The impact of rainfall interpolation techniques and unit hydrograph estimation has been explored for four gauged locations in the Brahmani basin in east India. The use of ground-based and satellite-based data, coupled with testing two interpolation techniques (Thiessen polygon and inverse distance weighting), can yield improved rainfall estimates and fits to observed flows. Due to the presence of significant errors in the areal rainfall estimate it was found that identification of known errors in rainfall data can assist in focusing model calibration on catchment response, thereby reducing the uncertainty in model parameter values. Similarly, using several approaches to estimate the unit hydrograph can assist in reducing uncertainty. The resulting performance of the model for the gauged sites in the Brahmani basin gave Nash–Sutcliffe efficiency (NSE) values for the calibration period of 0.6–0.7. For this basin, the inverse distance weighting approach corrected for spatial variation in rainfall distribution generally gave the best fits to the observed streamflow. Sensitivity to errors in the rainfall surface limits the applicability for this approach in modelling the flows in ungauged basins, however.
Keywords: model calibration, parameter estimation, rainfall estimation, unit hydrograph