Climate Change & Water Resources: Analysis of Groundwater Recharge Around Lyon, France

Context

For those responsible for defining adaptation strategies, it is crucial to have clear information about climate change impacts, consider uncertainties, and understand the magnitude of potential effects. The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for consistently projecting the impacts of climate change across different sectors and spatial scales. Through the collaboration of an international network of climate-impact modelers, ISIMIP offers a detailed and consistent picture of the world under different climate change scenarios.

General Objectives

This study aims to test the applicability and replicability of the workflow developed by Müller & Döll (2024) to assess the impact of climate change on a specific variable available in the ISIMIP repository: groundwater recharge. Our focus is on an area of interest (AOI) around Lyon, France.

Figure 1: Screenshot of the ISIMIP Platform

Data Utilized

The study utilized an extensive dataset comprising 212 NetCDF files, amounting to 60 GB of data. This dataset includes:

• Historical Data: 54 NetCDF files (22 GB) covering the period from 1850 to 2014.
• Future Projections: 158 NetCDF files (38 GB) covering the period from 2015 to 2100.
• Global Climate Models (GCMs): Six models were considered — ipsl-cm6a-lr, mri-esm2–0, mpi-esm1–2-hr, ukesm1–0-ll, and gfdl-esm4.
• Global Hydrological Models (GHMs): Four models were included — cwatm, watergap2–2e, h08, and miroc-integ-land.
• Shared Socioeconomic Pathways (SSPs): Three scenarios were considered — SSP 1, SSP 3, and SSP 5.
• ISIMIP 3b Protocol: The most recent and representative protocol was used for this study.

Method

The method of analysis is based on the work described by Müller & Döll (2024):

• Determine a reference distribution of the annual mean groundwater recharge for each model combination over a historical period from 1985 to 2015.
• Define horizons of interest and 30-year distributions (aroun 2050, 2070 and 2084) and calculate the annual mean groundwater recharge for each model combination, then calculate the relative change compared to its reference mean for different SSPs.
• Analyze the interannual variability to determine the relative changes for dry, normal, and wet years. The groundwater recharge values are sorted by magnitude, and relative differences have been calculated between values of the same rank in the future period and the reference period. This sorting corresponds to the exceedance probability, which is indicated as a percentage.

Figure 2: Combination of multiple GCMs, GHMs and SSPs to understand the relative changes caused by Climate Changes

In the following, the results are described by means of percentile boxes (Figure 3) to describe the distribution of results given by the multi-models ensemble.

Figure 3: illustration of a percentile box.

Results

The analysis based on Figure 4, revealed significant insights into the future of groundwater recharge around Lyon:

• Short-Term Projections (by 2050): Approximately 90% of the models indicate a decrease in groundwater recharge. This trend is observed in both optimistic and pessimistic scenarios.
• Long-Term Projections (by 2084): In the pessimistic scenario (SSP 5), 80% of the models project a decrease in mean groundwater recharge by 10% to 40%.

Figure 4: Percentile boxes showing (a) the average annual recharge over a reference period and (b) the potential percentage changes of the mean groundwater recharge of the multi-model ensemble in the periods around 2050, 2084 and 2084 relative to the reference period.

Additionnaly, the future interannual fluctuations have been analysed for the horizon 2084 and considering the pessimistic scenario (SSP 5)(Figure 5):

• Wet Years (exceedence between 0 to 20%): 80% of the models indicate a decrease in recharge by 10% to 30%.
• Normal Years (exceedence between 40 to 60%): 80% of the models indicate a decrease in recharge by 10% to 40%.
• Dry Years (exceedence between 80 to 100%): 80% of the models indicate a decrease in recharge by 0% to 55%.

Figure 5: changes in the interannual variability of groundwater recharge. Percentage change in annual groundwater recharge. The 30 yearly groundwater recharge values are sorted according to their magnitude, and the relative changes were calculated between the values of the same rank in the future and reference periods. This sorting corresponds to the exceedance probability.

Conclusion

The study successfully developed a reproducible and scalable workflow using ISIMIP repository data and the Müller & Döll (2024) methodology to determine the impact of climate change on a complex environmental variable — groundwater recharge — around a location of interest. This workflow is not limited to Lyon or groundwater recharge; it can be applied to any location worldwide and to various other hydrologic or environmental variables, such as agriculture, biodiversity, and marine ecosystems.

The power of this workflow lies in its comprehensive approach, utilizing all available models of the ISIMIP platform, scenarios, and combinations of GCMs, GHMs, and SSPs. By leveraging this extensive dataset, we provide a holistic view of the potential consequences of climate change on variables of interest. This approach offers valuable insights for policymakers and stakeholders, allowing them to make informed decisions and develop robust adaptation strategies that consider a wide range of potential outcomes — from optimistic to pessimistic scenarios.

Acknowledgements

Thanks to Laura Müller, Hannes Müller Schmied and Petra Döll for scientific advices.

Complementary notes — contact

This article and the code has been elaborated with the support of Ageoce. Ageoce builds digital solutions and services focusing on geodata and geosciences.

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