The aim of this paper is to assess the correlation of groundwater level changes (or groundwater level anomalies (GWLA)) obtained from direct measurements in wells with groundwater storage anomalies (GWSA) calculated using Gravity Recovery and Climate Experiment (GRACE) products and Global Land Data Assimilation Systems (GLDAS) models across different climate zones, from temperate Poland to Arctic Sweden. We recognize that such validation studies are needed to increase the understanding of the spatio-temporal limits of remote sensing model applicability, not least in data-scarce sub-Arctic and Arctic environments where processes are complex due to the impacts of snow and (perma) frost. Results for temperate climates in Poland and southern Sweden show that, whereas one of the models (JPL_NOAH_GWSA) failed due to water balance term overestimation, the other model (CSR_CLM_GWSA) produced excellent results of monthly groundwater dynamics when compared with the observations in 387 groundwater wells in the region during 2003–2022 (cross-correlation coefficient of 0.8). However, for the sub-Arctic and Arctic northern Sweden, the model suitable for other regions failed to reproduce typical northern groundwater regimes (of the region’s 85 wells), where winter levels decrease due to the blocking effect of ground frost on groundwater recharge. This suggests, more generally, that conventional methods for deriving GWSA and its seasonality ceases to be reliable in the presence of considerably infiltration-blocking ground frost and permafrost (whereas snow storage modules perform well), which hence need further attention in future research. Regarding long-term groundwater level trends, remote sensing results for southern Sweden show increasing levels, in contrast with observed unchanged to decreasing (~10 mm/a) levels, which may not necessarily be due to errors in the remote sensing model but may rather emphasize impacts of anthropogenic pressures, which are higher near the observation wells that are often located in eskers used for water supply. For sub-Arctic and Arctic Sweden, the (relatively uncertain) trend of the remote sensing results nevertheless agrees reasonably well with the groundwater well observations that show increasing groundwater levels of up to ~14 mm/a, which, e.g., is consistent with reported trends of large Siberian river basins.

While geogenic arsenic (As) contamination of aquifers have been intensively investigated across the world, the mobilization and transport of As from anthropogenic sources have received less scientific attention, despite emerging evidence of poor performance of widely used risk assessment models. In this study we hypothesize that such poor model performance is largely due to insufficient attention to heterogeneous subsurface properties, including the hydraulic conductivity K and the solid-liquid partition (K_d), as well as neglect of laboratory-to-field scaling effects. Our multi-method investigation includes i) inverse transport modelling, ii) in-situ measurements of As concentrations in paired samples of soil and groundwater, and iii) batch equilibrium experiments combined with (iv) geochemical modelling. As case study we use a unique 20-year series of spatially distributed monitoring data, capturing an expanding As plume in a Chromated Copper Arsenate (CCA)-contaminated anoxic aquifer in southern Sweden. The in-situ results showed a high variability in local K_d values of As (1 to 107 L kg⁻¹), implying that over-reliance of data from only one or few locations can lead to interpretations that are inconsistent with field-scale As transport. However, the geometric mean of the local K_d values (14.4 L kg⁻¹) showed high consistency with the independently estimated field-scale “effective K_d” derived from inverse transport modelling (13.6 L kg⁻¹). This provides empirical evidence for the relevance of using geometric averaging when estimating large-scale “effective K_d” values from local measurements within highly heterogenous, isotropic aquifers. Overall, the considered As plume is prolonged by about 0.7 m year⁻¹, now starting to extend beyond the borders of the industrial source area, a problem likely shared with many of the world's As-polluted sites. In this context, geochemical modelling assessments, as presented here, provided a unique understanding of the processes governing As retention, including local variability in, e.g., Fe/Al-(hydr)oxides contents, redox potential and pH.

The objectives of this study are to characterize the input signal of a shallow carbonate aquifer in northeastern France and to clarify the recharge and groundwater mineralization processes, by analysing the chemical and isotopic (δ¹⁸O, δ²H) composition of rain and groundwater. The groundwater isotopic signature was very close to the calculated local meteoric water line and showed a narrow range, which is explained by the buffer effect of the matrix-dominated chalk aquifer. Nevertheless, intensive fracture networks can exist at local scale and lead to rapid aquifer response to rainfall, as attested by observed large variations in groundwater isotopic and chemical signatures at one specific site. Main factors controlling the groundwater mineralization are highlighted, including the input signal, water-rock interactions and human activities. Moreover, groundwater isotopic signatures are related to groundwater ages and historical climate conditions, showing that groundwater isotopic signal could also be used as a record of climate changes.