.72), moderate (− 3.71–− 1.42), high (− 1.41–1.77), and very high (1.78–13.45) which covers 31.24% (1225.72 km2), 35.73% (1401.78 km2), 19.74% (774.36 km2), 10.79% (423.61 km2) and 2.48% (97.47 km2). The generated flood susceptibility map was then overlayed in the population density map to understand flood vulnerability in different parts of the area. The areas with high susceptibility zones have high population density. Silchar, Katigorah and Kalain areas are more vulnerable to flooding.

Keywords: GIS; Remote Sensing; Multi criteria decision making; Analytical hierarchy process; Flood susceptibility (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-024-07100-3

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