The effect of spatial rainfall variability on water balance modelling for south-eastern Australian catchments

• We evaluate spatial rainfall variability effect using virtual experiments.
• Spatial rainfall variability affects accuracy of water balance modelling.
• Effects of spatial rainfall variability are not uniform on water balance components.
• Ignoring spatial rainfall variability results in underestimation of streamflow.
• Effect is more pronounced in catchments with larger rainfall variability.

SummarySpatial rainfall variability is considered an important factor affecting the accuracy of streamflow prediction. This study evaluated the effect of spatial rainfall variability on water balance modelling by conducting a series of virtual experiments. The three-layer Variable Infiltration Capacity model (VIC-3L) was applied using both uniform and spatially variable rainfall for 60 catchments in south-eastern Australia. The spatially variable rainfall was generated from the 0.05° gridded SILO daily rainfall with different degrees of variability. The VIC-3L model was calibrated against observed daily streamflow using gridded SILO daily rainfall to generate reference parameter values. Then the model was applied using the generated spatially variable rainfall and reference parameter values to produce virtual water balance components associated with different spatially variable rainfall. Differences between the lumped and distributed modelling (i.e. virtual experiments) represent the effects of spatial rainfall variability on water balance modelling. The results showed that spatial rainfall variability interacts with catchments characteristics to influence hydrological processes and the effects are not uniform on different water balance components. For a given rainfall total, ignoring spatial rainfall variability will result in underestimation of the total streamflow volume and overestimation of evapotranspiration. Effect of spatial rainfall variability on water balance modelling is more pronounced in catchments with larger rainfall variability. In most cases, information on spatial rainfall variability will help to improve accuracy of water balance modelling. However, in some cases, lumped water balance modelling (i.e. ignoring spatial rainfall variability) may outperform distributed modelling due to catchment filtering effect. The results from this study suggest that more accurate information of rainfall spatial distribution in a catchment can help to improve water balance modelling.