Soil erosion/sedimentation is an immense problem that has threatened water resources development in the Nile river basin, particularly in the Eastern Nile (Ethiopia, Sudan and Egypt). An insight into soil erosion/sedimentation mechanisms and mitigation methods plays an imperative role for the sustainable water resources development in the region. This paper presents daily sediment yield simulations in the Upper Blue Nile under different Best Management Practice (BMP) scenarios. Scenarios applied in this paper are (i) maintaining existing conditions, (ii) introducing filter strips, (iii) applying stone bunds (parallel terraces), and (iv) reforestation. The Soil and Water Assessment Tool (SWAT) was used to model soil erosion, identify soil erosion prone areas and assess the impact of BMPs on sediment reduction. For the existing conditions scenario, the model results showed a satisfactory agreement between daily observed and simulated sediment concentrations as indicated by Nash-Sutcliffe efficiency greater than 0.83. The simulation results showed that applying filter strips, stone bunds and reforestation scenarios reduced the current sediment yields both at the subbasins and the basin outlets. However, a precise interpretation of the quantitative results may not be appropriate because some physical processes are not well represented in the SWAT model.

The Soil and Water Assessment Tool (SWAT) is an integrated river basin model that is widely applied within the Nile basin. Up to date, more than 20 peer-reviewed papers describe the use of SWAT for a variety of problems in the upper Nile basin countries, such as erosion modelling, land use and climate change impact modelling and water resources management. The majority of the studies are focused on locations in the tropical highlands in Ethiopia and around Lake Victoria. The popularity of SWAT is attributed to the fact that the tool is freely available and that it is readily applicable through the development of geographic information system (GIS) based interfaces and its easy linkage to sensitivity, calibration and uncertainty analysis tools. The online and free availability of basic GIS data that are required for SWAT made its applicability more straightforward even in data-scarce areas. However, the easy use of SWAT may not always lead to appropriate models which is also a consequence of the quality of the available free databases in these regions. In this paper, we aim at critically reviewing the use of SWAT in the context of the modelling purpose and problem descriptions in the tropical highlands of the Nile basin countries. To evaluate the models that are described in journal papers, a number of criteria are used to evaluate the model set-up, model performances, physical representation of the model parameters, and the correctness of the hydrological model balance. On the basis of performance indicators, the majority of the SWAT models were classified as giving satisfactory to very good results. Nevertheless, the hydrological mass balances as reported in several papers contained losses that might not be justified. Several papers also reported the use of unrealistic parameter values. More worrying is that many papers lack this information. For this reason, most of the reported SWAT models have to be evaluated critically. An important gap is the lack of attention that is given to the vegetation and crop processes. None of the papers reported any adaptation to the crop parameters, or any crop-related output such as leaf area index, biomass or crop yields. A proper simulation of the land cover is important for obtaining correct runoff generation, evapotranspiration and erosion computations. It is also found that a comparison of SWAT applications on the same or similar case study but by different research teams and/or model versions resulted in very different results. It is therefore recommended to find better methods to evaluate the representativeness of the distributed processes and parameters (especially when land use studies are envisaged) or predictions of the future through environmental changes. The main recommendation is that more details on the model set-up, the parameters and outputs should be provided in the journal papers or supplementary materials in order to allow for a more stringent evaluation of these models.

Worldwide, the application of river basin water quality models is increasing, often imposed by law. It is, thus, important to know the degree of uncertainty associated with these models and their application to a specific watershed. These uncertainties lead to errors that are revealed when model outputs are compared to observations. Such uncertainty is typically described by calculating the residuals. However, residuals should not be seen as an estimate of total uncertainty, since through the calibration process, the residuals may be reduced by over-adjustment to the data, which is typically the case for over-parameterised models. Over-adjustment during a calibration period can also lead to highly biased results when the model is applied to other periods or environmental conditions. The total model uncertainties are, therefore, assessed by four components: the sum of the squares of the residuals (SSQ), parameter uncertainties (that can be ignored when their error is much smaller than SSQ), input data uncertainties, and an additional predictive uncertainty that is expressed when the model appears to be biased when it is applied for data other than the data used for calibration. The sources are ranked according to a quantification criterion (magnitude) as well as an identification criterion that depends on the number of observations that are covered by the confidence region. This approach is illustrated with SWAT2003 simulations for flow and sediment of Honey Creek, a tributary of the Sandusky River basin (Ohio). The results show the dominance of the model uncertainty. The input data uncertainty is less important.