Land Use Land Cover (LULC) changes analysis is one of the most useful methodologies to understand how the land was used in the past years, what types of detections are to be expected in the future, as well as the driving forces and processes behind these changes. In Ethiopia, Africa, the rapid variations of LULC observed in the last decades are mainly due to population pressure, resettlement programs, climate change, and other human- and nature-induced driving forces. Anthropogenic activities are the most significant factors adversely changing the natural status of the landscape and resources, which exerts unfavourable and adverse impacts on the environment and livelihood. The main goal of the present work is to review previous studies, discussing the spatiotemporal LULC changes in Ethiopian basins, to find out common points and gaps that exist in the current literature, to be eventually addressed in the future. A total of 25 articles, published from 2011 to 2020, were selected and reviewed, focusing on LULC classification using ArcGIS and ERDAS imagine software by unsupervised and maximum likelihood supervised classification methods. Key informant interview, focal group discussions, and collection of ground truth information using ground positioning systems for data validation were the major approaches applied in most of the studies. All the analysed research showed that, during the last decades, Ethiopian lands changed from natural to agricultural land use, waterbody, commercial farmland, and built-up/settlement. Some parts of forest land, grazing land, swamp/wetland, shrubland, rangeland, and bare/ rock out cropland cover class changed to other LULC class types, mainly as a consequence of the increasing anthropogenic pressure. In summary, these articles confirmed that LULC changes are a direct result of both natural and human influences, with anthropogenic pressure due to globalisation as the main driver. However, most of the studies provided details of LULC for the past decades within a specific spatial location, while they did not address the challenge of forecasting future LULC changes at the watershed scale, therefore reducing the opportunity to develop adequate basin-wide management strategies for the next years.

Groundwater is a crucial source of water supply due to its continuous availability, reasonable natural quality, and being easily diverted directly to the poor community more cheaply and quickly. The West Arsi Zone residents remain surface water dependent due to traditional exploration of groundwater, which is a tedious approach in terms of resources and time. This study uses remote sensing data and geographic information system techniques to evaluate the groundwater potential of the study area. This technique is a fast, accurate, and feasible technique. Groundwater potential and recharge zone influencing parameters were derived from Operational Land Imager 8, digital elevation models, soil data, lithological data, and rainfall data. Borehole data were used for results validation. With spatial analysis tools, the parameters affecting groundwater potential (LULC, soil, lithology, rainfall, drainage density, lineament density, slope, and elevation) were mapped and organized. The weight of the parameters according to percent of influence on groundwater potential and recharge was determined by Analytical Hierarchy Process according to their relative influence. For weights allocated to each parameter, the consistency ratio obtained was 0.033, which is less than 0.1, showing the weight allocated to each parameter is acceptable. In the weighted overlay analysis, from a percent influence point of view, slope, land use/cover, and lithology are equally important and account for 24% each, while the soil group has the lowest percent of influence, which accounts only 2% according to this study. The generated groundwater potential map has four ranks, 2, 3, 4, and 5, in which its classes are Low, Moderate, High, and Very High, respectively, based on its groundwater potential availability rank and class. The area coverage is 9825.84 ha (0.79%), 440,726.49 ha (35.46%), 761,438.61 ha (61.27%), and 30,748.68 ha (2.47%) of the study area, respectively. Accordingly, the western part of district is expected to have very high groundwater potential. High groundwater potential is concentrated in the central and western parts whereas moderate groundwater potential distribution is dominant in the eastern part of the area. The validation result of 87.61% confirms the very good agreement among the groundwater record data and groundwater potential classes delineated.

Land use land cover (LULC) changes are highly pronounced in African countries, as they are characterized by an agriculture-based economy and a rapidly growing population. Understanding how land use/cover changes (LULCC) influence watershed hydrology will enable local governments and policymakers to formulate and implement effective and appropriate response strategies to minimize the undesirable effects of future land use/cover change or modification and sustain the local socio-economic situation. The hydrological response of the Ethiopia Fincha’a watershed to LULCC that happened during 25 years was investigated, comparing the situation in three reference years: 1994, 2004, and 2018. The information was derived from Landsat sensors, respectively Landsat 5 TM, Landsat 7 ETM, and Landsat 8 OLI/TIRS. The various LULC classes were derived via ArcGIS using a supervised classification system, and the accuracy assessment was done using confusion matrixes. For all the years investigated, the overall accuracies and the kappa coefficients were higher than 80%, with 2018 as the more accurate year. The analysis of LULCC revealed that forest decreased by 20.0% between the years 1994–2004, and it decreased by 11.8% in the following period 2004–2018. Such decline in areas covered by forest is correlated to an expansion of cultivated land by 16.4% and 10.81%, respectively. After having evaluated the LULCC at the basin scale, the watershed was divided into 18 sub-watersheds, which contained 176 hydrologic response units (HRUs), having a specific LULC. Accounting for such a detailed subdivision of the Fincha’a watershed, the SWAT model was firstly calibrated and validated on past data, and then applied to infer information on the hydrological response of each HRU on LULCC. The modelling results pointed out a general increase of average water flow, both during dry and wet periods, as a consequence of a shift of land coverage from forest and grass towards settlements and build-up areas. The present analysis pointed out the need of accounting for past and future LULCC in modelling the hydrological responses of rivers at the watershed scale.

Climate change, with its reaching implications, has become a popular topic in recent years. Among the many aspects of climate change, one of the most pressing concerns has been identified as the impact on the terrestrial water cycle, which has a direct impact on human settlement and ecosystems. The paper begins by reviewing previous studies, and then identifies their flaws and future research directions. The effects of climate change on surface water resources in the Dhidhessa Sub-basin, Abbay Basin, Ethiopia, were studied as practices. For future potential climate change, the results of global climate models (GCMs) and high-resolution regional climate models (RCMs) from multiple climate models were combined with data from Representative Concentration Pathways (RCPs) prepared by the Intergovernmental Panel on Climate Change from the CCAFS Data Distribution Center web page. To evaluate the impacts on water resources, various distributed hydrologic models based on local underlying surfaces were developed. The future potential climate change of the Dhidhessa Sub-basin Province was evaluated by integrating RCP outputs, whereas the climate change of the Dhidhessa River was directly derived from the results of different RCP. Dhidhessa stream flow will decrease in the future compared to the baseline era. The predictions of future discharge (stream flow) were based on climate scenarios data from 1991 to 2020 and for the future with two time windows, 2044 (2030–2059) and 2084 (2070–2099), on a monthly time-step after bias correction to both precipitation and temperature in the future climate described in the under each RCP. According to model results, the quantity of surface water resources in the Dhidhessa river region will decrease over the next 100 years, the percent decrease in mean annual stream flow by 10%, in 2044, and 6.3% in 2084, respectively, making the impact of temperature increase on runoff greater than that of precipitation. The distribution of runoff would be more even across years but more uneven across years in the long-term window, implying a higher possibility of drought and flooding. In general, this study discovered that any effect on this river that results in a decrease in flow will have a direct impact on the area’s ongoing water resource development and socioeconomic development.