Commit 3f827678 authored by Delaigue Olivier's avatar Delaigue Olivier

v1.4.3.51 DOC: references to GR5H added in V01_get_started vignette (and bib...

v1.4.3.51 DOC: references to GR5H added in V01_get_started vignette (and bib file) and web linked corrected (from irstea to inrae)
parent ad68c31d
Package: airGR
Type: Package
Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
Version: 1.4.3.50
Version: 1.4.3.51
Date: 2020-01-20
Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl"), comment = c(ORCID = "0000-0002-1503-6204")),
......
......@@ -2,7 +2,7 @@
### 1.4.3.50 Release Notes (2020-01-20)
### 1.4.3.51 Release Notes (2020-01-20)
#### New features
......
@phdthesis{ficchi_adaptive_2017,
title = {An adaptive hydrological model for multiple time-steps: diagnostics and improvements based on fluxes consistency},
shorttitle = {An adaptive hydrological model for multiple time-steps},
url = {http://www.theses.fr/2017PA066097},
abstract = {Cette thèse vise à explorer la question du changement d'échelle temporelle en modélisation hydrologique conceptuelle. Les principaux objectifs sont : (i) étudier les effets du changement du pas de temps sur les performances, les paramètres et la structure des modèles hydrologiques ; (ii) mettre au point un modèle pluie-débit applicable à différents pas de temps. Notre point de départ est le modèle global journalier GR4J, développé à Irstea. Ce modèle a été choisi comme le modèle de référence à adapter à d'autres résolutions plus fines, jusqu'à des pas de temps infra-horaires, en suivant une approche descendante. Pour nos tests, nous avons construit une base de données de 240 bassins versants non influencés en France, à différents pas de temps allant de 6 minutes à 1 jour, en utilisant: (i) les données pluviométriques à 6 minutes et la réanalyse des lames d'eau journalières à plus haute résolution spatiale ; (ii) les données de température journalière pour le calcul de l'évapotranspiration potentielle ; (iii) les données hydrométriques à pas de temps variable. Nous avons étudié l'impact de la distribution temporelle des entrées sur les performances du modèle en se focalisant sur la simulation de crue, sur la base de 2400 événements. Ensuite, notre évaluation du modèle a porté sur l'analyse de la cohérence des flux internes du modèle à différents pas de temps, afin d'assurer une performance satisfaisante à travers un fonctionnement du modèle cohérent. Notre diagnostic du modèle nous a permis d'identifier une amélioration de la structure du modèle à différents pas de temps infra-journaliers basée sur la complexification de la composante d'interception du modèle.},
urldate = {2017-11-24},
school = {Université Pierre et Marie Curie, Paris 6},
author = {Ficchi, Andrea},
month = feb,
year = {2017},
keywords = {Rainfall-runoff modelling, airGRcite, Cohérence structurelle, Événements de crue, Interception, Modèles GR, Modélisation pluie-Débit, Pas de temps fin, Short time step}
}
@article{ficchi_hydrological_2019,
title = {Hydrological modelling at multiple sub-daily time steps: model improvement via flux-matching},
issn = {00221694},
shorttitle = {Hydrological modelling at multiple sub-daily time steps},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0022169419305281},
doi = {10.1016/j.jhydrol.2019.05.084},
language = {en},
urldate = {2019-06-11},
journal = {Journal of Hydrology},
author = {Ficchì, Andrea and Perrin, Charles and Andréassian, Vazken},
month = jun,
year = {2019},
keywords = {airGR, airGRcite}
}
@phdthesis{mathevet_quels_2005,
address = {Paris},
title = {Quels modèles pluie-débit globaux au pas de temps horaire ? {Développements} empiriques et comparaison de modèles sur un large échantillon de bassins versants},
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......@@ -10,7 +10,7 @@ vignette: >
# Introduction
**airGR** is a package that brings into the [**R software**](https://cran.r-project.org/) the hydrological modelling tools used and developed at the [Catchment Hydrology Research Group](https://webgr.irstea.fr/en/) at [Irstea (France)](http://www.irstea.fr/en/), including the [**GR rainfall-runoff models**](https://webgr.irstea.fr/en/modeles/) and a snowmelt and accumulation model, [**CemaNeige**](https://webgr.irstea.fr/en/modeles/modele-de-neige/). Each model core is coded in **Fortran** to ensure low computational time. The other package functions (i.e. mainly the calibration algorithm and the efficiency criteria calculation) are coded in **R**.
**airGR** is a package that brings into the [**R software**](https://cran.r-project.org/) the hydrological modelling tools used and developed at the [Catchment Hydrology Research Group](https://webgr.inrae.fr/en/) at [INRAE (France)](https://webgr.inrae.fr/en/), including the [**GR rainfall-runoff models**](https://webgr.inrae.fr/en/modeles/) and a snowmelt and accumulation model, [**CemaNeige**](https://webgr.inrae.fr/en/models/snow-model/). Each model core is coded in **Fortran** to ensure low computational time. The other package functions (i.e. mainly the calibration algorithm and the efficiency criteria calculation) are coded in **R**.
The **airGR** package has been designed to fulfill two major requirements: to facilitate the use by non-expert users and to allow flexibility regarding the addition of external criteria, models or calibration algorithms. The names of the functions and their arguments were chosen to this end. **airGR** also contains basics plotting facilities.
......@@ -22,17 +22,20 @@ Six hydrological models and one snowmelt and accumulation model are implemented
The models can be called within **airGR** using the following functions:
* `RunModel_GR4H()`: four-parameter hourly lumped hydrological model [@mathevet_quels_2005]
* `RunModel_GR5H()`: five-parameter hourly lumped hydrological model [@ficchi_adaptive_2017; @ficchi_hydrological_2019]
* `RunModel_GR4J()`: four-parameter daily lumped hydrological model [@perrin_improvement_2003]
* `RunModel_GR5J()`: five-parameter daily lumped hydrological model [@le_moine_bassin_2008]
* `RunModel_GR6J()`: six-parameter daily lumped hydrological model [@pushpalatha_downward_2011]
* `RunModel_GR2M()`: two-parameter monthly lumped hydrological model [@mouelhi_vers_2003; @mouelhi_stepwise_2006]
* `RunModel_GR1A()`: one-parameter yearly lumped hydrological model [@mouelhi_vers_2003; @mouelhi_linking_2006]
* `RunModel_CemaNeige()`: two-parameter degree-day snowmelt and accumulation model [@valery_as_2014]
* `RunModel_CemaNeigeGR4H()`: combined use of **GR4H** and **CemaNeige**
* `RunModel_CemaNeigeGR5H()`: combined use of **GR5H** and **CemaNeige**
* `RunModel_CemaNeigeGR4J()`: combined use of **GR4J** and **CemaNeige**
* `RunModel_CemaNeigeGR5J()`: combined use of **GR5J** and **CemaNeige**
* `RunModel_CemaNeigeGR6J()`: combined use of **GR6J** and **CemaNeige**
The [**GRP**](https://webgr.irstea.fr/en/modeles/modele-de-prevision-grp/) forecasting model and the [**Otamin**](https://webgr.irstea.fr/en/modeles/otamin/) predictive uncertainty tool are not available in **airGR**.
The [**GRP**](https://webgr.inrae.fr/en/models/hydrological-forecasting-model-grp/) forecasting model and the [**Otamin**](https://webgr.inrae.fr/en/software/otamin/) predictive uncertainty tool are not available in **airGR**.
In this vignette, we show how to prepare and run a calibration and a simulation with airGR hydrological models.
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