A new method of rainfall temporal downscaling: a case study on sanmenxia station in the Yellow River Basin

Abstract. Distributed hydrological models are effective tools for Predictions in Ungauged Basins (PUB). The rainfall input uncertainty is an important source of hydrological model uncertainty. With the improvement of hydrological model accuracy, the requirements of the accuracy of input data are correspondingly improved. Daily rainfall data is the most common data that the researchers can get, however this cannot satisfy the requirement of hydrological simulation. Therefore, researches of daily rainfall temporal downscaling method is focus in distributed hydrological models. In the Yellow River Basin, the random distribution method, the sinusoidal distribution method and the normal distribution method all underestimate the maximum rainfall intensity. This paper raises a new daily rainfall downscaling method called proportional method based on the rainfall hyetograph of 28 years. This method significantly improves the accuracy of the maximum rainfall intensity simulation and the rainfall process curves, so this method can improve the accuracy of modeling the hydrology process and reducing the input uncertainty of the rainfall data.