Exploratory regression modeling for flood susceptibility mapping in the GIS environment.

Understanding the temporal and spatial patterns of flood in the Awash River basin, which is located in Ethiopia's Afar region, is crucial. The Awash basin was picked because it is continuously in danger both spatially and temporally. The likelihood of flooding was assessed using eight independent variables: elevation, slope, rainfall, drainage density, land use, soil type, wetness index, and lineament density. Each constituent was assigned a weight based on its susceptibility to the danger, which was classified into four classifications. Exploratory regression analysis showed that the existing land use is the main factor influencing flood susceptibility. For the GIS domain, a total of 31 models were built using exploratory regression. Model number 31 was found to be the best fit model, having the highest Adjusted R2 value of 0.8 and the lowest Akaike's Information criterion value of 1536.8. The spatial autocorrelation tool's Z score and p-value for the standard residuals are, respectively, 0.7 and 0.4, indicating that they were neither clustered nor scattered. The geographic breadth of flood susceptibility and risk is thoroughly examined in this paper, as is the significance of spatial planning in the Awash basin.

Application of hydrological indices for erosion hazard mapping using Spatial Analyst tool.

Hydrological indices provide excellent input to geographic information systems for the successful mapping of erosion-prone areas. In this research, a digital elevation model was processed and analyzed to obtain the necessary hydrological indices necessary for erosion modeling. The indices (such as sediment transport index, compound topography index, and stream power index) along with other themes (Like Slope gradient, curvature, distance to channels, and channel density) were overlaid using the "Weighted Sum" overlay tool in the geographic information system. The results showed that 33.14 km2 of the test watershed (sub-basin of Abay, Ethiopia) falls in very high/severe erosion zone and needs immediate conservation measures. A total of 98.26 km2, 153.40 km2, and 263.17 km2 fall in high-, moderate-, and low-erosion hazard zones, respectively. Therefore, the primary and secondary derivatives of the digital elevation model along with morphometric parameters coupled with a Spatial Analyst tool proves to be a powerful integrated approach in demarcating erosion vulnerable zones and could be applied at regional and continental scale for proper watershed management.