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In recent years, sub–Saharan African countries including Ethiopia have largely targeted large-scale agricultural investment (LAI) on the grounds of economic growth, employment and income generation, but with little consideration of its potential impacts on local smallholder farmers. Using evidence from the Central Rift Valley of Ethiopia (CRVE), this study provides an in-depth analysis of the socioeconomic impacts of LAIs, particularly on the local smallholder farmers, based on data collected through a household survey, key informant interviews and focus group discussions. For the purpose, descriptive and inferential statistics and qualitative thematic analysis were used to interpret the data. Our study found that the LAI has many positive socioeconomic benefits to the local communities, as measured by technological transfer, employment opportunity and local infrastructure development. However, those farmers who were able to access LAI had better positive socioeconomic benefits while those who could not access LAI (particularly the smallholder farmers) were disproportionately disadvantaged. Nonetheless, LAI motivated and prompted some farmers to use improved agricultural technologies, including irrigation, better crop varieties, chemical fertilizer and engagement in alternative sources of income such as shopkeeping, selling manufactured products and food and drinks to farm employees and casual employment opportunities within the LAI. This has resulted in improvement of the livelihood status of some farming households. Despite several positive impacts, some negative impacts, such as loss of farmlands, reduced numbers of livestock, increased price of farmland for renting, have disproportionately affected the livelihoods of local smallholder [End Page 59] households. In light of these findings, we conclude that scaling up of agricultural technologies and targeted support to smallholder farmers for alternative income sources (with technical and financial support) could improve their livelihoods. [ABSTRACT FROM AUTHOR]

Application of models to identify soil erosion processes, estimate sediment accumulations into lakes, technically design best management practices, and monitor and evaluate different management scenarios in the Ethiopian highlands has been growing. However, proper model implementation will require verification of the model against known output parameters. This study investigated the performance and applicability of one such model, Soil and Water Assessment Tool (SWAT). Sequential Uncertainty Fitting-2 (SUFI-2), a SWAT-CUP2012 sub-module computer program, was applied to optimize the parameters of the SWAT using monthly observed sediment yield data at a monitoring site in Maybar experimental watershed, Ethiopia. Thirteen hydrological years were used for model calibration, validation and uncertainty analysis. Multi-objective function statistics: P-factor (23%, 12%), R-factor (0.63, 0.40), Nash–Sutcliffe efficiency, NSE (0.55, 0.53), root mean square error-observations standard deviation ratio (RSR) (0.67, 0.69), coefficient of determination, R 2 (0.55, 0.52), and percent bias, PBIAS (− 14.6%, 0.8%) for calibration and validation, respectively were obtained. The model evaluation statistics suggested that SWAT extremely under-predicted peak sediment loads in both calibration and validation periods. However, according to model evaluation guidelines and performance ratings, modeled sediment yield can be rated as satisfactory. Although the accuracy of modeling of soil erosion processes using SWAT is likely affected by spatial variation of watershed characteristics, and scale of management, among other factors, Maybar calibrated SWAT model do suggest a broad guide: prediction of sediment yield at ungauged watershed with SWAT could be possible under comparable topography, land use, soil, management and climate condition for the purpose of soil erosion assessment, scenario analysis, and recommendation of best management practices to support watershed management initiatives in the Ethiopian highlands. [ABSTRACT FROM AUTHOR]

Land use/land cover changes in a lake drainage basin reflect changes in the magnitude of the water balance components and rate of sediment deposition in a lake as a reflection of the fundamental linkage between what happens in a lake considered against what is happening in the drainage basin of the lake. The objective of this study was to quantify the spatio-temporal land cover/land use changes across the Lake Hayq closed drainage basin in north-east Ethiopia over a 50-years period, using multitemporal remote sensing and geospatial data. Two historical occasions of aerial photographs (1957 and 1986) and one satellite image (2007) were examined with image analysis tools: Leica Photogrammetric Suite ( LPS 9.2) Project Manager, ArcGIS10.0, and ERDAS EMAGINE 9.2. Seven aerial coverage of land use/land cover categories were identified and mapped for the past three historical times. The results indicated that farmlands/settlements and shrublands/degraded lands increased by 43.1% and 136.9%, at an annual rate of 27.4 and 13.5 ha year−1, respectively, between 1957 and 2007. In contrast, bushlands, grasslands, forestlands and lake surface area were diminished by 68.8%, 62.7%, 90.5% and 7.6%, at a rate of 24.0, 7.6, 6.1 and 3.7 ha year−1, respectively, over the past five decades. The basin had undergone significant transformation in land use/land cover over the past half century, affecting the lake's biophysical stability by accelerating soil erosion in the basin, sediment accumulation, and a reduced quantity and quality of cumulative stream flow into the lake. [ABSTRACT FROM AUTHOR]

Climate analysis at relevant time scales is important for water resources management, agricultural planning, flood risk assessment, ecological modeling and climate change adaptation. This study analyses spatiotemporal variability and trends in rainfall and temperature in Alwero watershed, western Ethiopia. Our analysis is focused on describing spatial and temporal variability of rainfall in the study area including detection of trends, with no attempt at providing meteorological explanations to any of the patterns or trends. The study is based on gridded monthly rainfall and maximum and minimum temperature data series at a resolution of 4 × 4 km which were obtained from the National Meteorological Agency of Ethiopia for the period 1983–2016. The study area is represented by 558 points (each point representing 4 × 4 km area). Mean annual rainfall of the watershed is > 1600 mm. Annual, June–September (Kiremt), March–May (Belg) rainfall totals exhibit low inter-annual variability. Annual and October-February (Bega) rainfalls show statistically significant increasing trends at p = 0.01 level. May and November rainfall show statistically significant increasing trends at p = 0.01 level. March shows statistically significant decreasing trend at p = 0.1 level. The mean annual temperature of the watershed is 25 °C with standard deviation of 0.31 °C and coefficient of variation of 0.01 °C. Mean annual minimum and maximum temperatures show statistically non-significant decreasing trends. Bega season experienced statistically significant deceasing trend in the maximum temperature at p = 0.01 level. The year-to-year variability in the mean annual minimum and maximum temperatures showed that the 2000s is cooler than the preceding decades. Unlike our expectations, annual and seasonal rainfall totals showed increasing trends while maximum and minimum temperatures showed decreasing trends. Our results suggest that local level investigations such as this one are important in developing context-specific climate change adaptation and agricultural planning, instead of coarse-scale national level analysis guiding local level decisions. [ABSTRACT FROM AUTHOR]

Background: Assessment of soil loss rates is crucial to sustainably enhance the benefits of land resources and diminish the adverse impacts of land degradation thereby areas requiring immediate soil erosion management practices can be identified. The study aimed to examine the impacts of land cover dynamics on the spatiotemporal patterns of erosion hotspots. RUSLE factors were produced using GIS and remote sensing techniques.Results: The RUSLE model adapted to Ethiopian conditions was run for 2004 and 2014 where input data layers were overlaid. The results of the model showed clear patterns of changes characterized by gradual shifting of one erosion soil loss severity class into next higher class. There was a net increase in the total soil loss largely under the very high, low and very low soil loss severity classes by 8%, 21% and 9% despite a decline in other severity classes, respectively. It also revealed that more than two-third of the catchment has experienced soil losses rates higher than the tolerable value reported for Ethiopia over which agriculturists should be concerned.Conclusions: Therefore, the observed soil loss rate and sediment yield in the study catchment would lead to further ecological deterioration unless site-specific participatory watershed management practices are employed. [ABSTRACT FROM AUTHOR]