Scholarlink

<p>Extreme weather events, including cloudbursts and flash floods, are increasing in frequency and intensity due to global warming, posing major challenges for flood prediction in steep, short river basins of the Western Ghats. Flash floods in these humid tropical catchments are particularly destructive because of their sudden onset, high peak discharge, and limited warning time, resulting in severe impacts on life, infrastructure, and fragile mountain ecosystems. Despite advances in remote sensing (RS), GIS, and machine-learning techniques, reliable flood-susceptibility mapping remains limited in data-scarce tropical regions, and few studies integrate geomorphology-driven susceptibility assessment with flood-magnitude indices or examine interdependencies among controlling parameters. In this context, the present study evaluates flash-flood susceptibility in the Swarna River Basin of the Central Western Ghats, with specific emphasis on the Yennehole sub-basin, by integrating eleven hydrologically relevant parameters within an AHP-based Flash Flood Susceptibility Index (FFSI) framework, complemented by the Flash Flood Magnitude Index (FFMI). The basin-average FFMI (1.24) is approximately 4.5 times higher than the global river average, highlighting the extreme flash-flood potential of the region. Although very low susceptibility dominates at the basin scale, high and very high susceptibility zones are consistently associated with steep slopes, high elevation, rugged terrain, and short concentration times. Validation using 38 independent flood points from NDEM yielded a ROC AUC of 0.99, demonstrating excellent predictive performance. The integrated susceptibility–magnitude framework effectively captures spatial variability in flash-flood behavior, is transferable to similar small tropical basins, and provides a robust scientific basis for flood-risk management, land-use planning, and policy formulation.</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

Demarcation and validation of flood susceptibility hazard zone mapping by AHP for the Swarna River Basin, Southern Part of the West Coast India

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月7日

查看全文
  • K. T. Nagamani,
  • T. N. Bhagwat,
  • Busnur Rachotappa Manjunatha,
  • H. K. Ramaraju

摘要

Extreme weather events, including cloudbursts and flash floods, are increasing in frequency and intensity due to global warming, posing major challenges for flood prediction in steep, short river basins of the Western Ghats. Flash floods in these humid tropical catchments are particularly destructive because of their sudden onset, high peak discharge, and limited warning time, resulting in severe impacts on life, infrastructure, and fragile mountain ecosystems. Despite advances in remote sensing (RS), GIS, and machine-learning techniques, reliable flood-susceptibility mapping remains limited in data-scarce tropical regions, and few studies integrate geomorphology-driven susceptibility assessment with flood-magnitude indices or examine interdependencies among controlling parameters. In this context, the present study evaluates flash-flood susceptibility in the Swarna River Basin of the Central Western Ghats, with specific emphasis on the Yennehole sub-basin, by integrating eleven hydrologically relevant parameters within an AHP-based Flash Flood Susceptibility Index (FFSI) framework, complemented by the Flash Flood Magnitude Index (FFMI). The basin-average FFMI (1.24) is approximately 4.5 times higher than the global river average, highlighting the extreme flash-flood potential of the region. Although very low susceptibility dominates at the basin scale, high and very high susceptibility zones are consistently associated with steep slopes, high elevation, rugged terrain, and short concentration times. Validation using 38 independent flood points from NDEM yielded a ROC AUC of 0.99, demonstrating excellent predictive performance. The integrated susceptibility–magnitude framework effectively captures spatial variability in flash-flood behavior, is transferable to similar small tropical basins, and provides a robust scientific basis for flood-risk management, land-use planning, and policy formulation.