Assessment of Groundwater Potential Zones of Upper Blue Nile River Basin Using Multi-Influencing Factors under GIS and RS Environment: A Case Study on Guder Watersheds, Abay Basin, Oromia Region, Ethiopia

Abstract

Groundwater is the most crucial resource for human beings and plays an important role in combating climate change and is substantial to human existence on the globe. Overall increased demand for water in different sectors, population growth, and unreliable rainfall necessitates the planning and management of groundwater. In this study, groundwater potential zones are delineated by combining remote sensing and geographical information system techniques in the Guder watersheds of the Upper Blue Nile Basin. Groundwater potential zones are prepared by using various multi-influencing factors like geomorphology, land use/cover, lithology, soil type, soil texture, drainage density, slope, lineament, rainfall, and elevation. These influencing factors’ features were given appropriate weightage according to Saaty’s AHP method, expert judgment, and their relative significance for groundwater occurrence. The groundwater potential zone was classified into different categories as very poor, poor, moderate, good, and very good according to quantile classification. This study reveals that about 33.6% of the Guder River Basin represents a good andvery good GWPZ category with an equal value of 16.8%,; while values 23.3%, 20.2%, and 22.9% were denoted by very poor, poor, and moderate groundwater potential zone, respectively. GWPZ was validated by field-collected data such as well discharge and soil depth. An accepted similarity was observed between delineated GWPZ and the basin’s soil depth graphically. The results of this study were also verified by correlation and kappa statistics values of 0.73and 77%, respectively. The study is certain with a sensible dimension of consistency in pairwise comparison between influencing and the overall weightage. The very high GWPZs are found in the northern part starting from the center longitude of the study area, more along with the northwestern, southern, and southwestern of the Guder subbasin. Low to very low groundwater potentiality has been seen at different distances from the center due to the presence of escapements, hills and steep side slopes, slopes, and rock surfaces. The study also revealed that the zone of high groundwater potential has high soil depth, and the zone of low groundwater showed low soil depth as the capacity of the aquifer to store water may depend on the depth of soil profile. This study attests to the GIS and remote sensing techniques as an effective model for delineation of GWPZs and can be applied at other basins of Ethiopia.

Soil erosion risk assessment and treatment priority classification: A case study on guder watersheds, Abay river basin, Oromia, Ethiopia

“…According to Sentinel-2 land-use land-cover 2016, the major land use/cover of the Guder sub-basin is dominated by cropland/agriculture and covers (57.87%) of the whole watersheds; while Trees cover areas is (22.33%), and Grassland covers (18.75%) portion of the area respectively ( Figure 2 (b)). The average altitude of the area varies from 1144 to 3288 m above sea level as delineated by a 30m spatial resolution and it receives an annual mean rainfall of between 812.0mm to 1699.0mm ( Duguma and Duguma, 2022 ). The Expansion of irrigation activities has been extremely practiced in the Guder watersheds ( Subash et al., 2017 ).…”

“…The whole population of the sub-basin is about 130,500 of which the numbers male and female are 64,881 and 65,619 respectively. The main economic activity in the sub-basin is crop production or agriculture and livestock production ( Duguma and Duguma, 2022 ; Muleta and Biru, 2019b ; Subash, 2017 ). As stated by Muleta and Biru (2019a) , landscape-level watershed conservation was recommended to enhance ecosystem services.…”

Identification of Groundwater Potential Zones Using Remote Sensing and GIS Technique: A Case Study of the Ketungau Basin in Sintang, West Kalimantan

“…A pairwise comparison matrix was formed, where aii = 1 and aij = 1/ai, for the determination of weights assigned to different thematic maps and their features based on field experience and expert judgment. This was normalized with the AHP Saaty method (Duguma & Duguma, 2022;Goepel, 2013;A. Kumar & Krishna, 2018) as shown in Table 3.…”

“…The weight factors for the ranking criteria and resulting sub-criteria were calculated using the right eigenvectors, which were derived from the maximum absolute eigenvalues (λmax). Meanwhile, the principal eigenvalue (λ) was estimated with the eigenvector technique (Duguma & Duguma, 2022;A. Kumar & Krishna, 2018) where W is the corresponding eigenvector of λmax, wi (i = 1, 2, ..., n) is the weight value for ranking, and in this study, λmax = 10.214.…”

“…Kumar & Krishna, 2018) where W is the corresponding eigenvector of λmax, wi (i = 1, 2, ..., n) is the weight value for ranking, and in this study, λmax = 10.214. The consistency of the decision matrix must be evaluated by calculating the consistency index (CI) (Duguma & Duguma, 2022;Goepel, 2013;Ş. Şener et al, 2011), which is defined as:…”