Suitability of SWAT Model for Sediment Yields Modelling in the Eastern Africa - Advances in Data, Methods, Models and Their Applications in Geoscience - page 273

Mean monthly Stream
flow discharges
[m 3 /s]

Sediment load,
[t/month]

Statistic

No. 180 180.00

Max 421.930 179,841

Min 1.000 200

Mean 47.710 12,596

Standard Deviation, STD 78.010 18,178

Coefficient of Variation, Cv (%) 163.510 144

Standard Error of the Mean, SEM 5.810 1355

Table 2c-2. A summary of continuous monthly sediment flow data for the Koka Reservoir
catchment for the period from January 1990 to December 2004 at the Koka Reservoir as
adopted from Endale (2008)

2.4 SWAT model applications procedures and assumptions
It should be noted that SWAT, if not properly applied, may result in parameter uncertainty
problems. Therefore, elaboration of the rationale of each application step is necessary.
In these study cases the model was set up to represent the spatial variability of the main
runoff-sediment yield controlling features such as soils, land use/cover, terrain ( i.e , slope
and slope length), river channels and reservoirs. The distributed nature of the sediment
yield and erosion representation (lumped, semi and fully distributed) depended on the
availability of data and computation resources.
The Latin Hypercube One-factor-At-a-Time (LH-OAT) design as proposed by Morris (1991)
implemented in SWAT was used as a sensitivity analysis tool. Sensitivity analysis of
hydrology and sediment transport components parameters were conducted without and/or
with observed data before and after calibration. Various lengths of simulations ( i.e . 2, 4, 6, 8
yrs and greater) were tested in order to capture model input ( i.e ., parameter and data)
uncertainty. These analyses were used to identify the sensitive parameters.
Manual calibration, expert knowledge and automatic calibration techniques were tested for
the calibration procedures. The autocalibration routine based on the Shuffled Complex
Evolution-University of Arizona (SCE-UA) that is incorporated in the SWAT model has
been used very often (Duan et al ., 1992). In one of the study cases, SRC, the SUFI-2 program
which combines calibration and uncertainty analysis (Abbaspour et al ., 2004, 2007) was used.
This tool is widely used in the region (Shimelis et al ., 2010). The sensitive model parameters
were adjusted within their feasible ranges during calibration to minimize model prediction
errors for daily and monthly flow and sediment loads. In one of the study cases, i.e . the
NYM Reservoir catchment, soil erodibility (K USLE ) (a MUSLE factor) was estimated
according to the equation proposed by Mulengera and Payton (1999) for tropics. Bias-
corrected rating curves were developed and used to interpolate or extrapolate sediment
loads (Ndomba et al ., 2008b). It should be noted that to date there is no consensus on how to
develop an excellent rating curve, especially from a short period of records. Ndomba et al .
(2008b) developed the rating curve from continuous subdaily suspended sediment data ( i.e .
2 to 12 samples a day) collected by an automatic pumping sampler (ISCO 6712). The ISCO
6712 sampler data were calibrated by daily-midway and intermittent-cross section sediment
samples collected by a depth-integrating sampler (D-74). The sediment loads from rating