IAHS2022-103, updated on 22 Sep 2022
IAHS-AISH Scientific Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

The airGR galaxy: hydrological tools around GR models

Olivier Delaigue1, David Dorchies2, and Guillaume Thirel1
Olivier Delaigue et al.
  • 1Université Paris-Saclay, INRAE, HYCAR, ANTONY, France (olivier.delaigue@inrae.fr)
  • 2G-EAU, Univ Montpellier, AgroParisTech, BRGM, CIRAD, IRD, INRAE, Institut Agro, Montpellier, France

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.

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.

Recently, a galaxy of tools (fig. 1) has formed around airGR (hydroGR.github.io/airGR).
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.
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.
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.
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.

Figure 1: airGR galaxy tools.

Figure 2: airGRteaching GUI.

Figure 3: airGRmaps GUI.


How to cite: Delaigue, O., Dorchies, D., and Thirel, G.: The airGR galaxy: hydrological tools around GR models, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-103, https://doi.org/10.5194/iahs2022-103, 2022.