Abstract. This research examines the nonstationary dynamics of extreme surges along the English Channel coasts and seeks to make their connection to the climate patterns at different timescales by the use of a detailed spectral analysis in order to gain insights into the physical mechanisms relating the global atmospheric circulation to the local-scale variability of the monthly extreme surges. This variability highlights different oscillatory components from the interannual (∼1.5, ∼2–4, ∼5–8 years) to the interdecadal (∼12–16 years) scales with mean explained variances of ∼25 %–32 % and ∼2 %–4 % of the total variability, respectively. Using the two hypotheses that the physical mechanisms of the atmospheric circulation change according to the timescales and their connection with the local variability improves the prediction of the extremes, we have demonstrated statistically significant relationships of ∼1.5, ∼2–4, ∼5–8 and 12–16 years with the different climate oscillations of sea level pressure, zonal wind, North Atlantic Oscillation and Atlantic Multidecadal Oscillation, respectively. Such physical links have been used to implement the parameters of the time-dependent generalized extreme value (GEV) distribution models. The introduced climate information in the GEV parameters has considerably improved the prediction of the different timescales of surges with an explained variance higher than 60 %. This improvement exhibits their non-linear relationship with the large-scale atmospheric circulation.
Abstract. Groundwater levels (GWLs) very often fluctuate over a wide range of timescales (intra-annual, annual, multi-annual, and decadal). In many instances, aquifers act as low-pass filters, dampening the high-frequency variability and amplifying low-frequency variations (from multi-annual to decadal timescales) which basically originate from large-scale climate variability. Within the aim of better understanding and ultimately anticipating groundwater droughts and floods, it appears crucial to evaluate whether (and how much) the very high or very low GWLs are resulting from such low-frequency variability (LFV), which was the main objective of the study presented here. As an example, we focused on exceedance and non-exceedance of the 80 % and 20 % GWL percentiles respectively, in the Paris Basin aquifers over the 1976–2019 period. GWL time series were extracted from a database consisting of relatively undisturbed GWL time series regarding anthropogenic influence (water abstraction by either continuous or periodic pumping) over metropolitan France. Based on this dataset, our approach consisted in exploring the effect of GWL low-frequency components on threshold exceedance and non-exceedance by successively filtering out low-frequency components of GWL signals using maximum overlap discrete wavelet transform (MODWT). Multi-annual (∼7-year) and decadal (∼17-year) variabilities were found to be the predominant LFVs in GWL signals, in accordance with previous studies in the northern France area. By filtering out these components (either independently or jointly), it is possible to (i) examine the proportion of high-level (HL) and low-level (LL) occurrences generated by these variabilities and (ii) estimate the contribution of each of these variabilities in explaining the occurrence of major historical events associated with well-recognized societal impacts. A typology of GWL variations in Paris Basin aquifers was first determined by quantifying the variance distribution across timescales. Four GWL variation types could be found according to the predominance of annual, multi-annual, or/and decadal variabilities in these signals: decadal-dominant (type iD), multi-annual- and decadal-dominant (type iMD), annual-dominant (type cA), and annual- and multi-annual-dominant (type cAM). We observed a clear dependence of high and low GWL on LFV for aquifers exhibiting these four GWL variation types. In addition, the respective contribution of multi-annual and decadal variabilities in the threshold exceedance varied according to the event. In numerous aquifers, it also appeared that the sensitivity to LFV was higher for LLs than HLs. A similar analysis was conducted on the only available long-term GWL time series which covered a hundred years. This allowed us to highlight the potential influence of multidecadal variability on HLs and LLs too. This study underlined the key role of LFV in the occurrence of HLs and LLs. Since LFV originates from large-scale stochastic climate variability as demonstrated in many previous studies in the Paris Basin or nearby regions, our results point out that (i) poor representation of LFV in general circulation model (GCM) outputs used afterwards for developing hydrological projections can result in strong uncertainty in the assessment of future groundwater extremes (GWEs), and (ii) potential changes in the amplitude of LFV, be they natural or induced by global climate change, may lead to substantial changes in the occurrence and severity of GWEs for the next decades. Finally, this study also stresses the fact that due to the stochastic nature of LFV, no deterministic prediction of future GWEs for the mid- or long-term horizons can be achieved, even though LFV may look periodic.
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