Abstract The Prediction in Ungauged Basins (PUB) initiative of the International Association
of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium …

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 …

Long short-term memory (LSTM) models are recurrent neural networks from the field of deep
learning (DL) which have shown promise for time series modelling, especially in conditions …

Neural networks have been shown to be extremely effective rainfall-runoff models, where
the river discharge is predicted from meteorological inputs. However, the question remains …

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 essay discusses some of the issues involved in the identification and predictions of
hydrological models given some calibration data. The reasons for the incompleteness of …

Ambiguities in the representation of environmental processes have manifested themselves
in a plethora of hydrological models, differing in almost every aspect of their …

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 …

The science of hydrology is on the threshold of major advances, driven by new hydrologic
measurements, new methods for analyzing hydrologic data, and new approaches to …

Uncertainty in the predictions of science when applied to the environment is an issue of
great current relevance in relation to the impacts of climate change, protecting against …