Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction

摘要

Advances in mesoscale numerical weather pred_ication make it possible to provide rainfall forecasts along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate high-resolution NWPs directly into flood forecasting systems in order to obtain an extended lead time. It is recognised, how_ever, that direct application of rainfall outputs from the NWP model can contribute considerable uncertainty to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be magnified by the scaling process. As the ensemble weather forecast has become operationally available, it is of particu_lar interest to the hydrologist to investigate both the poten_tial and implication of ensemble rainfall inputs to the hy_drological modelling systems in terms of uncertainty prop_agation. In this paper, we employ a distributed hydrologi_cal model to analyse the performance of the ensemble flow forecasts based on the ensemble rainfall inputs from a short-range high-resolution mesoscale weather model. The results show that: (l) The hydrological model driven by QPF can produce forecasts comparable with those from a raingauge_driven one; (2) The ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast it_self; and (3) the uncertainties as well as systematic biases are sometimes significant and, as such, extra effort needs to be made to improve the quality of such a system.