Flood Hazard Mapping Using Exploratory Regression Model in GIS Domain

Résumé

Abstract In this study, attempt has been made to understand the spatial distribution of flood hazard and flood risk in the Awash basin, Ethiopia. Awash basin has been chosen because it’s in continuous threat spatially and temporally. Eight determinant factors of flood hazard (viz., elevation, slope, rainfall, drainage density, landuse, soil type, wetness index and lineament density) were studied as independent variables. Each factor was reclassified into four classes and each was weighted according to its susceptibility towards the hazard. For example topographic lows were given the highest weight of 4; whereas topographic highs were given the lowest weight of 1. All the independent variables were overlaid in GIS domain to get the final spatial distribution of hotspots of flood hazard. Exploratory regression analysis showed that the existing landuse is the dominant factor influencing the flood vulnerability. A total of 31 models were generated using Exploratory regression in GIS domain. Model number 31 was found to be the best fit model with the highest Adjusted R2 value of 0.839539 and the least Akaike’s Information criterion value of 1536.866. Spatial autocorrelation tool run on the standard residuals yields the Z score and p value of 0.742522 and 0.457771 respectively; indicating that the residuals were neither clustered nor dispersed. Spatial extents of flood hazard and flood risk along with the priority for spatial planning in the Awash basin is digested well in this study.

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