Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS

Abstract

Floods are a widespread natural disaster with substantial economic implications and far-reaching consequences. In Northern Pakistan, the Hunza-Nagar valley faces vulnerability to floods, posing significant challenges to its sustainable development. This study aimed to evaluate flood risk in the region by employing a GIS-based Multi-Criteria Decision Analysis (MCDA) approach and big climate data records. By using a comprehensive flood risk assessment model, a flood hazard map was developed by considering nine influential factors: rainfall, regional temperature variation, distance to the river, elevation, slope, Normalized difference vegetation index (NDVI), Topographic wetness index (TWI), land use/land cover (LULC), curvature, and soil type. The analytical hierarchy process (AHP) analysis assigned weights to each factor and integrated with geospatial data using a GIS to generate flood risk maps, classifying hazard levels into five categories. The study assigned higher importance to rainfall, distance to the river, elevation, and slope compared to NDVI, TWI, LULC, curvature, and soil type. The weighted overlay flood risk map obtained from the reclassified maps of nine influencing factors identified 6% of the total area as very high, 36% as high, 41% as moderate, 16% as low, and 1% as very low flood risk. The accuracy of the flood risk model was demonstrated through the Receiver Operating Characteristics-Area Under the Curve (ROC-AUC) analysis, yielding a commendable prediction accuracy of 0.773. This MCDA approach offers an efficient and direct means of flood risk modeling, utilizing fundamental GIS data. The model serves as a valuable tool for decision-makers, enhancing flood risk awareness and providing vital insights for disaster management authorities in the Hunza-Nagar Valley. As future developments unfold, this study remains an indispensable resource for disaster preparedness and management in the Hunza-Nagar Valley region.