Suitability of SWAT Model for Sediment Yields Modelling in the Eastern Africa - Advances in Data, Methods, Models and Their Applications in Geoscience - page 280

Errors (RE) criteria suggest that the model can fairly/satisfactorily estimate sediment yield for
even poorly gauged catchments (Ndomba et al ., 2005; Ndomba, 2007; Mulungu and Munishi,
(2007); Ndomba and Birhanu, 2008; Ndomba et al ., 2008b; Andualem and Yonas, 2008; Shimelis
et al ., 2010). The latter mainly proves that the models are able to capture the dynamics in time,
but it provides little validation on the identification of the processes and/or the parameters in
space which would require observations at several internal points in the catchment.
4. Conclusions and recommendations
4.1 Conclusions
This chapter presents three study cases in Eastern Africa where the SWAT model was
applied extensively using the available data. In few cases primary data on sediment loads
were explored. These cases represent various climatic conditions within the equatorial
and/or tropical region. Based on the results of this study, the SWAT model seems to be
robust and can be relied upon as a tool for catchment sediment management in the tropics.
However, the model could not capture dynamics of sediment load delivery (i .e . equilibrium
river regime) in some seasons in one catchment. The particular study linked the latter
problem to model deficiency. Based on the simulation results the study has found that all
sorts of farming practices captured by P USLE and C USLE parameters are the main determining
management techniques in reducing soil loss/sediment yield and subsequently
sedimentation problems in the reservoir. Besides, the performances of the SWAT model in
these study cases as well as others conducted in Eastern Africa suggest that the model can
satisfactorily estimate sediment yield for even poorly gauged catchments. The temporal
variability is quite well captured. It should be noted that the calibration of the distributed
parameters was typically done in a “lumped” way using sediment observations at the outlet
instead of using observations at interior locations in the river basin. Therefore, the physical
meaning of these parameters as well as the spatial representativeness could be questioned.
The performance of the model suggests that the model can be used as a research tool in
reservoir sedimentation and sediment yield modelling studies in the region.
The results of these study cases are not conclusive enough because some challenges have not
been addressed. Although the input data varies in type and quality, from coarse-resolution
to high-resolution measured spatial and climate data, there is a general lack of high-
resolution spatial input data. More high-resolution spatial input data may not necessarily
improve the performance of the model, but it may contribute to a better representation of
the spatial variability. For erosion modelling, a high DEM resolution is especially important
because the DEM is used to compute the slopes. Slopes have dual role: they affect the runoff
processes in the hydrology that directly influence the erosion computations, and they are
also directly used in the MUSLE equation.
It should be noted that the authors are aware that the performance of the SWAT model
applications in the study cases can not be compared objectively because the performance is
affected by modelling efforts and techniques, input data quality and catchment
representation of important hydrological features.
4.2 Recommendations
A general recommendation is that more attention needs to be given to the spatial
representativeness of the processes, the process parameters and the input data. The latter
involves: