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%, 13.0%, and 1.05, respectively, which are superior to those of the lumped model. Furthermore, to evaluate the difference between the proposed and existing distributed models, the proposed distributed model was compared with the variable infiltration capacity (VIC) model at various time steps. The proposed distributed model could better capture the flooding processes at shorter time steps, especially at 3 h. Therefore, it could be considered a practical tool for sub-daily flood forecasting in semi-humid and semi-arid watersheds.