Remote sensing-based 2D hydrodynamic modeling and assessment of the 2014 flood in the Jhelum river basin
Article
| Article Title | Remote sensing-based 2D hydrodynamic modeling and assessment of the 2014 flood in the Jhelum river basin |
|---|---|
| ERA Journal ID | 213704 |
| Article Category | Article |
| Authors | Mansha, Rizwan, Haider, Sajjad, Azmat, Muhammad, Gabriel, Hamza Farooq and Ullah, Fahim |
| Editors | Islam, M.N. |
| Journal Title | Modeling Earth Systems and Environment |
| Journal Citation | 12 |
| Article Number | 84 |
| Number of Pages | 20 |
| Year | 2026 |
| Publisher | Springer |
| Place of Publication | Germany |
| ISSN | 2363-6203 |
| 2363-6211 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1007/s40808-026-02724-9 |
| Web Address (URL) | https://link.springer.com/article/10.1007/s40808-026-02724-9 |
| Abstract | 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. |
| Keywords | Flood simulation; Disaster management ; Remote sensing; HEC–RAS; GIS; DEM; Natural hazards |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 370401. Computational modelling and simulation in earth sciences |
| 330499. Urban and regional planning not elsewhere classified | |
| Byline Affiliations | National University of Sciences and Technology, Pakistan |
| School of Science, Engineering & Digital Technologies- Surveying & Built Env |
https://research.usq.edu.au/item/1013z2/remote-sensing-based-2d-hydrodynamic-modeling-and-assessment-of-the-2014-flood-in-the-jhelum-river-basin
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