Abstract

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.

Details

Title
Exploratory regression modeling for flood susceptibility mapping in the GIS environment
Author
Fenglin, Wang 1 ; Ahmad, Imran 2 ; Zelenakova, Martina 3 ; Fenta, Assefa 2 ; Dar, Mithas Ahmad 4 ; Teka, Afera Halefom 2 ; Belew, Amanuel Zewdu 2 ; Damtie, Minwagaw 2 ; Berhan, Marshet 2 ; Shafi, Sebahadin Nasir 5 

 China University of Geosciences, School of Environmental Studies, (Wu Han), China; China University of Geosciences Press Co., Ltd, Wuhan, China (GRID:grid.503241.1) (ISNI:0000 0004 1760 9015) 
 Debre Tabor University, Department of Hydraulic and Water Resources Engineering, Debra Tabor, Ethiopia (GRID:grid.510430.3) 
 Technical University of Kosice, Department of Environmental Engineering, Faculty of Civil Engineering, Kosice, Slovakia (GRID:grid.6903.c) (ISNI:0000 0001 2235 0982) 
 Integrated Watershed Management Programme, Department of Rural Development and Panchayati Raj, Government of Jammu and Kashmir, Srinagar, India (GRID:grid.510430.3) 
 Woldia University, Department of Computer Science, Weldiya, Ethiopia (GRID:grid.507691.c) (ISNI:0000 0004 6023 9806) 
Pages
247
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2761007047
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.