Flash Flood Hazard Mapping Using Analytical Hierarchy Process (AHP) and GIS Application: In the Barzan Area of Iraqi Kurdistan Region

Addressing the combined hazards of flooding and water scarcity in the same region requires a large-scale, evidence-based approach to disaster risk reduction. This investigation presents the evaluation of flood hazard area on a large scale for flood-prone Barzan region as a multi-criteria index, located 80 km northeast of Erbil City- Iraqi Kurdistan Region. The Flood Hazard Index (FHI) is delimited, and GIS spatial analysis is utilized to predict its value. The methodology, integrates information from ten parameters: Topographic of Wetness Index (TWI), Elevation (E), Slope (S), Precipitation (P), Land Use Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), Distance from River (D1), Distance from Road (D2), Density of Drainage (D3), with type of Soil (S). The importance of each characterizes in flood amount and severity is reflected through weight values calculated utilizing the Analyzing Hierarchy Process (AHP). Flood hazard mapping is generated by superimposing information from the parameters based on their weight values. The generated flood hazard map for the area under study, classifying flood vulnerability into five categories: very low, low, moderate, high, and very high. The generated flood hazard map for the study area indicates that regions with very high and high flood susceptibility are predominantly located in the central, southeastern, and southwestern parts, with a smaller area in the northwest. The distribution of the area across different flood susceptibility levels is as follows: 14% falls into the very high category, 24% into the high category, 23% into the moderate category, 25% into the low category, and 14% into the very low category. Areas with very high flood vulnerability are primarily situated near rivers, particularly the Greater Zab and Rezan Rivers. The method's accuracy is validated through sensitivity analysis, exploring various weight values and alternative scenarios. The sensitivity analysis leads to a revised index FHIS and flood mapping, reaffirming the methodology's robustness. Comparison with historical flood actions confirms the validity of the proposed approach. The methodology therefore suggests itself as a basis for large-scale predictive flood hazard mapping. The parameters of this approach also suggest it as a potential basis for planning Nature-based Solutions (NABs) on a large geographic scale.