Although Ethiopia has a large potential to develop surface irrigation, only 5% of the 30 to 70 million hectares (ha) potentially available has been developed. To examine the underlying causes of this lack of irrigation development, this study evaluates the suitability of surface water irrigation for the Lake Tana Basin development corridor. Surface water availability and land potentially suitable for irrigation development were considered. Surface water potential was examined by analyzing long-term daily historical river discharges. Land suitable for irrigation was determined with a GIS-based multi-criteria evaluation, which considers the interaction of various factors such as climate, river proximity, soil type, land cover, topography/slope, and market outlets. The results indicate that nearly 20% of the Lake Tana Basin is suitable for surface irrigation. However, after analyzing 27 years of river discharge, less than 3% of the potential irrigable area (or less than 0.25% of the basin area) could be irrigated consistently with runoff from the river systems. Thus, the irrigation potential in the Lake Tana Basin can be met by increasing dry season flows, by improving upland infiltration, by supplying water from reservoirs, or by pumping water directly from Lake Tana. Published by Elsevier B.V.

Hydrologic simulations of different models have direct impact on the accuracy of discharge prediction because of the diverse model structure. This study is an attempt to comprehend the uncertainty in discharge prediction of two models in the Ghatshila catchment, Subarnarekha Basin in India. A lumped Probability Distribution Model (PDM) and semi-distributed Soil and Water Assessment Tool (SWAT) were applied to simulate the discharge from 24 years of records (1982-2005), using gridded ground based meteorological variables. The results indicate a marginal outperformance of SWAT model with 0.69 Nash-Sutcliffe (NSE) for predicting discharge as compared to PDM with 0.62 NSE value. Extreme high flows are clearly depicted in the flow duration curve of SWAT model simulations. PDM model performed well in capturing low flows. However, with respect to input datasets and model complexity, SWAT requires both static and dynamic inputs for the parameterization of the model. This work is the comprehensive evaluation of discharge prediction in an Indian scenario using the selected models; ground based gridded rainfall and meteorological dataset. Uncertainty in the model prediction is established by means of Generalized Likelihood Uncertainty Estimation (GLUE) technique in both of the models.

According to Intergovernmental Panel on Climate Change (IPCC) future projections, precipitation and temperature will increase over eastern Africa in the coming century. This chapter presents basin-level impact of climate change on sediment yield in Upper Gilgel Abay catchment, Blue Nile Basin, Ethiopia, by downscaling HadCM3 global climate model using Statistical Downscaling Model (SDSM). IPCC-recommended baseline period (1961-1990) was used for baseline scenario analysis. Future scenario analysis was performed for the 2020s, 2050s, and 2080s. Globally, HadCM3 model is widely applied for climate change studies and it consists of A2 (medium high emission) and B2 (medium low emission) scenarios. Impact assessment on sediment yield was done by Soil and Water Assessment Tool (SWAT) hydrological model. SWAT model performance in simulating daily sediment yield for the study area was satisfactory with Nash-Sutcliffe Efficiency (NSE) of 0.58 and 0.51 for calibration and validation periods, respectively. Mean annual changes of precipitation and temperature (maximum and minimum) were applied to quantify these impacts. The result of downscaled precipitation and temperature reveals a systematic increase in all future time periods for both A2 and B2 scenarios. These increases in climate variables are expected to result in increase in mean annual sediment yield of 11.3, 16.3, and 21.3 % for A2 scenario and by 11.0, 14.3, and 11.3 % for B2 scenario for the 2020s, 2050s, and 2080s, respectively. This increase in sediment yield is double the increase in stream flow due to climate change for all time periods. Future work need to consider also impact of land use change on the catchment for future sustainable development plan.

This paper studied the impacts of small-scale irrigation (SSI) interventions on environmental sustainability, agricultural production, and socio-economics using an Integrated Decision Support System (IDSS). The IDSS is comprised of a suite of models, namely the Soil and Water Assessment Tool (SWAT), Agricultural Policy/Environmental extender (APEX), and Farm Income and Nutrition Simulator (FARMSIM). The IDSS was applied in Dimbasinia watershed in northern Ghana using irrigation water from shallow groundwater. The watershed has a modest amount of shallow groundwater resources. However, the average annual irrigation water requirement exceeded the average annual shallow groundwater recharge. It was found that the current crop yield in Dimbasinia watershed was only similar to 40% of the potential crop production. This is mainly related to climate variability, low soil fertility, and land-management practices. For example, application of 50 kg/ha urea and 50 kg/ha DAP doubled maize and sorghum yield from the current farmers' practices. Better income was obtained when irrigated vegetables/fodder were cultivated in rotation with sorghum as compared to in rotation with maize. Investment in solar pumps paid better dividends and also supplied clean energy. The socio-economic analysis indicated that having irrigated dry season vegetables will improve household nutrition. Since shallow groundwater recharge alone may not provide sufficient water for irrigation in a sustainable manner, surface water may be stored using water-harvesting structures to supplement the groundwater for irrigation. Integrated use of the water resources will also reduce depletion of the shallow groundwater aquifer. We conclude that IDSS is a promising tool to study gaps and constraints as well as upscaling of SSI.

The study was conducted in Lake Tana Basin of Ethiopia to assess potentially irrigable areas for home gardens, water availability, and feasibility of water-lifting technologies. A GIS-based Multi-Criteria Evaluation (MCE) technique was applied to access the potential of surface and groundwater sources for irrigation. The factors affecting irrigation practice were identified and feasibility of water-lifting technologies was evaluated. Pairwise method and expert's opinion were used to assign weights for each factor. The result showed that about 345,000 ha and 135,000 ha of land were found suitable for irrigation from the surface and groundwater sources, respectively. The rivers could address about 1-1.2% of the irrigable land during dry season without water storage structure whereas groundwater could address about 2.2-2.4% of the irrigable land, both using conventional irrigation techniques. If the seven major dams within the basin were considered, surface water potential would be increased and satisfy about 21% of the irrigable land. If rainwater harvesting techniques were used, about 76% of the basin would be suitable for irrigation. The potential of surface and groundwater was evaluated with respect to water requirements of dominant crops in the region. On the other hand, rope pump and deep well piston hand pump were found with relatively the most (26%) and the least (9%) applicable low-cost water-lifting technologies in the basin.

In many developing countries and remote areas of important ecosystems, good quality precipitation data are neither available nor readily accessible. Satellite observations and processing algorithms are being extensively used to produce satellite rainfall products (SREs). Nevertheless, these products are prone to systematic errors and need extensive validation before to be usable for streamflow simulations. In this study, we investigated and corrected the bias of Multi-Sensor Precipitation Estimate-Geostationary (MPEG) data. The corrected MPEG dataset was used as input to a semi-distributed hydrological model Hydrologiska Byrans Vattenbalansavdelning (HBV) for simulation of discharge of the Gilgel Abay and Gumara watersheds in the Upper Blue Nile basin, Ethiopia. The result indicated that the MPEG satellite rainfall captured 81% and 78% of the gauged rainfall variability with a consistent bias of underestimating the gauged rainfall by 60%. A linear bias correction applied significantly reduced the bias while maintaining the coefficient of correlation. The simulated flow using bias corrected MPEG SRE resulted in a simulated flow comparable to the gauge rainfall for both watersheds. The study indicated the potential of MPEG SRE in water budget studies after applying a linear bias correction. (C) 2017 Elsevier B.V. All rights reserved.

Watershed responses are affected by the watershed characteristics and rainfall events. The characteristics of soil layers are among the fundamental characteristics of a watershed and they are input to hydrologic modeling similar to topography and land use/cover. Although the roles of soils have been perceived, there are limited studies that quantify the role of soil characteristics on watershed runoff responses due to the lack of field datasets. Using two adjacent watersheds (Ribb and Gumara) which have a significant different runoff response with a similar characterstics except geological settings (including soil characteristics), we studied the effects of soil characteristics on runoff and water balance. The Soil and Water Assessment Tool (SWAT) was used to simulate the surface runoff response at the outlet of the watershed and the optimal model parameters distribution was tested with a non-parametric test for similarity. Results indicated that SWAT model captured the observed flow very well with a Nash-Sutcliffe Efficiency (NSE) of greater than 0.74 and with a PBIAS of less than 10% for both calibration and validation period. The comparison of the optimal model parameter distributions of the SWAT model showed that the watershed characteristics could be uniquely defined and represented by a hydrologic model due to the differences in the soils. Using field observations and modeling experiments, this study demonstrates how sensitive watershed hydrology is to soils, emphasizing the importance of accurate soil information in hydrological modeling. We conclude that due emphasis should be given to soil information in hydrologic analysis.

The agricultural system in Sub-Saharan Africa (SSA) is dominated by traditional farming practices with poor soil and water management, which contributes to soil degradation and low crop productivity. This study integrated field experiments and a field-scale biophysical model (Agricultural Policy Environmental Extender, APEX) to investigate the impacts of conservation agriculture (CA) with a drip irrigation system on the hydrology and water management as compared to the conventional tillage (CT) practice. Field data were collected from four study sites; Dangishita and Robit (Ethiopia), Yemu (Ghana), and Mkindo (Tanzania) to validate APEX for hydrology and crop yield simulation. Each study site consisted of 100 m(2) plots divided equally between CA and CT practices and both had a drip irrigation setup. Cropping pattern, management practices, and irrigation scheduling were monitored for each experimental plot. Significant water savings ( =3D 0.05) were observed under CA practice; evapotranspiration and runoff were reduced by up to 49% and 62%, respectively, whereas percolation increased up to three-fold. Consequently, irrigation water need was reduced in CA plots by about 14-35% for various crops. CA coupled with drip irrigation was found to be an efficient water saving technology and has substantial potential to sustain and intensify crop production in the region.