On the propagation of uncertainty in weather radar estimates of rainfall through hydrological models

Abstract

The generation of flow forecasts using rainfall inputs to hydrological models has been developed over many years. Unfortunately, errors in input data to models may vary considerably depending upon the different sources of data such as raingauges, radar and high resolution Numerical Weather Prediction (NWP) models. This has hampered the operational use of radar for quantitative flow forecasting. The manner with which radar rainfall input and model parametric uncertainty influence the character of the flow simulation uncertainty in hydrological models has been investigated by several authors. In this paper an approach to this problem based upon a stochastic hydrological model is considered. The errors in the input data, although they may be constrained, do propagate through the model to the flow predictions. Previous work on this error propagation through a fully distributed model is described, and a similar analysis for a stochastic hydrological model implemented in a mixed rural and urban area in north-west England carried out. Results are compared with those previously published for an American catchment. A possible approach to selecting flow forecast ensemble members is proposed. © 2009 Royal Meteorological Society.