4.6 Article

Integrated framework for flood relief package (FRP) allocation in semiarid region: a case of Rel River flood, Gujarat, India

期刊

NATURAL HAZARDS
卷 100, 期 1, 页码 279-311

出版社

SPRINGER
DOI: 10.1007/s11069-019-03812-z

关键词

AHP; Flash flood; Flood hazard; Morphometric; RS; GIS

资金

  1. Space Application Center-Indian Space Research Organization (SAC-ISRO)
  2. National Bureau of Soil Survey and Land Use Planning (NBSS LUP)
  3. National Resources Information System
  4. Survey of India (SOI)
  5. Central Water Commission (CWC)
  6. State Water Data Center (SWDC)
  7. PDPU
  8. Irrigation department

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Flash flood is disastrous; it losses property and life. Its effect is intensified while it occurs in semiarid region because of less preparedness. The present case conferred about a flash flood in semiarid region in Gujarat which was affected by flood in 2015 and 2017. Massive loss of lives and properties has been observed after the event. Now, recuperating the region against flood losses, it was a prime requirement to distribute the flood relief packages to the flood-susceptible areas. To identify the flood hazards and flood risk and assess the flood vulnerability in Rel River catchment, the region is divided into 52 micro-watersheds using RS and GIS techniques. The morphology of the Rel River catchments has been explored using the morphometric analysis. The priority rank and category for each micro-watershed were assigned based on compound factor values, whereas compound factor was calculated using weighted sum analysis techniques. Flood hazard zone map was prepared, and flood vulnerability has been characterized from very low to very high. Furthermore, the multi-criteria analysis was used to calculate the risk factor for the basin and AHP-MCE method was used to find the normalized weights of each factor (LU/LC, CF, soil, slope, drainage density) that were significant to the flood disaster. The integration of flood hazard map along with these parameters helped to understand the sensitivity of flash floods at different locations within the study area. Flood risk map was further analyzed at village level, and it has been identified that 17 out of 39 villages were at high risk, 12 villages were at moderate risk and 10 villages were at low risk. The study helped to clearly identify villages vulnerable to flood risk where more relief and flood insurance packages need to be allotted. Thus, the present method and integrated approach would be a useful tool for the decision maker to distribute the flood relief package in flash flood-prone area.

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