Approximately 1 billion ha of the global land surface is currently salt-affected, representing
about 7% of the earth's land surface. Whereas most of it results from natural geochemical …

Water | Free Full-Text | Review: Sources of Hydrological Model Uncertainties and Advances
in Their Analysis Next Article in Journal Assessing the Influence of Compounding Factors to …

This paper is derived from a keynote talk given at the Google's 2020 Flood Forecasting
Meets Machine Learning Workshop. Recent experiments applying deep learning to rainfall …

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

Bayesian inference has found widespread application and use in science and engineering
to reconcile Earth system models with data, including prediction in space (interpolation) …

In order to use environmental models effectively for management and decision-making, it is
vital to establish an appropriate level of confidence in their performance. This paper reviews …

With recent developments in computational techniques, Data-driven Machine Learning
Models (DMLs) have shown great potential in simulating streamflow and capturing the …

Rainfall-Runoff Modelling: The Primer, Second Edition is the follow-up of this popular and
authoritative text, first published in 2001. The book provides both a primer for the novice and …

This review and commentary sets out the need for authoritative and concise information on
the expected error distributions and magnitudes in observational data. We discuss the …

In catchment hydrology, it is in practice impossible to measure everything we would like to
know about the hydrological system, mainly due to high catchment heterogeneity and the …