Disentangling aquifer dynamics in coastal groundwater systems using high-resolution time series

Freshwater lenses are an important water resource in coastal areas as well as on oceanic islands, and understanding the dynamic forces acting upon this resource is vital for their sustainable management. A key water-management objective is to understand and manage these freshwater lenses, which requires accurate estimates of drawdown and groundwater recharge. Groundwater levels in such systems, however, are dominated by multiple dynamic factors, such as tidally and meteorologically forced ocean level fluctuations, coastal morphology, aquifer properties, recharge, and groundwater extraction. Unfortunately, tidal influences often dominate groundwater levels in these systems, which confounds the quantification of aquifer recharge and extraction.

This work uses regression deconvolution to quantify oceanic influences on groundwater levels by generating an “Ocean Response Function” (ORF) that is used to reveal groundwater recharge and extraction, once influences have been removed. We use groundwater levels from an unconfined and unconsolidated (mostly fine sand) aquifer on the island of Norderney located in the North Sea in Northwest Germany. Confounding tidal influences are removed from observed groundwater levels to reveal underlying processes. Most prominently, seasonal recharge patterns are now clearly visible, along with responses to daily groundwater extraction from a nearby water-supply well. The obtained ORF also constrains the aquifer hydraulic diffusivity, in that higher diffusivities induce faster responses. Overall, this work demonstrates how regression deconvolution leads to improved insight into groundwater processes and properties when applied to coastal and island groundwater observations.