The largest part of Earth's unbound fresh water is groundwater, thus being of great importance for human kind. Climate change is anticipated to have severe impacts on the amount and dynamics of groundwater recharge and consequently on water resources stored in aquifers (Butler et al., 2021;Russo & Lall, 2017;Whittemore et al., 2015). In particular, the spatial and temporal variations of the storage are still unclear. Furthermore, abstraction rates may increase to meet future human water demands, placing additional stress on groundwater

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<p>Groundwater resources are heavily exploited to supply domestic, industrial and agricultural water consumption. Climate and societal changes and associated higher abstraction will alter the subsurface storage in terms of quantity and quality in currently unpredictable ways. In order to ensure sustainable groundwater management, we must evaluate the intrinsic and spatially variable vulnerability of aquifers in terms of water quality issues and the resilience of groundwater volumes to external perturbations such as severe droughts in connection with intensive irrigation. For this purpose, physically based numerical groundwater models are of great importance, especially on the regional scale. The equations applied in these models must be fed with the hydrogeological parameters: The <strong>transmissivity <em>T</em></strong> and the <strong>storativity <em>S</em>.</strong></p> <p>Both parameters are typically obtained through time consuming and cost intensive hydrogeological in-situ tests or by laboratory analysis of core samples from point information (drillings and wells), resulting in parameters with limited transferability to regional settings. Instead, we propose to determine the parameters by spectral analysis of groundwater level fluctuations using (semi-)analytical solutions for the frequency domain. We developed a fully automatized workflow, taking groundwater level and recharge time series together with little information about the geometry of the aquifer to derive <strong><em>T</em></strong> and <strong><em>S</em></strong><em> </em>as well as<strong><em> t<sub>c</sub></em></strong> (<strong>the characteristic response time</strong>). While the first two will be used for hydrogeological modelling, the latter can serve as an indication to assess the resilience of the groundwater system directly without additional modelling attempts. The methodology was tested with great success in simplified numerical environments and was applied to real groundwater time series in southern Germany. The response times and the storativities could be robustly estimated while the transmissivities inherit quantifiable uncertainties. Depending on the hydrogeological regime, the parameters represented effective and regional estimates.</p>