Modeling surface water potential using the SWAT model combined with principal component analysis in the ungauged Gelana watershed, Ethiopia

Abstract

This study aims to model and assess surface water potential in an ungauged watershed using the Soil and Water Assessment Tool (SWAT), principal component analysis (PCA), and regression-based regionalization techniques in the Gelana River, Ethiopia. The SWAT model was calibrated (and validated) for the 1989–2007 (2008–2015) period, and it showed a very good performance to model the river flow. The 18 physical catchment characteristics that affect the production of streamflow were selected for correlation, and to make an equation using 19 optimized SWAT model parameters. These characteristics were categorized as two climate descriptors, three soil descriptors, seven land use land cover descriptors, and six topographical descriptors. The regression equations for each SWAT parameter with a function of the physical characteristics and principal components were developed. Then, SWAT model-sensitive parameters were transferred and validated. Results reveal that the watershed has a greatest surface runoff volume of 162.14 MCM in May and a least runoff of 9.15 MCM in January. The contribution of the water balance during the spring season is highest with a total surface runoff of 103.72 mm. From the whole Gelana watershed area of 336,460 ha, 778.4 MCM of yearly surface runoff was produced. The maximum mean monthly river flow is 15.7 m3/s in May. HIGHLIGHTS The 18 physical catchments characteristics were selected for correlation, and to make an equation with optimized SWAT parameters.; From the entire Gelana watershed area of 336,460 ha, 778.4 MCM of annual surface runoff was produced.; Streamflow data play a significant role in existing and upcoming engineering design and water resources management in and around the watershed.;

Keywords

• principal component analysis
• regionalization
• spss
• stepwise multiple linear regression
• swat
• ungauged watershed