This study investigates whether geostatistical properties of aquitards can be determined from data collected at a drinking water well field. A workflow adaptable to any drinking water extraction site with pumping and groundwater head data is developed. Using data from Budel, the Netherlands, a layered groundwater flow model is constructed and calibrated on hydraulic heads. A large number of realizations are generated for the aquitard, considering various heterogeneity parameters. These simulations are upscaled to the grid of the flow model, and their fit to observed heads is evaluated. Results show that optimal geostatistical parameters can be identified, even though many combinations reproduce observed heads. These parameters can be used to parameterize regional groundwater flow models. Particle tracking simulations show heterogeneity decreases contaminant breakthrough times while also decreasing the total flow through the aquitard. These findings emphasize the need to consider aquitard heterogeneity in risk assessments at drinking water production sites.

This study investigates the spatial and temporal sensitivity of aquitard hydraulic conductivity and specific storage on drawdowns in pumping tests. The objective is to understand which area of the aquitard is represented by drawdowns in different observation wells. A three-layered MODFLOW 6 model was used to simulate pumping tests on a circular Voronoi grid for three transmissivity scenarios and both confined and semiconfined top boundary conditions. A local sensitivity analysis was performed using PEST++ to determine how perturbations in hydraulic conductivity and specific storage of the aquitard affect head changes at observation wells in the pumped and overlying aquifer. Results indicate that for observation wells in the pumped aquifer, sensitivity forms an elliptical shape that is symmetrical around the observation well and the pumping well for all scenarios. The sensitivity map for the observation well in the overlying aquifer depends on the transmissivity ratio between both aquifers. It favors the area surrounding the pumping well if the transmissivity of the pumped aquifer is lower than that of the overlying aquifer. Conversely, with higher transmissivity in the pumped aquifer, sensitivity primarily lies around the observation well. Sensitivity patterns evolve over time, expanding the area of influence and shifting the sensitivity toward the observation well for a semiconfined top boundary. These findings are relevant for understanding the information regarding aquitard heterogeneity that is present in pumping test drawdowns and optimizing pumping test design.

Aquitards are common hydrogeological features and their hydraulic conductivity is an important property for various groundwater management issues. Predicting their hydraulic conductivity proves challenging, given its dependence on numerous variables. In this study, the dominant factors for predicting aquitard hydraulic conductivity are identified. To this end, a random forest model is trained on a dataset consisting of more than 1000 hydraulic conductivity measurements of core-scale sediment samples from a wide range of stratigraphic units and depths in the Netherlands. The dataset contains textural properties, such as the grain size distribution and porosity, as well as structural data, such as location, sampling depth, stratigraphical unit, lithofacies, organic carbon content, carbonate content and groundwater chloride concentration. Results show that clay fraction, stratigraphic unit, depth, lithofacies and x-coordinate are the most important features for predicting the hydraulic conductivity. Here, x-coordinate is presumably a proxy for distance from marine influence. Using a more detailed grain size distribution or using derived parameters such as the grain size percentiles does not improve the model any further. Our findings indicate that structural properties play a significant role in predicting aquitard conductivity, as they serve as indicators of processes such as compaction and soft-sediment deformation. The model is furthermore an effective method to estimate hydraulic conductivity for sediment samples without conducting costly and time-consuming hydraulic conductivity measurements.

Aquitards are common hydrogeological features in the subsurface. Typically, pumping tests are used to parameterize the hydraulic conductivity of heterogeneous aquitards. However, they do not take spatial variability and uncertainty into account. Alternatively, core-scale measurements of hydraulic conductivity are used in geostatistical upscaling methods, for which their correlation lengths are needed, but this information is extremely difficult to obtain. This study investigates whether a pumping test can be used to obtain the correlation lengths needed for geostatistical upscaling and account for the uncertainty about heterogeneous aquitard conductivity. Random realizations are generated from core-scale data with varying correlation lengths and inserted into a groundwater flow model which simulates the outcome of an actual pumping test. The realizations yielded a better fit to the pumping test data than the traditional pumping test result, assuming homogeneous layers are selected. Ranges of horizontal and vertical correlation lengths that fit the pumping-test well are found. However, considerable uncertainty regarding the correlation lengths remains, which should be considered when parameterizing a regional groundwater flow model.