Background and aim

Sustainable groundwater use by humans and ecosystems relies on adequate rates of groundwater recharge, which are expected to change as the global climate is changing. However, the impacts of climate change on groundwater recharge remain uncertain.

Here you will use climate and long-term recharge measurements at many different locations around the world to identify where groundwater recharge is most sensitive to climate change. Then you will test how well hydrological models capture the climate sensitivity of recharge, derived from the measurements. The aim is to better understand how climate change affects groundwater recharge.

Data and methods

The analysis mainly relies on groundwater recharge data compiled by Moeck et al. (2020), but using other datasets is also possible. Model output data from multiple global hydrological models are available from The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP; https://www.isimip.org/). ISIMIP uses standardized protocols (e.g. the same climate data) that enable structured model comparison experiments. Climate data can also be downloaded from the ISIMIP repository or from various other sources.

The basic idea of sensitivity is: how much does a response variable change when we change a forcing variable? For example, the precipitation sensitivity of groundwater recharge quantifies how much recharge would change for a unit change (1%) in precipitation. Depending on the hydrological system, this may be more or less than 1 %, which gives an indication of the impact of climate change on groundwater recharge.

In this project, you will first derive recharge sensitivities from data. Using the same methods, you will then analyze recharge sensitivities of different models and explore how robust modelled projections of groundwater recharge are.

Challenges

The project mostly involves data analysis and therefore you should have good coding skills (e.g. using Python, R, or Matlab). You should also be comfortable with the management of large datasets. Additionally, you should have some background knowledge about groundwater recharge processes or the willingness to obtain that knowledge during the project. This is important for conceptualizing the results of the analysis.

Supervision

Sebastian Gnann (University of Freiburg) and Wouter Berghuijs (VU Amsterdam)

Contact

Sebastian Gnann

sebastian.gnann@hydrologie.uni-freiburg.de

Tel. +49 (0)761 / 203-9283

Language

English (or German)

References

Berghuijs, W. R., Luijendijk, E., Moeck, C., van der Velde, Y., & Allen, S. T. (2022). Global recharge data set indicates strengthened groundwater connection to surface fluxes. Geophysical Research Letters, 49(23), e2022GL099010.

Cuthbert, M. O., Taylor, R. G., Favreau, G., Todd, M. C., Shamsudduha, M., Villholth, K. G., … & Kukuric, N. (2019). Observed controls on resilience of groundwater to climate variability in sub-Saharan Africa. Nature, 572(7768), 230-234.

MacDonald, A. M., Lark, R. M., Taylor, R. G., Abiye, T., Fallas, H. C., Favreau, G., … & West, C. (2021). Mapping groundwater recharge in Africa from ground observations and implications for water security. Environmental Research Letters, 16(3), 034012.

Moeck, C., Grech-Cumbo, N., Podgorski, J., Bretzler, A., Gurdak, J. J., Berg, M., & Schirmer, M. (2020). A global-scale dataset of direct natural groundwater recharge rates: A review of variables, processes and relationships. Science of the total environment, 717, 137042.

Reinecke, R., Müller Schmied, H., Trautmann, T., Andersen, L. S., Burek, P., Flörke, M., … & Döll, P. (2021). Uncertainty of simulated groundwater recharge at different global warming levels: a global-scale multi-model ensemble study. Hydrology and Earth System Sciences, 25(2), 787-810.