The water balances of twenty catchments in the Upper Blue Nile basin have been analyzed using a top-down modeling approach based on Budyko's hypotheses. The objective of this study is to obtain better understanding of water balance dynamics of upper Blue Nile catchments on annual and monthly time scales and on a spatial scale of meso scale to large scale. The water balance analysis using a Budyko-type curve at annual scale reveals that the aridity index does not exert a first order control in most of the catchments. This implies the need to increase model complexity to monthly time scale to include the effects of seasonal soil moisture dynamics. The dynamic water balance model used in this study predicts the direct runoff and other processes based on the limit concept; i.e. for dry environments since rainfall amount is small, the aridity index approaches to infinity or equivalently evaporation approaches rainfall and for wet environments where the rainfall amount is large, the aridity index approaches to zero and actual evaporation approaches the potential evaporation. The uncertainty of model parameters has been assessed using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology. The results show that the majority of the parameters are reasonably well identifiable. However, the baseflow recession constant was poorly identifiable. Parameter uncertainty and model structural errors could be the reason for the poorly identifiable parameter. Moreover, a multi-objective model calibration strategy has been employed to emphasize the different aspects of the hydrographs on low and high flows. The model has been calibrated and validated against observed streamflow time series and it shows good performance for the twenty study catchments in the upper Blue Nile. During the calibration period (1995–2000) the Nash and Sutcliffe efficiency (E _NS) for monthly flow prediction varied between 0.52 to 0.93 (dominated by high flows), while it varied between 0.32 to 0.90 using logarithms of flow series (indicating the goodness of low flow simulations). The model is parsimonious and it is suggested that the calibrated parameters could be used after some more regionalization efforts to predict monthly stream flows in ungauged catchments of the Upper Blue Nile basin, which is the vast majority of catchments in that region.

Measurements of the stable isotopes oxygen-18 (18O) and deuterium (2H) were carried out in two meso-scale catchments, Chemoga (358 km2) and Jedeb (296 km2) south of Lake Tana, Abay/Upper Blue Nile basin, Ethiopia. The region is of paramount importance for the water resources in the Nile basin, as more than 70% of total Nile water flow originates from the Ethiopian highlands. Stable isotope compositions in precipitation, spring water and streamflow were analysed (i) to characterise the spatial and temporal variations of water fluxes; (ii) to estimate the mean residence time of water using a sine wave regression approach; and (iii) to identify runoff components using classical two-component hydrograph separations on a seasonal timescale. The results show that the isotopic composition of precipitation exhibits marked seasonal variations, which suggests different sources of moisture generation for the rainfall in the study area. The Atlantic–Indian Ocean, Congo basin, Upper White Nile and the Sudd swamps are the potential moisture source areas during the main rainy (summer) season, while the Indian–Arabian and Mediterranean Sea moisture source areas during little rain (spring) and dry (winter) seasons. The spatial variation in the isotopic composition is influenced by the amount effect as depicted by moderate coefficients of determination on a monthly timescale (R2 varies from 0.38 to 0.68) and weak regression coefficients (R2 varies from 0.18 to 0.58) for the altitude and temperature effects. A mean altitude effect accounting for −0.12‰/100 m for 18O and −0.58‰/100 m for 2H was discernible in precipitation isotope composition. Results from the hydrograph separation on a seasonal timescale indicate the dominance of event water, with an average of 71 and 64% of the total runoff during the wet season in the Chemoga and Jedeb catchments, respectively. Moreover, the stable isotope compositions of streamflow samples were damped compared to the input function of precipitation for both catchments. This damping was used to estimate mean residence times of stream water of 4.1 and 6.0 months at the Chemoga and Jedeb catchment outlets, respectively. Short mean residence times and high fractions of event water components recommend catchment management measures aiming at reduction of overland flow/soil erosion and increasing of soil water retention and recharge to enable sustainable development in these agriculturally dominated catchments.

HIGHLIGHTS. The review article summarizes the uncertainties in estimating recharge using widely applied methods.The review article highlights methods for invest

Quantifying uncertainties in water resource prediction in data-scarce regions is essential for resource development. We use globally available datasets of precipitation and potential evapotranspiration for the regionalization of model parameters in the data-scarce regions of Ethiopia. A regional model was developed based on 14 gauged catchments. Three possible parameter sets were tested for regionalization: (1) the best calibration parameters, (2) the best validation parameter set derived from behavioral parameters during the validation period, and (3) the stable parameter sets. Weighted multiple linear regression was applied by assigning more weight to identifiable parameters, using a novel leave-one-out cross-validation technique for evaluation and uncertainty quantification. The regionalized parameter sets were applied to the remaining 35 ungauged catchments in the Ethiopian Rift Valley Lake Basin (RVLB) to provide regional water balance estimations. The monthly calibration of the gauged catchments resulted in Nash Sutcliffe Efficiencies (NSE) ranging from 0.53 to 0.86. The regionalization approach provides acceptable regional model performances with a median NSE of 0.63. The results showed that, other than the commonly used best-calibrated parameters, the stable parameter sets provide the most robust estimates of regionalized parameters. As this approach is model-independent and the input data used are available globally, it can be applied to any other data-scarce region.

The availability of water for agricultural production is under threat from climate change and rising demands from various sectors. In this paper, a simulation-optimization model for optimizing the irrigation schedule in the Bilate watershed was developed, to save irrigation water and maximize the yield of deficit irrigation. The model integrated the Soil and Water Assessment Tool (SWAT) and an irrigation-scheduling optimization model. The SWAT model was used to simulate crop yield and evapotranspiration. The Jensen crop-water-production function was applied to solve potato and wheat irrigation-scheduling-optimization problems. Results showed that the model can be applied to manage the complicated simulation-optimization irrigation-scheduling problems for potato and wheat. The optimization result indicated that optimizing irrigation-scheduling based on moisture-stress-sensitivity levels can save up to 25.6% of irrigation water in the study area, with insignificant yield-reduction. Furthermore, optimizing deficit-irrigation-scheduling based on moisture-stress-sensitivity levels can maximize the yield of potato and wheat by up to 25% and 34%, respectively. The model developed in this study can provide technical support for effective irrigation-scheduling to save irrigation water and maximize yield production.