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.

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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.

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Groundwater level time series are of great value for a variety of groundwater studies, particularly for those dealing with the impacts of anthropogenic and climate change. Quality control of groundwater level observations is an essential step prior to any further application, e.g., trend analysis. Often the quality control of data is limited to the removal of outliers or elimination of entire time series from a dataset, while such approaches drastically reduce the spatial coverage of initially huge datasets. Frequently studies tend to present already qualitycontrolleddata, but neglect to demonstrate how the data were selected, judged, and modified. We present a data rescue approach developed for correcting the Latvian national groundwater level database, containing 1.68 million groundwater level observations since 1959, including 0.69 million manual measurements. A web-based R-Shiny interface was developed and used for visual identification and manual correction of erroneous measurements in groundwater level time series. All data manipulations were performed programmatically. Reproducibilityand traceability were ensured by deploying separate data tables for raw observations, data repair actions and the final dataset. As a result of applied actions, 34.3% of all automatic measurements were either deleted or corrected, while only 6.5% of manual measurements were edited. Commonly found errors ingroundwater level time series were grouped into: errors in measurement and data recording; technical problems at the observation site; local anthropogenic impact and other unclassified problems. The improvement from the rescue approach was assessed by comparing the Akaike information criterion derived from fitted ARMA and ARIMA models to both original and repaired time series. The results showed that models fitted using repaired time series were better than those fitted on the original time series for the same time series sections. The presented rescue approach and results can be of great value for all studies using groundwater level time series as an input.@en

Groundwater recharge quantification is essential for sustainable groundwater resources management, but typically limited to local and regional scale estimates. A high-resolution (1 km × 1 km) dataset consisting of long-term average actual evapotranspiration, effective precipitation, a groundwater recharge coefficient, and the resulting groundwater recharge map has been created for all of Europe using a variety of pan-European and seven national gridded datasets. As an initial step, the approach developed for continental scale mapping consists of a merged estimate of actual evapotranspiration originating from satellite data and the vegetation controlled Budyko approach to subsequently estimate effective precipitation. Secondly, a machine learning model based on the Random Forest regressor was developed for mapping groundwater recharge coefficients, using a range of covariates related to geology, soil, topography and climate. A common feature of the approach is the validation and training against effective precipitation, recharge coefficients and groundwater recharge from seven national gridded datasets covering the UK, Ireland, Finland, Denmark, the Netherlands, France and Spain, representing a wide range of climatic and hydrogeological conditions across Europe. The groundwater recharge map provides harmonised high-resolution estimates across Europe and locally relevant estimates for areas where this information is otherwise not available, while being consistent with the existing national gridded datasets. The Pan-European groundwater recharge pattern compares well with results from the global hydrological model PCR-GLOBWB 2. At country scale, the results were compared to a German recharge map showing great similarity. The full dataset of long-term average actual evapotranspiration, effective precipitation, recharge coefficients and groundwater recharge is available through the EuroGeoSurveys' open access European Geological Data Infrastructure (EGDI).

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Since the nineteen fifties, groundwater levels in the Netherlands dropped more than as simulated by hydrological models. In the rural sandy part of the Netherlands, the difference amounts to approximately 0.3 m on average. The answer to the question of what or who caused this 'background decline' of groundwater tables may have juridical and financial consequences, especially since Dutch farmers are entitled to financial compensation for crop damage caused by groundwater abstractions. In our forensic study, we investigated how anthropogenic changes in groundwater recharge from 1950 to 2010 affected groundwater levels. In this period, crop yields in agriculture have risen sharply, and, because crop water use is proportionate to crop production, this led to more crop evapotranspiration and subsequently less groundwater recharge. Urban expansion and forestation has also led to a decrease in groundwater recharge. We showed that these changes in recharge may have caused a decline of groundwater of 0.2-0.3 m over 60 years (1950-2010). The simulated drawdown caused by groundwater abstractions appeared to depend on the amount of groundwater recharge related to land use and crop yield. This means that to properly evaluate the effects of a particular groundwater abstraction, one should account for the hydrological history of the landscape since the start of that abstraction.@en

The Geological Survey of the Netherlands (TNO-GSN) provides public information on the subsurface (http://www.dinoloket.nl). Among this information are (hydro)geological models with hydraulic parametrization. GeoTOP is a voxel model of the upper 50 meters with voxels of 100m x 100m x 0.5m. The basis of the hydraulic parametrisation is a large collection of laboratory measurements of the hydraulic conductivity determined for samples from undisturbed cores, which TNO-GSN collects systematically throughout the Netherlands. The values are upscaled from laboratory to voxel scale for each combination of geological unit and lithoclass. The hydraulic parametrization of GeoTOP for the province of Zeeland (TNO-GSN, 2016) resulted in very high resistances of the confining layer covering the main regional aquifer. The high resistance was predicted for a large area, which made it feasible to validate it. The magnitiude of the resistance is important for the salinization risk for the shallow groundwater and the increase of this risk due to sea level rise. @en

TNO Geological Survey of the Netherlands makes groundwater information available on https://www.grondwatertools.nl/grondwatertools-viewer in addition to the measured heads at https://www.dinoloket.nl/ondergrondgegevens: (1) piezometric contours and (2) time series models with precipitation and evaporation as explanatory variables. Head time series implicitly contain information about the groundwater system. This information is reflected in response of the head to precipitation. The database with ±34000 acceptable time series models throughout the Netherlands may serve many purposes. Examples are: –– Spatial patterns (1) of heads as indication of groundwater flow directions and (2) of precipitation response quantity and response time which gives information of the aquifer system, e.g. the presence of a confining layer or aquitard; –– Improvement of bad time series models using spatial correlation of the precipitation response between neighboring monitoring wells; –– Detection of changes over time (in groundwater heads only or also the groundwater system); this can be done by e.g. (1) evaluating trends in the residuals (difference between measurements and model predictions – indicative for influences not in the time series model), (2) comparing models of different periods, (3) estimating a trend as explanatory variable in the time series model; –– Determination of status: the percentile of the actual groundwater head with respect to a standardized period and frequency. The time series models allow to fill gaps or extend measurement series so calculated percentiles are comparable. The time series models and piezometric contouring of http://www.grondwatertools.nl offer valuable 4D information for management and research on groundwater heads in the Netherlands. @en

The Geological Survey of the Netherlands (TNO-GSN) maintains a public national database of groundwater head observations. Transfer function-noise modeling has been applied to the time series in order to extract the impulse response functions for precipitation and evaporation for each piezometer. An automated procedure has been developed to assess the quality of the time series and of the models. The time series models of sufficient quality offer far more homogeneous data on the piezometric head than the original measurements. This allows for improved mapping of the head at a specific date or of characteristics of the head like average summer or winter levels. Also, the separation of precipitation and evaporation from other influences is useful for groundwater management and policy. The individual time series models are available online with interactive graphics (https://www.grondwatertools.nl/grondwatertools-viewer). The spatial patterns of the impulse response function characteristics can support analyses of the groundwater system.
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A sustainable drinking-water supply requires durable securing of the resource. With an increase in spatial pressure, the need is increasing to prioritize measures based on the vulnerability of the resources and the impact of surrounding land use functions. This is especially challenging in the Province of Overijssel with groundwater abstraction sites in vulnerable Pleistocene sandy soils and increasing spatial pressure from both agricultural and urban areas. The governance of the groundwater abstractions in the Province of Overijssel is based on a combination of precaution and a risk-based approach. The Province has adopted REFLECT to assess the risks of spatial developments. REFLECT is a negotiation support system that gives an overview of the vulnerability of the groundwater abstractions and risks of several land use functions on the groundwater quality. REFLECT has been used to obtain the current risk scores of all drinking water abstractions in the Province and following the EU Water Framework Directive. Spatial insight of risks was used to identify and target measures reducing these risks. Moreover, REFLECT has been applied to decide on a local spatial development near an abstraction. Knowledge of the impact of land use changes on groundwater quality helped the municipality harmonizing the spatial plan with the interest of the drinking water abstraction and creating a step-forward in the protection level of the abstraction site. These applications illustrate that REFLECT is an instrument that fits well within risk-based groundwater governance which aims at safeguarding of the public water supply by harmonizing land use functions.@en

The Geological Survey of the Netherlands makes available 3D models of the subsurface at various resolutions. GeoTOP is a high resolution voxel model of the upper tens of meters of the subsurface. It consists of voxels of 100m x 100m x 0.5m for which the stratigraphy, lithology, and hydrogeological parameters are identified with their uncertainties. The first step in the creation of GeoTOP is a geological schematization of the borehole descriptions into lithostratigraphical units. During the second step, maps are created of the top and base of each unit based on the elevation in the boreholes. The third step is a 3D stochastic interpolation of lithofacies and lithology within each unit, resulting in probabilities for each voxel. In the fourth step, voxels get hydraulic conductivities from stochastic upscaling of values from laboratory tests on undisturbed samples from high quality cores from boreholes. Hydraulic parametrization of GeoTOP has been carried out for the Province of Zeeland in the Netherlands. The resulting hydraulic resistance of the Holocene confining layer compared reasonably well to existing information. However, no data was available for an area with very high resistances according to GeoTOP. Therefor, a pumping test has been designed to obtain data for the validation of these high resistances. The integration of the geology in GeoTOP gives better a priori hydraulic parametrization of (complex) confining layers for groundwater modeling. Still unresolved is how the 3D voxel model can be improved with the a posteriori values of groundwater model calibration. Corresponding email: willem_jan.zaadnoordijk@tno.nl@en

The efficiency of heat recovery in high-temperature (>60 °C) aquifer thermal energy storage (HT-ATES) systems is limited due to the buoyancy of the injected hot water. This study investigates the potential to improve the efficiency through compensation of the density difference by increased salinity of the injected hot water for a single injection-recovery well scheme. The proposed method was tested through numerical modeling with SEAWATv4, considering seasonal HT-ATES with four consecutive injection-storage-recovery cycles. Recovery efficiencies for the consecutive cycles were investigated for six cases with three simulated scenarios: (a) regular HT-ATES, (b) HT-ATES with density difference compensation using saline water, and (c) theoretical regular HT-ATES without free thermal convection. For the reference case, in which 80 °C water was injected into a high-permeability aquifer, regular HT-ATES had an efficiency of 0.40 after four consecutive recovery cycles. The density difference compensation method resulted in an efficiency of 0.69, approximating the theoretical case (0.76). Sensitivity analysis showed that the net efficiency increase by using the density difference compensation method instead of regular HT-ATES is greater for higher aquifer hydraulic conductivity, larger temperature difference between injection water and ambient groundwater, smaller injection volume, and larger aquifer thickness. This means that density difference compensation allows the application of HT-ATES in thicker, more permeable aquifers and with larger temperatures than would be considered for regular HT-ATES systems.

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