Artificial intelligence has transformed hydrological modelling by offering robust tools for capturing complex and nonlinear processes that govern the movement and distribution of water. Data-driven ...

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 ...

As climate change increases the risk of flooding worldwide, understanding how floods form has never been more important.

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 ...