In the era of global climate change, the monitoring of water resources, including groundwater, is of fundamental importance for nature, agriculture, economy and society. The purpose of this paper is to check compliance of changes in groundwater level obtained from direct measurements in wells with groundwater storage (GWS) anomalies calculated using gravity recovery and climate experiment (GRACE) observations in Poland. Data from the global land data assimilation (GLDAS), in the form of soil moisture (SM) and snow water equivalence (SWE), were used to convert GRACE observations into a series of GWS changes. It was found that very high consistency occurs between GRACE observations and changes in water level in wells, while the GWS series obtained from GRACE and GLDAS do not provide adequate compatibility. Further research presented in the paper was devoted to attempts to explain this phenomenon. In addition, time series of GRACE, GLDAS and groundwater head series were analyzed.

The Gravity Recovery and Climate Experiment (GRACE) observations have provided global observations of total water storage (TWS) changes at monthly intervals for over 15 years, which can be useful for estimating changes in GWS after extracting other water storage components. In this study, we analyzed the TWS and groundwater storage (GWS) variations of the main Polish basins, the Vistula and the Odra, using GRACE observations, in-situ data, GLDAS (Global Land Data Assimilation System) hydrological models, and CMIP5 (the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 5) climate data. The research was conducted for the period between September 2006 and October 2015. The TWS data were taken directly from GRACE measurements and also computed from four GLDAS (VIC, CLM, MOSAIC, and NOAH) and six CMIP5 (FGOALS-g2, GFDL-ESM2G, GISS-E2-H, inmcm4, MIROC5, and MPI-ESM-LR) models. The GWS data were obtained by subtracting the model TWS from the GRACE TWS. The resulting GWS values were compared with in-situ well measurements calibrated using porosity coefficients. For each time series, the trends, spectra, amplitudes, and seasonal components were computed and analyzed. The results suggest that in Poland there has been generally no major TWS or GWS depletion. Our results indicate that when comparing TWS values, better compliance with GRACE data was obtained for GLDAS than for CMIP5 models. However, the GWS analysis showed better consistency of climate models with the well results. The results can contribute toward selection of an appropriate model that, in combination with global GRACE observations, would provide information on groundwater changes in regions with limited or inaccurate ground measurements.

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.

The European Union Water Framework Directive obliges each country to monitor the groundwater level as it is an important source of drinking water, but also an important part of agriculture. A water budget is used for assessing the accuracy of the groundwater level determination. The computations of the water budget are based on evapotranspiration and the state of land surface hydrosphere. On the basis of the determined water budget, statistics and the prognosis for the next 12 months can be computed. In this paper, all the components of the water budget, such as precipitation, surface run-off and evapotranspiration, are studied for the three tested locations in Poland: Suwalki, Zegrzynski and Tarnow cells. The resultant water budget was also determined and presented graphically. On the basis of the water budget research, a prognosis was determined using AutoRegressive Integrated Moving Average (ARIMA) models with the parameters (2,0,2). A comparison between actual water budget data and a prediction prepared for 2015.08–2016.08 indicated that analysing a 12-month period provides a satisfactory prediction assessment.