The sensitivity of catchment runoff models to rainfall data at different spatial scales

The sensitivity of catchment runoff models to rainfall is investigated at a variety of spatial scales using data from a dense raingauge network and we ather radar. These data form part of the HYREX (HYdrological Radar EXperime nt) dataset. They encompass records from 49 raingauges over the 135 km(2) B rue catchment in south-west England together with 2 and 5 km grid-square ra dar data. Separate rainfall time-series for the radar and raingauge data ar e constructed on 2, 5 and 10 km grids, and as catchment average values, at a 15 minute time-step. The sensitivity of the catchment runoff models to th ese grid scales of input data is evaluated on selected convective and strat iform rainfall events. Each rainfall time-series is used to produce an ense mble of modelled hydrographs in order to investigate this sensitivity. The distributed model is shown to be sensitive to the locations of the raingaug es within the catchment and hence to the spatial variability of rainfall ov er the catchment. Runoff sensitivity is strongest during convective rainfal l when a broader spread of modelled hydrographs results, with twice the var iability of that arising from stratiform rain. Sensitivity to rainfall data and model resolution is explored and, surprisingly, best performance is ob tained using a lower resolution of rainfall data and model. Results from th e distributed catchment model, the Simple Grid Model, are compared with tho se obtained From a lumped model, the PDM. Performance from the distributed model is found to be only marginally better during stratiform rain (R-2 of 0.922 compared to 0.911) but significantly better during convective rain (R -2 of 0.953 compared to 0.909). The improved performance from the distribut ed model can, in part, be accredited to the excellence of the dense raingau ge network which would not be the norm for operational flood warning system s. In the final part of the paper, the effect of rainfall resolution on the performance of the 2 km distributed model is explored. The need to recalib rate the model for use with rainfall data of a given resolution, particular ly for periods of convective rain, is highlighted. Again, best performance is obtained using lower resolution rainfall data. This is interpreted as ev idence for the need to improve the distributed model structure to make bett er use of the higher resolution information on rainfall and topographic con trols on runoff. Degrading the resolution of rainfall data, model or both t o achieve the smoothing apparently needed is not seen as wholly appropriate .