Flood Risk Assessment Using Morphometric and Hydrological Analysis in Afghanistan: An Integrated RS and GIS Approach

The increasing frequency and severity of climatic-driven extreme events such as heavy precipitation, floods, and droughts have raised global concerns due to their substantial social, economic, and environmental impacts. Among these, floods are considered the most devastating, causing extensive damage to life, property, and infrastructure.

This study focuses on assessing flood risks in Afghanistan, a country highly vulnerable to climatic disasters due to decades of conflict, environmental degradation, and limited mitigation capacities. Using remote sensing (RS) data and geographic information systems (GIS) techniques, the study evaluates flood hazard and vulnerability as key components of flood risk at the sub-basin and provincial levels. Principal component analysis (PCA) is employed to identify governing environmental, climatic and social indicators of flood risk. Additionally, the Analytical Hierarchy Process (AHP) is used to rank and prioritize the relative importance of various indicators in the hazard and vulnerability index, ensuring logical consistency through a systematic evaluation and minimizing bias by reducing subjective influence in decision-making.

The findings reveal that the eastern and northeastern regions of Afghanistan, mainly overlying the Amu and Kabul River basins, are severely exposed to very high flood hazards. This is primarily due to the combined effects of precipitation, topography, and drainage characteristics, all of which contribute to rapid runoff and increased flooding potential. The vulnerability assessment indicates that the densely populated rural areas in the northern and eastern regions are more susceptible to flood risk. Significant land use changes further intensify vulnerability, increasing the exposure of communities to flooding.  Overall, the study identifies key flood-prone areas, providing essential guidance for policymakers. These findings offer a roadmap for resource allocation with an aim of developing targeted mitigation strategies, ultimately enhancing community preparedness and building a sustainable adaptive capacity to manage future flood risks effectively.