Articles | Volume 25, issue 7
https://doi.org/10.5194/hess-25-3937-2021
https://doi.org/10.5194/hess-25-3937-2021
Technical note
 | 
08 Jul 2021
Technical note |  | 08 Jul 2021

Technical note: Hydrology modelling R packages – a unified analysis of models and practicalities from a user perspective

Paul C. Astagneau, Guillaume Thirel, Olivier Delaigue, Joseph H. A. Guillaume, Juraj Parajka, Claudia C. Brauer, Alberto Viglione, Wouter Buytaert, and Keith J. Beven

Related authors

Physically based modelling of glacier evolution under climate change in the tropical Andes
Jonathan D. Mackay, Nicholas E. Barrand, David M. Hannah, Emily Potter, Nilton Montoya, and Wouter Buytaert
The Cryosphere, 19, 685–712, https://doi.org/10.5194/tc-19-685-2025,https://doi.org/10.5194/tc-19-685-2025, 2025
Short summary
Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025,https://doi.org/10.5194/hess-29-683-2025, 2025
Short summary
CAMELS-FR dataset: A large-sample hydroclimatic dataset for France to explore hydrological diversity and support model benchmarking
Olivier Delaigue, Guilherme Mendoza Guimarães, Pierre Brigode, Benoît Génot, Charles Perrin, Jean-Michel Soubeyroux, Bruno Janet, Nans Addor, and Vazken Andréassian
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-415,https://doi.org/10.5194/essd-2024-415, 2024
Revised manuscript accepted for ESSD
Short summary
On the use of streamflow transformations for hydrological model calibration
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024,https://doi.org/10.5194/hess-28-4837-2024, 2024
Short summary
Hyper-resolution flood hazard mapping at the national scale
Günter Blöschl, Andreas Buttinger-Kreuzhuber, Daniel Cornel, Julia Eisl, Michael Hofer, Markus Hollaus, Zsolt Horváth, Jürgen Komma, Artem Konev, Juraj Parajka, Norbert Pfeifer, Andreas Reithofer, José Salinas, Peter Valent, Roman Výleta, Jürgen Waser, Michael H. Wimmer, and Heinz Stiefelmeyer
Nat. Hazards Earth Syst. Sci., 24, 2071–2091, https://doi.org/10.5194/nhess-24-2071-2024,https://doi.org/10.5194/nhess-24-2071-2024, 2024
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
A diversity-centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci., 29, 785–798, https://doi.org/10.5194/hess-29-785-2025,https://doi.org/10.5194/hess-29-785-2025, 2025
Short summary
Simulating the Tone River eastward diversion project in Japan carried out 4 centuries ago
Joško Trošelj and Naota Hanasaki
Hydrol. Earth Syst. Sci., 29, 753–766, https://doi.org/10.5194/hess-29-753-2025,https://doi.org/10.5194/hess-29-753-2025, 2025
Short summary
Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025,https://doi.org/10.5194/hess-29-683-2025, 2025
Short summary
Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025,https://doi.org/10.5194/hess-29-627-2025, 2025
Short summary
Heavy-tailed flood peak distributions: what is the effect of the spatial variability of rainfall and runoff generation?
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 29, 447–463, https://doi.org/10.5194/hess-29-447-2025,https://doi.org/10.5194/hess-29-447-2025, 2025
Short summary

Cited articles

Anderson, E. A.: A point energy and mass balance model of a snow cover, vol. 19, US Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, Office of Hydrology, Silver Spring, US, 1976. a
Anderson, E. A.: Snow accumulation and ablation model SNOW-17, NOAA’s National Weather Service Hydrology Laboratory NWSRFS user manual, 61 pp., Silver Spring, US, 2006. a, b
Andréassian, V., Perrin, C., Berthet, L., Le Moine, N., Lerat, J., Loumagne, C., Oudin, L., Mathevet, T., Ramos, M.-H., and Valéry, A.: HESS Opinions ”Crash tests for a standardized evaluation of hydrological models”, Hydrol. Earth Syst. Sci., 13, 1757–1764, https://doi.org/10.5194/hess-13-1757-2009, 2009. a
Andrews, F. T. and Guillaume, J. H.: hydromad: Hydrological Model Assessment and Development, available at: http://hydromad.catchment.org/ (last access: 6 July 2021), R package version 0.9-26, 2018. a, b, c, d
Andrews, F. T., Croke, B. F. W., and Jakeman, A. J.: An open software environment for hydrological model assessment and development, Environ. Modell. Softw., 26, 1171–1185, https://doi.org/10.1016/j.envsoft.2011.04.006, 2011. a, b
Download
Short summary
The R programming language has become an important tool for many applications in hydrology. In this study, we provide an analysis of some of the R tools providing hydrological models. In total, two aspects are uniformly investigated, namely the conceptualisation of the models and the practicality of their implementation for end-users. These comparisons aim at easing the choice of R tools for users and at improving their usability for hydrology modelling to support more transferable research.
Share