Despite the rapid economic and population growth, the risks related to the current dynamics of land use and land cover (LULC) have attracted a lot of attention in Ethiopia. Therefore, a complete investigation of past and future LULC changes is essential for sustainable water resources and land-use planning and management. Since the 1980s, LULC change has been detected in the upper stream of the Awash River basin. The main purpose of this research was to investigate the current dynamics of LULC and use the combined application of the cellular automata and the Markov chain (CA–Markov) model to simulate the year 2038 LULC in the future; key informant interviews, household surveys, focus group discussions, and field observations were used to assess the consequences and drivers of LULC changes in the upstream Awash basin (USAB). This research highlighted the importance of remote sensing (RS) and geographic information system (GIS) techniques for analyzing the LULC changes in the USAB. Multi-temporal cloud-free Landsat images of three sequential data sets for the periods (1984, 2000, and 2019) were employed to classify based on supervised classification and map LULC changes. Satellite imagery enhancement techniques were performed to improve and visualize the image for interpretation. ArcGIS10.4 and IDRISI software was used for LULC classification, data processing, and analyses. Based on Landsat 5 TM-GLS 1984, Landsat 7 ETM-GLS 2000, and Landsat 8 2019 OLI-TIRS, the supervised maximum likelihood image classification method was used to map the LULC dynamics. Landsat images from 1984, 2000, and 2019 were classified to simulate possible LULC in 2019 and 2038. The result reveals that the maximum area is covered by agricultural land and shrubland. It showed, to the areal extent, a substantial increase in agricultural land and urbanization and a decrease in shrubland, forest, grassland, and water. The LULC dynamics showed that those larger change rates were observed from forest and shrubland to agricultural areas. The results of the study show the radical changes in LULC during 1984–2019; the main reasons for this were agricultural expansion and urbanization. From 1984 to 2019, agriculture increased by 62%, urban area increased by 570.5%, and forest decreased by 88.7%. In the same year, the area of shrubland decreased by 68.6%, the area of water decreased by 65.5%, and the area of grassland decreased by 57.7%. In view of the greater increase in agricultural land and urbanization, as well as the decrease in shrubland, it means that the LULC of the region has changed. This research provides valuable information for water resources managers and land-use planners to make changes in the improvement of future LULC policies and development of sub-basin management strategies in the context of sustainable water resources and land-use planning and management.

The Awash River Basin is the most irrigated area in Ethiopia, which is facing critical water resources problems. The main objective of this study was to assess the impacts of climate change on river flows in the upper Awash Subbasin, Ethiopia, using the soil and water assessment tool (SWAT) hydrological model. The ensemble of two global climate models (CSIRO-Mk3-6-0 and MIROC-ESM-CHEM with RCP4.5 and RCP8.5) for climate data projections (the 2020s, 2050s, and 2080s) and historical climate data from 1981–2010 was considered. Bias-corrections were made for both the GCM data. SWAT model was calibrated and validated to simulate future hydrologic variables in response to changes in rainfall and temperature. The results showed that the projected climate change scenarios were an increase in rainfall for the period of the 2020s but reduced for the periods of 2050s and 2080s. The annual mean temperature increases, ranging from 0.5 to 0.9 °C under RCP4.5 and 0.6 to 1.2 °C under RCP8.5 for all time slices. In the 2020s, annual mean rainfall increases by 5.77% under RCP4.5 and 7.80% under RCP8.5, while in 2050s and 2080s time slices, rainfall decrements range from 3.31 to 9.87% under RCP4.5 and 6.80 to 16.22% under RCP8.5. The change in rainfall and temperature probably leads to increases in the annual streamflow by 5.79% for RCP4.5 and 7.20% for RCP8.5 in the 2020s, whereas decreases by 10.39% and 11.45% under RCP4.5; and 10.79% and −12.38% for RCP8.5 in 2050s and 2080s, respectively. Similarly, in the 2020s, an increment of annual runoff was 10.73% for RCP4.5 and 12.08% for RCP8.5. Runoff reduces by 12.03% and 4.12% under RCP4.5; and 12.65% and 5.31% under RCP8.5 in the 2050s and the 2080s, respectively. Overall, the results revealed that changes in rainfall and temperature would have significant impacts on the streamflow and surface runoff, causing a possible reduction in the total water availability in the subbasin. This study provides useful information for future water resource planning and management in the face of climate change in the upper Awash River basin.

Land use and land cover (LULC) change have intense implications on soil resources, that requires research attention and global collaboration to take urgent actions. The present study attempted to analyze the impact of LULC change on soil erosion and sedimentation in Muger Sub-basin, southwestern parts of Ethiopia. Landsat TM 1986, Landsat ETM+ 2003, and Landsat OLI/TIRS 2020 are used for LULC analysis. We used rainfall erosivity, soil erodibility, slope length and steepness, cover management, and conservation practices to calculate soil erosion and sedimentation between 1986 and 2020. In this study, the integration of revised universal soil loss equation (RUSLE) model and geographic information system (GIS) are used to analyze the impact of LULC change on soil erosion and sedimentation. The average soil loss rate is about 53.2 ton/ha/year in 1986 and increased to 63.6, and 64 ton/ha/year in 2003, 2020, respectively. Result revealed that about 2707.7 ha (33%), 3124.5 ha (38.1%) and 3197.4 ha (38.9%) were exposed to severe erosion in 1986, 2003 and 2020, respectively. The mean sediment yields of the study area is estimated to 7.8 ton/ha/year in 1986, and later increased to 10, and 10.2 ton/ha/year in 2003, and 2020, respectively. Results revealed that the steep slope areas with crop land experience considerable soil loss, with mean soil loss increasing over all study period. Thus, urgent policy on the wise use of natural resources is essential not optional to reduce the current soil loss and sedimentation in Muger Sub-basin.

Understanding long-term trends in hydroclimatic variables is important for future sustainable water resource management as it could show the possible regime shifts in hydrology. The main objective of this study was to analyze the homogeneity and trends of hydroclimatic data of Upper Awash Sab-Basin (UASB) in Oromia, Ethiopia, by employing homogeneity tests and Mann-Kendall and Sens slope tests. The data consist of 18 rainfall stations, 8 temperature stations, and 8 flow gauging stations across the UASB. Homogeneity and trends in streamflow, rainfall, and temperature variables were analyzed for the time period 1980 to 2017. In order to analyze homogeneity of hydroclimatic variables, we used four homogeneity tests (Pettitts test, Buishands test, standard normal homogeneity test, and von Neumann ratio test) at 5 significance level. Based on the outputs of four homogeneity tests, the results were classified into three categories, namely, useful, doubtful, and suspect to select the homogeneity stations. Mann-Kendall (Z) and Sens slope tests (Q) were applied for the selected homogeneous time series to detect the trend and magnitude of changes in hydroclimatic variables. The result showed that most of the stations in annual rainfall and streamflow data series were classified as useful. It is found that 58 of the rainfall stations were homogeneous. It is highlighted that 3 out of 8 discharge gauging stations have an inhomogeneity as they failed from one or a combination of the four tests. The MK revealed significant decreasing trends of annual rainfall in Addis Alem (Q=19.81), Akaki (Q=5.60), Hombole (Q=9.49), and Ghinch (Q=12.38) stations. The trend of annual temperature was a significant increasing trend in Addis Ababa Bole (Q=0.05), Addis Ababa Tikur Ambessa (Q=0.03), Tulu Bolo (Q=0.07), and Addis Alem (Q=0.06) stations. The results of discharge showed a significant increasing trend in Bega at Mojo (Q=0.17) and Hombole (Q=0.03) gauging stations. In general, the results obtained from discharge, rainfall, and temperature series indicated that most of the stations exhibited no trends in both annual and seasonal time series. It can be concluded that decreases in average annual rainfall totals and increases in mean annual temperature will probably drive sub-basin scale changes in discharge. We believe that the results obtained can fill information gaps on homogeneity and trends of hydroclimatic variables, which is very crucial for future water resource planning and management in the face of climate change.

The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final Run (IMERGF) product has now been upgraded to Version 4 (V4), which has been available since March 2017. Therefore, it is desirable to evaluate the characteristic differences between the V4 and the previous V3 products. A comprehensive performance evaluation of the errors of the successive V3 and V4 IMERGF products is performed with a comparison of the China daily Precipitation Analysis Products (CPAP) from March 2014 to February 2015. The version 6 Global Satellite Mapping of Precipitation (GSMaP) research product (which is another Global Precipitation Measurement (GPM) based precipitation product) is also used as a comparison in this study. Overall, the IMERGF-V4 product does not exhibit the anticipated improvement for China compared to the IMERGF-V3 product. An analysis of the metrics of annual daily average precipitation over China for the IMERGF-V3 and IMERGF-V4 products indicates a decrease of the relative bias (RB) from 3.70% to −7.18%, a decrease of the correlation coefficient (CC) from 0.91 to 0.89, an increase of the fractional standard error (FSE) from 0.49 to 0.56, and an increase of the root-mean-square error (RMSE) from 0.63 mm to 0.72 mm. Compared to the IMERGF-V3 product, the IMERGF-V4 product exhibits a significant underestimation of precipitation in the Qinghai-Tibetan plateau with a much lower RB of −60.91% (−58.19%, −65.30%, and −63.74%) based on the annual (summer, autumn, and winter) daily average precipitation and an even worse performance during winter (−72.33% of RB). In comparison, the GSMaP product outperforms the IMERGF-V3 and IMERGF-V4 products and has the smallest RMSE (0.47 mm/day), highest CC (0.95), lowest FSE (0.37), and best performance of the RB (−2.39%) in terms of annual daily precipitation over China. However, the GSMaP product underestimates the precipitation more than the IMERGF-V3 product for the arid XJ region.