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<p>Flood modeling and hazard mapping are essential for effective disaster management. This paper models the 2014 flood along a 72&#xa0;km stretch of the Jhelum River between Mangla Dam and Rasul Barrage in Pakistan using a 2D Hydrologic Engineering Center River Analysis System (HEC–RAS) framework integrated with remote sensing (RS) and Geographic Information System (GIS) techniques. Three digital elevation models (DEMs), namely SRTM, ALOS, and ASTER, along with MODIS and Landsat imagery, were used for terrain modeling and flood extent validation. The simulated flood depths and velocities were compared with observed flow data at the Rasul Barrage gauge station, while flood extents were validated with satellite-derived inundation maps. The proposed model displayed superior performance when comparing the maximum flood extents of SRTM and ALOS, with 72% and 71% fitness. It matched the area with a percentage of 84% and 83% and overestimation with a rate of 16% and 17%, respectively. The performance of ASTER, on the other hand, was below par, with a measure of fit at 50%, a matching area of 80%, and overestimation at a rate of 42%. Overall, the average flood extents of SRTM and ALOS showed superior performance to that of ASTER. The results highlight the suitability of SRTM and ALOS DEMs for reliable flood modeling and hazard assessment in data-scarce regions. Relevant disaster management authorities can use this approach for effective disaster management.</p>

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Remote sensing-based 2D hydrodynamic modeling and assessment of the 2014 flood in the Jhelum river basin

  • 期刊论文

  • 发表日期：

    2026年2月9日

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  • Rizwan Mansha,
  • Sajjad Haider,
  • Muhammad Azmat,
  • Hamza Farooq Gabriel,
  • Fahim Ullah

摘要

Flood modeling and hazard mapping are essential for effective disaster management. This paper models the 2014 flood along a 72 km stretch of the Jhelum River between Mangla Dam and Rasul Barrage in Pakistan using a 2D Hydrologic Engineering Center River Analysis System (HEC–RAS) framework integrated with remote sensing (RS) and Geographic Information System (GIS) techniques. Three digital elevation models (DEMs), namely SRTM, ALOS, and ASTER, along with MODIS and Landsat imagery, were used for terrain modeling and flood extent validation. The simulated flood depths and velocities were compared with observed flow data at the Rasul Barrage gauge station, while flood extents were validated with satellite-derived inundation maps. The proposed model displayed superior performance when comparing the maximum flood extents of SRTM and ALOS, with 72% and 71% fitness. It matched the area with a percentage of 84% and 83% and overestimation with a rate of 16% and 17%, respectively. The performance of ASTER, on the other hand, was below par, with a measure of fit at 50%, a matching area of 80%, and overestimation at a rate of 42%. Overall, the average flood extents of SRTM and ALOS showed superior performance to that of ASTER. The results highlight the suitability of SRTM and ALOS DEMs for reliable flood modeling and hazard assessment in data-scarce regions. Relevant disaster management authorities can use this approach for effective disaster management.