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<p>Floods pose a significant threat to both infrastructure and human lives, particularly in regions with inadequate flood management strategies. This study employs a multi-criteria decision-making approach using the VIKOR method to assess flood risk in the Rel River watershed. Geospatial techniques, including remote sensing and GIS, were utilized to delineate 52 micro-watersheds and evaluate flood hazards and vulnerabilities. Key hazard indicators, such as elevation, slope, soil type, flow accumulation, and precipitation, were integrated with vulnerability factors, including land use/land cover (LULC), population density, distance from hospitals, Normalized Difference Vegetation Index (NDVI), and land surface temperature (LST). The decision matrix was normalized to ensure comparability, and weightage was assigned to each criterion for accurate risk classification. The results categorize micro-watersheds into five flood risk levels: very high, high, medium, low, and very low. Twenty micro-watersheds covering 213.15 km<sup>2</sup> were identified as high to very high-risk zones, while 32 micro-watersheds (228.41 km<sup>2</sup>) were classified under low to moderate risk. The findings highlight the importance of integrating hydrological modeling with geospatial analysis for effective flood risk assessment. The study underscores the necessity for improved flood mitigation strategies, including better drainage infrastructure, sustainable land-use planning, and enhanced early warning systems. The flood risk map generated provides critical insights for decision-makers to prioritize flood preparedness measures and resource allocation, ultimately fostering resilience in flood-prone regions.</p>

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Integrating Earth Observations and Multi-Criteria Decision Making for Flood Risk Assessment

  • 期刊论文

  • 发表日期：

    2025年6月17日

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  • Keval H. Jodhani,
  • Dhruvesh Patel,
  • N. Madhavan,
  • Nitesh Gupta,
  • Sudhir Kumar Singh

摘要

Floods pose a significant threat to both infrastructure and human lives, particularly in regions with inadequate flood management strategies. This study employs a multi-criteria decision-making approach using the VIKOR method to assess flood risk in the Rel River watershed. Geospatial techniques, including remote sensing and GIS, were utilized to delineate 52 micro-watersheds and evaluate flood hazards and vulnerabilities. Key hazard indicators, such as elevation, slope, soil type, flow accumulation, and precipitation, were integrated with vulnerability factors, including land use/land cover (LULC), population density, distance from hospitals, Normalized Difference Vegetation Index (NDVI), and land surface temperature (LST). The decision matrix was normalized to ensure comparability, and weightage was assigned to each criterion for accurate risk classification. The results categorize micro-watersheds into five flood risk levels: very high, high, medium, low, and very low. Twenty micro-watersheds covering 213.15 km2 were identified as high to very high-risk zones, while 32 micro-watersheds (228.41 km2) were classified under low to moderate risk. The findings highlight the importance of integrating hydrological modeling with geospatial analysis for effective flood risk assessment. The study underscores the necessity for improved flood mitigation strategies, including better drainage infrastructure, sustainable land-use planning, and enhanced early warning systems. The flood risk map generated provides critical insights for decision-makers to prioritize flood preparedness measures and resource allocation, ultimately fostering resilience in flood-prone regions.