airGR et airGRteaching : deux packages pour la modélisation pluie-débit et l'enseignement de l'hydrologie
| Autor: | Delaigue, O., Thirel, G., Coron, L., Brigode, P. |
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| Přispěvatelé: | Hydrosystèmes continentaux anthropisés : ressources, risques, restauration (UR HYCAR), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), EDF (EDF), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), IRSTEA ANTONY UR HYCAR FRA, EDF TOULOUSE FRA, UNIVERSITE DE NICE SOPHIA ANTIPOLIS FRA |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | 15th edition of the International R User Conference 15th edition of the International R User Conference, Jul 2019, Toulouse, France. pp.1, 2019 |
| Popis: | International audience; The use of R is growing fast on every step of hydrological studies, from the retrieval of hydro-meteorological data, to spatial analysis and cartography, hydrological modeling, statistics, and the design of static and dynamic visualizations (Slater et al., 2019, HESSD). Recently, IRSTEA developed an R package called airGR (Coron et al, 2017, EM&S, and 2018), to make the GR rainfall-runoff models widely available and facilitate reproducible science. It is available on the CRAN and includes efficient and fast-running hydrological models. The airGR package was designed to facilitate the use by non-expert users and allows the user to customize evaluation criteria, models or calibration algorithm. To help students learning and because the GR models are widely used in hydrology courses in French universities or engineering schools, we developed a package called airGRteaching (Delaigue et al., 2018, HIC, and 2018) based on airGR. This package reduces modeling to only three functions. In addition, the package offers various graphical outputs, static and dynamic (using the dygraphs package) to easily explore the model input data, as well as the results obtained during the model calibration or simulation phase. Finally, airGRteaching offers a Shiny interface allowing students to fully understand the role of each parameter or internal state of the models. |
| Databáze: | OpenAIRE |
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