Flood vulnerability assessment using an integrated approach of multi-criteria decision-making model and geospatial techniques

被引:0
|
作者
K. S. Vignesh
I. Anandakumar
Rajeev Ranjan
Debashree Borah
机构
[1] SRMIST,School of Public Health
[2] Centre for Natural Hazards and Disaster Studies,Civil Engineering Department
[3] University of Madras,Department of Geography
[4] Indian Institute of Technology (IIT),undefined
[5] Delhi,undefined
[6] Hauz Khas,undefined
[7] New Delhi,undefined
[8] Guwahati University,undefined
关键词
Flood hazard; AHP; MCDM; Vulnerable zones; FVZ;
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学科分类号
摘要
Floods are one of the most devastating natural catastrophes, always associated with massive disruption to humans, land, and the economy. The current research focusses on the identification of Flood Vulnerable Zones (FVZ) of Kanyakumari district with the integration of Remote Sensing (RS) and Geographic Information System (GIS), and the Multi-criteria Decision-Making Analysis (MCDM)-based Analytical Hierarchy Process (AHP) model in the geospatial environment. The weights derived from 10 × 10 decision matrix of AHP model for the flood inducing factors are reflecting their varied priorities from high to low priority as rainfall (0.22), slope (0.124), drainage density (0.154), Land Use Land Cover (LULC) (0.153), Digital Elevation Model (DEM) (0.109), Soil (0.068), geology (0.052), geomorphology (0.048), Surface Runoff (0.042) and Topographic Wetness Index (TWI) (0.03), respectively. Consistency Ratio (CR) value obtained in this case is equal to 0.093 (< 0.1) signifies the acceptance of the derived weights. The more is the weightage given to the parameters, more significance is of the factor towards the occurrence of the flood hazard. The outcomes of the research found that the very high and highly vulnerable zones are spreading over a vast expanse of the district, which are situated in the south, south-east, south-west, and in some pockets of middle and north-east. The use of such a decision-making model-based approach is helpful in the identification and prediction of the susceptible sites, further helps the policymakers in hazard mitigation and decision-making planning.
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页码:767 / 781
页数:14
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