Disaggregated monthly hydrological models can outperform daily models in providing daily flow statistics and extrapolate well to a drying climate

Abstract

Daily timescale hydrological information is important for many purposes such as flood estimation, predicting the consequences of catchment management and meeting the needs of freshwater ecology. In hydrological assessments, daily timestep modelling is typically used because of the availability of daily data and many of the processes governing impacts occur at this timescale. However, daily models can suffer from poor performance in certain contexts (e.g. drier climates), and their computational requirements can make it difficult to efficiently explore many sources of uncertainty in some situations, such as understanding the impacts of climate change in larger water resource systems. Here, we..