Remote sensing-based flash flood mapping and damage assessment in Dera Ismail Khan, Khyber Pakhtunkhwa, Pakistan

Abstract

Flash floods pose significant risks due to their rapid onset and destructive potential, causing an estimated 5000 fatalities and billions of dollars in damage annually worldwide. The Dera Ismail Khan district in Pakistan, highly susceptible to flooding, highlights the urgent need for a robust flood risk management framework, especially in the aftermath of the devastating 2022 flash flood, the most severe on record for the region. This study employed remote sensing (RS) and Geographic Information System (GIS) techniques to analyze the flood’s spatiotemporal dynamics and assess the resulting damage. Flood maps were generated using Landsat 9 images using the Modified Normalized Difference Water Index (MNDWI) and classified land use using the supervised maximum likelihood method. The findings revealed that the flood inundated approximately 2876 km² for about 1.5 months, significantly impacting agricultural and urban areas, with widespread damage to crops and infrastructure. This research highlights the importance of spatiotemporal analysis in improving flood management in Dera Ismail Khan and can serve as a model for similar assessments in other regions globally.