Vollständiger Abstract
Worum geht es in dieser Arbeit?
<p>As they are useful and convenient, rainfall-runoff models are widely used in research and engineering. Applications of rainfall-runoff models range from flood risks estimation, to water resources management and low-flow related issues. The Catchment Hydrology Group at INRAE (Antony, France) has developed a set of conceptual GR models over the past 30 years with the main objective of designing models that are as efficient as possible in terms of streamflow simulation, and are applicable to a wide range of catchments with low data requirements.</p><p>In recent years, in order to provide access to these hydrological models, INRAE has developed an open-source package named airGR for the R free software environment. This tool embeds the GR4H, GR4J, GR2M and GR1A models, among others, which operate at the hourly, daily, monthly and annual time steps. This package also includes a snow accumulation and melt module, a calibration tool, efficiency criterion calculations and plotting facilities.</p><p>Recently, a galaxy of tools (fig. 1) has formed around airGR (hydroGR.github.io/airGR). <br>airGRteaching R package is designed for simple applications and requires limited coding knowledge. It also offers a graphical user interface particularly useful for educational purposes. <br>airGRiwrm R package (for integrated water resources management) provides tools to integrate human influences in a semi-distributed hydrological model, namely local flow injections or withdrawals based on predefined flows, or on user-defined decision algorithms given model outputs during simulation. <br>airGRdatassim R package allows assimilating uncertain observed data to constrain the GR model predictions. Two data assimilation methods are available: the ensemble Kalman Filter & the Particle Filter. It also includes a model inputs perturbation function to generate probabilistic meteorological forcings. <br>In addition to these R packages, the airGR constellation includes two web applications available on sunshine.irstea.fr. First, the airGRteaching GUI (fig. 2) is a demo of the tool embedded in the R package. Second, the airGRmaps GUI (fig. 3) provides regionalized parameters for GR daily hydrological models from geographical coordinates or by browsing on the map, over France.</p><p><img src="data:image/png;base64, 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
Bibliografischer Nachweis
Publikationsdaten
- Autor:innen
- Olivier Delaigue, David Dorchies, Guillaume Thirel
- Quelle
- Copernicus GmbH
- Publikation
- 2022-01-01
- Band / Ausgabe
- Nicht angegeben
- Seiten
- Nicht angegeben
- ISSN / ISBN
- Nicht angegeben
- Zitationen
- 0 laut Crossref
- Referenzen
- 0 hinterlegt
Zitieren
Zitierfähiger Nachweis
Olivier Delaigue, David Dorchies, Guillaume Thirel (2022). The airGR galaxy: hydrological tools around GR models. https://doi.org/10.47191/ijmra/v9-i8-09