Scholarlink

<p>Surat, a city in Gujarat, India has confronted large-scale flood events over the last few years. The present study attempts to identify flood susceptibility zones along the lower course of the Tapi River flowing through Surat. A cluster of 11 parameters, including elevation, slope, stream order, contour, drainage density, flow accumulation, soil, rainfall, topographic wetness index (TWI), land use and land cover, and normalized difference vegetation index (NDVI) has been used. An integrated approach of remote sensing and GIS coupled with the analytical hierarchy process (AHP), was applied to identify the flood susceptibility zones of the study area. Thematic maps of the parameters were reclassified after assigning ranks to different classes. A pair-wise comparison matrix among all the parameters was prepared using AHP to determine the relative weight of each parameter. Finally, a flood susceptibility zoning map of the study area was prepared by multiplying the reclassified values with the weighted values. The influence value of the elevation was assigned the highest weight in the final weighted overlay analysis that combined all the components. The output zones were divided into five flood-prone zones very high, high, moderate, low, and very low. The consequence of the study revealed that 34.62, 12.80, 16.39, 16.98, and 19.2% areas fall under zones very high, high, moderate, low, and very low, respectively.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Assessment of urban flood risk of the lower Tapi basin through an integrated approach using GIS based AHP

  • 期刊论文

  • 发表日期：

    2025年9月25日

查看全文
  • Aayushi Jariwala,
  • Prasit Agnihotri

摘要

Surat, a city in Gujarat, India has confronted large-scale flood events over the last few years. The present study attempts to identify flood susceptibility zones along the lower course of the Tapi River flowing through Surat. A cluster of 11 parameters, including elevation, slope, stream order, contour, drainage density, flow accumulation, soil, rainfall, topographic wetness index (TWI), land use and land cover, and normalized difference vegetation index (NDVI) has been used. An integrated approach of remote sensing and GIS coupled with the analytical hierarchy process (AHP), was applied to identify the flood susceptibility zones of the study area. Thematic maps of the parameters were reclassified after assigning ranks to different classes. A pair-wise comparison matrix among all the parameters was prepared using AHP to determine the relative weight of each parameter. Finally, a flood susceptibility zoning map of the study area was prepared by multiplying the reclassified values with the weighted values. The influence value of the elevation was assigned the highest weight in the final weighted overlay analysis that combined all the components. The output zones were divided into five flood-prone zones very high, high, moderate, low, and very low. The consequence of the study revealed that 34.62, 12.80, 16.39, 16.98, and 19.2% areas fall under zones very high, high, moderate, low, and very low, respectively.