| Summary: | International audience Groundwater level (GWL) fluctuations can be expressed over a wide range of timescales. In particular, as aquifers act as low-pass filters, low-frequency variability (from interannual to decadal timescales) originating from large-scale climate variability usually represents a significant part of GWL variance. This is typically the case of aquifers in the Seine River basin for which extreme GWL then appear largely dependent on such low-frequency fluctuations. In addition to expected trend behaviours (e.g., progressive increase in air temperature or evapotranspiration, increase or decrease of monthly or seasonal precipitation amounts, etc.), global climate change can also affect, and have maybe already affected, the internal variability as described by climate modes like for instance the El Nino Southern Oscillation (ENSO) or the North-Atlantic Oscillation (NAO), which explain more or less directly the low-frequency variability of hydrological processes including GWL. How GWL in a large hydrosystem may respond to such changes then remains an open question, and even appears as an important issue regarding extreme GWL. Would that lead to more or to less severe extremes, with more groundwater droughts or, on the contrary, more groundwater floodings? Would this be expressed in the same way for aquifers exhibiting different GWL behaviours in terms of low-frequency variance? To tackle this issue, we implemented an empirical numerical approach that would allow to assess the sensitivity of aquifers to changes in large-scale climate variability, using the whole Seine hydrosystem as a test case. The approach consisted in i) identifying and modifying the spectral content, originating from large-scale climate variability, of the precipitation field using signal processing techniques, ii) re-injecting this modified field as input to a physically-based hydrological/hydrogeological modeling tool (the CaWaQS software) for the Seine basin. We used the Safran precipitation field over the period 1970-2018, ...
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