The assessment of land suitability is the key to sustained agricultural output. Thus, the study aimed to assess the land suitability for irrigation development in the West Shewa zone, Oromia, Ethiopia. A GIS-based analytical hierarchy process was applied to evaluate a multi-criteria land suitability analysis. The key factors such as soil (depth, drainage, texture, pH, organic carbon, available water content, and salinity), slope, land use/cover, proximity to the river, proximity to the road, proximity to urban areas, and rainfall deficit were considered. These factors were reclassified, weighted, and then overlaid using the weighted overlay tool of ArcGIS software. The study classified the agricultural lands in the area from highly suitable to permanently unsuitable for irrigation to determine the suitability of the classes. The results showed that 10.27% (1419.87 km²) was highly suitable, 73.23% (10,128.97 km²) was moderately suitable, 16.34% (2259.95 km²) was marginally suitable, and 0.16% (22.16 km²) was not suitable. The area in all woredas was mainly moderately suitable for irrigation. However, Metarobi had the most highly suitable land, followed by Elfata with the most moderately suitable land, and Abuna Gindeberet with the most marginally suitable land. The results revealed huge potential for irrigation development in the West Shewa zone. As a result, it can serve as the basis for zonal-level planning and future irrigation development. Therefore, the study helps to improve the community’s lifestyle in the study area by increasing agricultural production.

Before planning the use of existing land resources for irrigation, it is necessary to determine their availability. The primary goal of this research was to examine the Guder watershed's land resource potential for irrigation development and to create a geo-referenced map of these resources using a geographic information system coupled with fuzzy logic. Irrigation suitability criteria such as slope, land use, proximity to water body, rainfall deficit, soil texture class, soil depth, soil drainage classes, and proximity to road were considered when evaluating prospective irrigable properties. The criteria maps were divided into four suitability classes using a natural break interval range technique. According to the study's findings, 39.8% of the watershed area is Highly suitable, 34.5% is moderately acceptable, 24.5% is marginally suitable, and 1.2% is not suitable for the aforementioned reasons. According to the irrigation suitability study of these characteristics, 70.42% of the slope, 15.57% of the slope, 10.6% of the slope, and 3.95% of the slope are Highly, moderately, and marginally suitable for surface irrigation, respectively. In addition, 15% of the soil in the study Area is suitable for a surface irrigation system. In terms of land cover and use, 75% is highly favorable, whereas 0.3% is not suitable for irrigation development. GIS and remote sensing offer a straightforward and powerful framework for combining spatially complicated field variables for land suitability research. This study demonstrates the effectiveness of the fuzzy logic technique combined with GIS as an effective model for finding prospective irrigable land on a continental scale.

The study attempted to map soil-erosion critical zones in the Guder sub-basin in Ethiopia. To map soil erosion sensitive areas, a digital elevation model (12 m × 12 m spatial resolution), precipitation data covering 30 years, soil type, and land use were utilized as inputs. Fuzzy logic techniques based on Geographic Information Systems (GIS) were integrated and analyzed on the ArcGIS 10.5 platform. Five contributing variables were considered as potential causes associated to soil-erosion in the study. Slope, land use, soil type, rainfall, and compound topographic index are the variables. Fuzzy membership values were constructed to generate the rankings of each parameter and their subclasses. Researcher and expert judgment with a survey of the previous studies were used to determine the membership value for each thematic layer and their classes. As a result, the soil-erosion zone map revealed very high, high, moderate, low, and very low erosion susceptibility with areal percentage distribution of 4.96%, 67.48%, 25.41%, 1.88%, and 0.27%, respectively. The study's findings were validated using cross-relationship of the contributing elements and the final map, which revealed strong relationships. The study's findings would help decision-makers and policymakers plan and implement effective watershed management strategies in highly vulnerable locations to soil erosion. Fuzzy logic approaches, when combined with GIS, have been proven to be a basic tool for determining erosion important locations. The final soil erosion map revealed that the majority of the studied areas were prone to soil erosion as a result of agricultural practices, necessitating integrated soil and water conservation practices.

Groundwater recharge potential is an important spatial analysis to refer where the groundwater recharge is likely to happen. The present study discusses approaches for determining groundwater recharge potential zones in the Guder watershed, Ethiopia, using geospatial and fuzzy logic techniques on derived thematic layers based on significant influence of groundwater occurrence. A variety of thematic layers were created using satellite images and other ancillary data, including drainage density, slope, rainfall, geology, land use/land cover, lineament density, soil, and geomorphology. Researchers, expert opinion, and previous studies were used to estimate the membership value for each governing factors. According to the findings of the study, approximately 5.25% of the area has very high groundwater recharge potential, and 9.34% of the area has high groundwater recharge potential, while the areas with very low, low, and moderate groundwater recharge potential are approximately 20.04%, 34.21%, and 31.15%, respectively. The study’s findings were confirmed by looking at the cross-tabulation area between the contributing features and the final map, which demonstrated strong associations. The findings of the study will help decision-makers and policymakers plan to implement appropriate groundwater recharge procedures. Fuzzy logic approaches have been found to be a basic tool for estimating groundwater recharge locations when used with GIS.

The univariate analysis of hydrological extremes is a well-established practice in developing countries such as Ethiopia. However, for the design of hydrological and hydraulic systems, it is essential to have a thorough understanding of flood event characteristics, including volumes, peaks, time of occurrence, and duration. This study utilizes copula functions for bivariate modeling of flood peak and volume characteristics, examining the performance of four Archimedean copulas in the Guder basin located in Ethiopia from 1987 to 2017. Flood peak and volume were extracted using the theory of runs for analysis of their joint characteristics with the truncation level chosen as equal to the lowest annual maximum event. Univariate distributions with the best fitness on both variables were determined, and results showed that gamma and GEV-fitted flood peaks and lognormal-fitted flood volumes are the most suitable. Four Archimedean copulas were evaluated, and the Gumbel-Hougaard copula was found to be the best fit for the data based on graphical and measurable tests. Bivariate probability and return period were computed in AND and OR states. The joint return period for flood peak (97.49m³/s) and volume (77.35m³/s) was found to be 15years in the AND state and approximately 4years in the OR state. The study also evaluates univariate and conditional return periods, comparing them with the primary one. The copula method was an effective method for distributing marginal variables, highlighting its potential as a valuable tool in flood management.