With global warming and urbanization accelerating, urban flooding is becoming more severe. Real-time forecasting plays a key role in disaster mitigation, but traditional hydrodynamic models are too resource-intensive for timely prediction. Machine learning models offer high efficiency but often lack accuracy in simulating spatiotemporal flood dynamics. This study proposes a new data-driven model, which performs well in a flood-prone area of Macao.

This study presents an experimental framework (EF-SPM) to disentangle and evaluate the benefits of spatially explicit parameterization and multi-gauge calibration in distributed hydrological modelling. Intensive experiments in a nested catchment show that both strategies consistently improve streamflow simulations across sub-basins, while exhibiting a trade-off in parameter identifiability, with their cross-benefit manifested in an effective alleviation of multi-objective competition.

Water budget non-closure is a widespread phenomenon among multisource datasets which undermines the robustness of hydrological inferences. This study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.

Considering the impact of the special geological and climatic conditions of the Qinghai–Tibet Plateau on the hydrological cycle, this study established the WEP-QTP hydrological model. The snow cover and gravel layers affected the temporal and spatial changes in frozen soil and improved the regulation of groundwater on the flow process. Ignoring he influence of special underlying surface conditions has a great impact on the hydrological forecast and water resource utilization in this area.

Combining the geological characteristics of the thin soil layer on the thick gravel layer and the climate characteristics of the long-term snow cover of the Qinghai-Tibet Plateau, the WEP-QTP hydrological model was constructed by dividing a single soil structure into soil and gravel. In contrast to the general cold area, the special environment of the Qinghai–Tibet Plateau affects the hydrothermal transport process, which can not be ignored in hydrological forecast and water resource assessment.