Abstract:

Introduction: Flash floods are among the most devastating natural disasters, impacting both rural and urban areas by causing extensive damage to communities, infrastructure, and livelihoods. Effective flash flood mapping is essential for assessing risks in flood-prone regions, involving a comprehensive decision-making framework that considers multiple criteria. Globally, flash floods result in significant casualties and damage, underscoring the need for enhanced mapping and damage assessment to mitigate their impacts. In Pakistan, the Dera Ismail Khan (DI Khan) district is particularly vulnerable to flash floods, with the 2022 event marking the most severe flood in the district's history.

Materials and Methods: To address this, we employed Remote Sensing (RS) and Geographic Information System (GIS) techniques to map the spatiotemporal dynamics of the flood and assess the resulting damage. Landsat 9 data were utilized for flood mapping and damage assessment. We developed flood maps for pre-flood, during-flood, and post-flood scenarios using the Modified Normalized Difference Water Index (MNDWI). Land use and land cover were classified using the Supervised Maximum Likelihood technique, with spatial training and validation samples sourced from Google Earth Pro.

Results: Our results indicate that the flood inundated an area of approximately 2,876 km², lasting around one and a half months, and caused substantial damage to agricultural lands and built-up areas.

Conclusion: This study provides valuable insights into flood management in DI Khan, offering strategies to improve flood management practices. Furthermore, this approach can be applied to analyze flash floods in other regions globally, enhancing our ability to manage and mitigate the impacts of such events.