Development of A Distributed Modeling Framework Considering Spatiotemporally Varying Hydrological Processes for Sub-Daily Flood Forecasting in Semi-Humid and Semi-Arid Watersheds

The complex and varied climatic conditions, short duration and high intensity of rainfall, and complex subsurface properties of semi-humid and semi-arid watersheds pose challenges for sub-daily flood forecasting. Previous studies have revealed that lumped models are insufficient because they do not effectively account for the spatial variability in hydrological processes. Extending the lumped model to a distributed modeling framework is a reliable approach for runoff simulation purposes. However, existing distributed models do not adequately characterize the high spatiotemporal variability in sub-daily hydrological processes. To address the above concerns, a distributed modeling framework was proposed that is extended from a lumped model and accounts for the effects of time-varying rainfall intensity and reservoir regulation on hydrological processes. The results indicated that the proposed distributed model could simulate sub-daily flood events with mean values of the NSE, BIAS, RPE, and PTE evaluation metrics of 0.80, 9.2