Abstract:
The agricultural drainage engineering community is steadily shifting the design of subsurface drainage systems from the
experience-based design approach to the simulation-based design approach. As with any design problem, two challenges
are faced; firstly, how to determine all the input data required by the simulation model, and secondly to, a priori, anticipate
what the performance of the designed system will be. This study sought to evaluate the performance of the WaSim model
to simulate fluctuating water table depths (WTD), and drainage discharges (DD) in KwaZulu-Natal Province, South Africa.
Saturated hydraulic conductivity (Ksat), which is an input to the WaSim model, was estimated by the Rosetta computer program,
based on soil particle size distribution data, bulk density, and soil water retention characteristics at pressure heads of
– 33 and – 1500 kPa. performance of the WaSim model was statistically assessed using the coefficient of determination (R2),
coefficient of residual mass (CRM), mean absolute error (MAE), mean percent error (MPE), and the nash–sutcliffe efficiency
(NSE). during the validation period, the WaSim model predicted WTDs with R2, CRM, MAE, MPE, and NSE of 0.86, 0.003,
4.9 cm, 6.0%, and 0.98, respectively. In the same validation period, the model predicted DDs with R2, CRM, MAE, MPE,
and NSE of 0.57, 0.002, 0.30 mm day−
1,11%, and 0.76, respectively. These results suggest that the use of Rosetta-estimated
Ksat data as inputs to the WaSim model compromised its accuracy and applicability as a subsurface drainage design tool.
Owing to the relatively low R2 value of 0.57, and that the WaSim model was empirically developed, we recommend further
improvement on the calibration of the model for it to be suitable for application under the prevailing conditions. Also, in the
absence of other means of determining Ksat, we caution the use of Rosetta-estimated Ksat data as inputs to the WaSim model
for the design and analysis of subsurface drainage systems in KwaZulu-Natal Province, South Africa.
