Multi-source geospatial analysis of the August 2025 cloudburst-induced flood in district Buner, Pakistan
DOI:
https://doi.org/10.47264/idea.nasij/1.1.%25xKeywords:
Normalized difference index, Flood hazard index, Cloudburst, Flood, Remote sensing, GIS, Flood prone area, Flood hazard areas, Spatial modellingAbstract
This study analyzes the cloudburst-induced flood in Buner, Pakistan, in August 2025 through remote sensing and GIS-based multi-parametric criteria. The aim of this work is to define flood-prone areas by investigating the topography and validating the satellite-derived flood hazard areas for spatial modeling. Moreover, the CHIRPS daily precipitation, AW3D30 DEM, and Normalized Difference Water Index (NDWI) are studied from satellite images for the pre-and post-event. The rainfall analysis estimated the precipitation to be high, with a value of 66 mm/day on 15 August 2025, to induce a cloudburst event. The terrain survey revealed that the flood affected the low-elevation (357 to 900 m elevation) region with a slope of less than 6° to incur surface runoff. According to the weighted overlay model, three paramount parameters have been added (rainfall, 50%, slope 30%, and elevation 20%) in the Flood Hazard Index to subdivide the region of Buner into four zones of the hazard, i.e., Low, Moderate, High, and Very High. The results of testing the actual magnitude of the flood indicated that there was a good spatial compatibility of 88% of the flooding area, which was enclosed by the Very High Hazard area, thus providing evidence of the model. This study demonstrated the efficiency of the integration of remote sensing indices, rainfall data, and topographic parameters into a GIS environment to perform a rapid evaluation of the risks of floods.
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