ANALYSIS OF THE EFFECT OF RAINFALL AND STREAMFLOW DATA QUALITY AND CATCHMENT DYNAMICS ON STREAMFLOW PREDICTION USING THE RAINFALL-RUNOFF MODEL IHACRES

A lumped-parameter rainfall-runoff model, IHACRES, has been used to pr edict the long-term natural variability of runoff from approximately 1 00 years of daily rainfall and evaporation data for eight different ca tchments. The model efficiently encapsulates the response dynamics of a catchment and is a good predictor of stream discharge. it is well su ited to illustrate the factors influencing the quality of stream disch arge predictions, in terms of rainfall-runoff model fits to daily disc harge in calibration and validation mode and to the flow duration curv e. The predominant factors are rain gauge density, stream gauge rating quality, catchment response dynamics (especially slowflow/baseflow vo lume) and the sampling interval of rainfall discharge (always daily he re). These factors manifest themselves to sufficiently different degre es in the range of catchments studied to reveal a useful appreciation of their individual and combined contributions to the quality of strea mflow prediction. The predictive benefits of improvements in rain gaug e coverage or in stream discharge rating are indicated. A large propor tion of slowflow/baseflow in a catchment is a factor which can compens ate for data quality problems. The analysis and findings in this paper can be used to improve rainfall-runoff model performance and the synt hesis of long-term stream discharge records in a large number and vari ety of catchments. Copyright (C) 1996 Elsevier Science Ltd.