Results 1 to 10 of about 307,852 (218)
Hydrology without dimensions [PDF]
Hydrology and Earth System Sciences, 2022 By rigorously accounting for dimensional homogeneity in physical laws, the Π theorem and the related self-similarity hypotheses allow us to achieve a dimensionless reformulation of scientific hypotheses in a lower-dimensional context. This paper presents
A. Porporato, A. Porporato
doaj +5 more sources
50 Years with Nordic Hydrology/Hydrology Research
Hydrology Research, 2022 The history of Nordic Hydrology/Hydrology Research is described from its initiation in 1970 to its current state in 2021. This includes dramatic changes leading first to an ownership transformation to Nordic Association for Hydrology (NAH) in 1976, and ...
Dan Rosbjerg
doaj +3 more sources
Acknowledgment to the Reviewers of Hydrology in 2022
Hydrology, 2023 High-quality academic publishing is built on rigorous peer review [...]
Hydrology Editorial Office
doaj +1 more source
Hydrological post-processing for predicting extreme quantiles [PDF]
Journal of Hydrology 617(Part C) (2023) 129082, 2022 Hydrological post-processing using quantile regression algorithms constitutes a prime means of estimating the uncertainty of hydrological predictions. Nonetheless, conventional large-sample theory for quantile regression does not apply sufficiently far in the tails of the probability distribution of the dependent variable.
arxiv +1 more source
Acknowledgment to Reviewers of Hydrology in 2020
Hydrology, 2021 Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Hydrology maintains its standards for the high quality of its published papers [...]
Hydrology Editorial Office
doaj +1 more source
Quantile-based hydrological modelling [PDF]
Water 13 (2021) 3420, 2021 Predictive uncertainty in hydrological modelling is quantified by using post-processing or Bayesian-based methods. The former methods are not straightforward and the latter ones are not distribution-free (i.e. assumptions on the probability distribution of the hydrological model's output are necessary).
arxiv +1 more source
Acknowledgment to Reviewers of Hydrology in 2021
Hydrology, 2022 Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Hydrology Editorial Office
doaj +1 more source
Expectile-based hydrological modelling for uncertainty estimation: Life after mean [PDF]
Journal of Hydrology 617(Part B) (2023) 128986, 2022 Predictions of hydrological models should be probabilistic in nature. Our aim is to introduce a method that estimates directly the uncertainty of hydrological simulations using expectiles, thus complementing previous quantile-based direct approaches as well as generalizing mean-based approaches. Expectiles are new risk measures in hydrology.
arxiv +1 more source