Reliable runoff estimation is important for simulating long-term crop yields in semi-arid areas. It requires reliable data including soil and rainfall characteristics. This paper aims to simulate runoff for each rainfall event on the Glen/Tukulu ecotope, in central South Africa, using annual runoff data measured over 18 years (1937 to 1955) on a conventional tilled soil, annually planted to maize, and a bare untilled soil. Runoff calculated for these two treatments provides information needed to simulate long-term crop yields using conventional tillage and in-field water harvesting. The PutuRun model was used to stochastically disaggregate daily rainfall data into shorter duration rainfall intensities and to simulate runoff for each rainfall event during a particular season. The simulated runoff data were summed for each season and compared with the observed annual runoff values during the respective years to evaluate the performance of the model. The model was calibrated using half of the data and validated using the rest. Calibration was carried out by running the model a number of times with a different set of input parameter values, until acceptable results were obtained. The following statistical results were obtained for the validation tests: for the maize plots index of agreement (d) = 0.85, root mean square error (RMSE) = 24 mm, mean absolute error (MAE) = 18 mm, systematic RMSE (RMSEs) = 16 mm, unsystematic RMSE (RMSEu) = 17 mm, and coefficient of determination (r 2 ) = 0.58; and for the bare plots d = 0.90, RMSE = 51 mm, MAE = 48 mm, RMSEs = 13 mm, RMSEu = 49 mm, and r 2 = 0.74. It is concluded that the PutuRun Model can be used with reasonable confidence after calibration to simulate long-term runoff on conventionally tilled, and bare untilled plots on the Glen/Tukulu ecotope using daily rainfall data. This procedure is expected to yield satisfactory results on other ecotopes with similar soil, slope, and rainfall characteristics.

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Soil water content is a major factor that affects the hydrological response of a hillslope or catchment. It is therefore important to have reliable soil water content data to estimate catchment water yield. Daily soil water content (θ) data was calculated based on weekly measured and other data for the Weatherley grassland catchment in South Africa. A modelling procedure, based on the soil water balance equation and the interpretation of the physical properties of soils was used to calculate daily θ for all 28 sites for the six-year period. A statistical model performance indicated that the mean index of agreement was 0.88, root mean square error (RMSE) was 6.8 mm water per 300 mm soil and mean unsystematic RMSE to total RMSE was 93%. These results indicated that the calculated soil water contents agreed well with the measured values and could therefore be used with reasonable confidence to fill data gaps. The proposed procedure therefore affords the possibility to increase the resolution of irregular measured soil water content data. This would significantly advance the usability of such data, because the influence of rainfall events on soil water content is frequently missed by manual soil water content measurements.

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