Droughts can have strong environmental and socio-economic impacts in the Mediterranean
region, in particular for countries relying on rain-fed agricultural production, but also in areas …

Flood hazard mapping (FHM) has undergone significant development in terms of approach
and capacity of the result to meet the target of policymakers for accurate prediction and …

Rainfall–runoff modelling is one of the key challenges in the field of hydrology. Various
approaches exist, ranging from physically based over conceptual to fully data-driven …

Although machine learning (ML) techniques are increasingly used in rainfall-runoff models,
most of them are based on one-dimensional datasets. In this study, a rainfall-runoff model …

Nowadays, mathematical models of hydrological systems are used routinely to guide
decision making in diverse subjects, such as: environmental and risk assessments, design …

Deep Learning (DL) methods have gained significant recognition in hydrology and water
resources applications in recent years. Beginning with a discussion on fundamental …

Ensemble flood forecasting has gained significant momentum over the past decade due to
the growth of ensemble numerical weather and climate prediction, expansion in high …

Hydrological model calibration combining Earth observations and in situ measurements is a
promising solution to overcome the limitations of the traditional streamflow‐only calibration …

In hydrology, two somewhat competing philosophies form the basis of most process-based
models. At one endpoint of this continuum are detailed, high-resolution descriptions of small …

Plant functional traits determine vegetation responses to environmental variation, but
variation in trait values is large, even within a single site. Likewise, uncertainty in how these …