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Abstract. Groundwater serves as a crucial freshwater resource for people and ecosystems, playing a vital role in adapting to climate change. Yet, its availability and dynamics are affected by climate variations, changes in land use, and abstraction. Despite its importance, our understanding of how global change will influence groundwater in the future remains limited. Multi-model ensembles are powerful tools for impact assessments; compared to single-model studies, they provide a more comprehensive understanding of uncertainties and enhance the robustness of projections by capturing a range of possible outcomes. However, to date, no ensemble of groundwater models has been available to assess the impacts of global change. Here, we present the new Groundwater sector within ISIMIP, which combines multiple global, continental, and regional-scale groundwater models. We describe the rationale for the sector, the sectoral output variables that underpinned the modeling protocol, and showcase current model differences and possible future analysis. Currently, eight models are participating in this sector, ranging from gradient-based groundwater models to specialized karst recharge models, each producing up to 19 out of 23 modeling protocol-defined output variables. To showcase the benefits of a joint sector, we utilize available model outputs of the participating models to show the substantial differences in estimating water table depth (global arithmetic mean 6–127 m) and groundwater recharge (global arithmetic mean 78–228 mm yr−1), which is consistent with recent studies on the uncertainty of groundwater models, but with distinct spatial patterns. We further outline synergies with 13 of the 17 existing ISIMIP sectors and specifically discuss those with the global water and water quality sectors. Finally, this paper outlines a vision for ensemble-based groundwater studies that can contribute to a better understanding of the impacts of climate change, land use change, environmental change, and socio-economic change on the world's largest accessible freshwater store – groundwater. 

Abstract Global water models are increasingly used to understand past, present and future water cycles, but disagreements between simulated variables make model-based inferences uncertain. Although there is empirical evidence of different large-scale relationships in hydrology, these relationships are rarely considered in model evaluation. Here we evaluate global water models using functional relationships that capture the spatial co-variability of forcing variables (precipitation, net radiation) and key response variables (actual evapotranspiration, groundwater recharge, total runoff). Results show strong disagreement in both shape and strength of model-based functional relationships, especially for groundwater recharge. Empirical and theory-derived functional relationships show varying agreements with models, indicating that our process understanding is particularly uncertain for energy balance processes, groundwater recharge processes and in dry and/or cold regions. Functional relationships offer great potential for model evaluation and an opportunity for fundamental advances in global hydrology and Earth system research in general. 

Abstract Enhanced drought modeling is crucial for realistic prediction and effective management of water resources, especially with climate change anticipated to exacerbate drought frequency and severity. Global water models (GWMs) simulate historical and future terrestrial water storage (TWS) with continuous spatial and temporal coverage. However, a global evaluation of TWS simulations by GWMs focused on drought is lacking. Here we evaluate, for the first time, GWMs' capability to represent TWS droughts by comparing simulations with Gravity Recovery and Climate Experiment satellite data. We find notable underestimation of drought severity and coverage by GWMs, across diverse regions, including North America, South America, Africa, and Northern Asia. When examined without trend removal, the underestimation of TWS droughts is more pronounced in recent years (2016–2019) compared to 2002–2015, especially in northern latitudes. This underrepresentation highlights the necessity to improve GWMs to simulate TWS droughts. Our results imply that previously reported future TWS projections could have underestimated droughts. 

Abstract. Billions of people rely on groundwater as being an accessible source of drinking water and for irrigation, especially in times of drought. Its importance will likely increase with a changing climate. It is still unclear, however, how climate change will impact groundwater systems globally and, thus, the availability of this vital resource. Groundwater recharge is an important indicator for groundwater availability, but it is a water flux that is difficult to estimate as uncertainties in the water balance accumulate, leading to possibly large errors in particular in dry regions. This study investigates uncertainties in groundwater recharge projections using a multi-model ensemble of eight global hydrological models (GHMs) that are driven by the bias-adjusted output of four global circulation models (GCMs). Pre-industrial and current groundwater recharge values are compared with recharge for different global warming (GW) levels as a result of three representative concentration pathways (RCPs). Results suggest that projected changes strongly vary among the different GHM–GCM combinations, and statistically significant changes are only computed for a few regions of the world. Statistically significant GWR increases are projected for northern Europe and some parts of the Arctic, East Africa, and India. Statistically significant decreases are simulated in southern Chile, parts of Brazil, central USA, the Mediterranean, and southeastern China. In some regions, reversals of groundwater recharge trends can be observed with global warming. Because most GHMs do not simulate the impact of changing atmospheric CO2 and climate on vegetation and, thus, evapotranspiration, we investigate how estimated changes in GWR are affected by the inclusion of these processes. In some regions, inclusion leads to differences in groundwater recharge changes of up to 100 mm per year. Most GHMs with active vegetation simulate less severe decreases in groundwater recharge than GHMs without active vegetation and, in some regions, even increases instead of decreases are simulated. However, in regions where GCMs predict decreases in precipitation and where groundwater availability is the most important, model agreement among GHMs with active vegetation is the lowest. Overall, large uncertainties in the model outcomes suggest that additional research on simulating groundwater processes in GHMs is necessary. 

Anthropogenic climate change is expected to affect global river flow. Here, we analyze time series of low, mean, and high river flows from 7250 observatories around the world covering the years 1971 to 2010. We identify spatially complex trend patterns, where some regions are drying and others are wetting consistently across low, mean, and high flows. Trends computed from state-of-the-art model simulations are consistent with the observations only if radiative forcing that accounts for anthropogenic climate change is considered. Simulated effects of water and land management do not suffice to reproduce the observed trend pattern. Thus, the analysis provides clear evidence for the role of externally forced climate change as a causal driver of recent trends in mean and extreme river flow at the global scale.