Hydrological modelling entails constructing mathematical representations of the water cycle within a defined catchment area, linking precipitation, evapotranspiration, infiltration, storage and runoff ...

Machine learning has revolutionised hydrological modelling by offering data-driven alternatives to traditional process-based approaches. Algorithms such as deep neural networks and ensemble learning ...

Hydrologic modelers are increasingly using explainable AI (XAI) to provide additional insight into complex hydrological problems, but a new University of Adelaide study suggests XAI's insights may not ...

Hydrologic models that simulate and predict water flow are used to estimate how natural systems respond to different scenarios such as changes in climate, land use, and soil management. The output ...

In a new study, researchers applied a large-scale model linking surface water to groundwater, which can be used for estimating water resources at a high spatial resolution. Against the backdrop of ...

The fluvial geomorphology field has long investigated the interplay between climate, hydrology, and sediment transport in river systems. Recent studies ...

The hydrologic system is subjected unprecedented stresses and increasing demands driven by climate variabilities, landuse changes, groundwater ...

CHENNAI: The IIT Madras has found that the proposed Mamallan (Kovalam sub-basin) reservoir is hydrologically feasible to ...