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WaterGAP is a global hydrological model that quantifies human use of groundwater and surface water as well as water flows and water storage and thus water resources on all land areas of the Earth. Since 1996, it has served to assess water resources and water stress both historically and in the future, in particular under climate change. It has improved our understanding of continental water storage variations, with a focus on overexploitation and depletion of water resources. In this paper, we describe the most recent model version WaterGAP 2.2d, including the water use models, the linking model that computes net abstractions from groundwater and surface water and the WaterGAP Global Hydrology Model (WGHM). Standard model output variables that are freely available at a data repository are explained. In addition, the most requested model outputs, total water storage anomalies, streamflow and water use, are evaluated against observation data. Finally, we show examples of assessments of the global freshwater system that can be achieved with WaterGAP 2.2d model output. [ABSTRACT FROM AUTHOR]

WaterGAP is a global hydrological model that quantifies human use of groundwater and surface water as well as water flows and water storage and thus water resources on all land areas of the Earth. Since 1996, it has served to assess water resources and water stress both historically and in the future, in particular under climate change. It has improved our understanding of continental water storage variations, with a focus on overexploitation and depletion of water resources. In this paper, we describe the most recent model version WaterGAP 2.2d, including the water use models, the linking model that computes net abstractions from groundwater and surface water and the WaterGAP Global Hydrology Model WGHM. Standard model output variables that are freely available at a data repository are explained. In addition, the most requested model outputs, total water storage anomalies, streamflow and water use, are evaluated against observation data. Finally, we show examples of assessments of the global freshwater system that can be done with WaterGAP2.2d model output. [ABSTRACT FROM AUTHOR]

In global hydrological models, groundwater storages and flows are generally simulated by linear reservoir models. Recently, the first global gradient-based groundwater models were developed in order to improve the representation of groundwater–surface-water interactions, capillary rise, lateral flows, and human water use impacts. However, the reliability of model outputs is limited by a lack of data and by uncertain model assumptions that are necessary due to the coarse spatial resolution. The impact of data quality is presented in this study by showing the sensitivity of a groundwater model to changes in the only available global hydraulic conductivity dataset. To better understand the sensitivity of model output to uncertain spatially distributed parameters, we present the first application of a global sensitivity method for a global-scale groundwater model using nearly 2000 steady-state model runs of the global gradient-based groundwater model G 3 M. By applying the Morris method in a novel domain decomposition approach that identifies global hydrological response units, spatially distributed parameter sensitivities are determined for a computationally expensive model. Results indicate that globally simulated hydraulic heads are equally sensitive to hydraulic conductivity, groundwater recharge, and surface water body elevation, though parameter sensitivities vary regionally. For large areas of the globe, rivers are simulated to be either losing or gaining, depending on the parameter combination, indicating a high uncertainty in simulating the direction of flow between the two compartments. Mountainous and dry regions show a high variance in simulated head due to numerical instabilities of the model, limiting the reliability of computed sensitivities in these regions. This is likely caused by the uncertainty in surface water body elevation. We conclude that maps of spatially distributed sensitivities can help to understand the complex behavior of models that incorporate data with varying spatial uncertainties. The findings support the selection of possible calibration parameters and help to anticipate challenges for a transient coupling of the model. [ABSTRACT FROM AUTHOR]

Global-scale hydrological models have recently moved to include gradient-based groundwater models to better represent groundwater-surface water interactions, lateral and vertical flows as well as human water use impacts. G³M is a new MODFLOW-like groundwater model with a spatial resolution of 5' that replaces the former linear groundwater reservoir in the 0.5° WaterGAP Global Hydrology Model (WGHM).We present first results of the fully transient integration of the 5' groundwater model into the 0.5° global hydrology model. Main challenges include (1) the simulation of groundwater on with a low spatial resolution, (2) the connection of two models with different grid sizes (between the 5' groundwater model and the 0.5° global hydrology model) and (3) how the fluxes will be exchanged and distributed at different scales to preserve the water balance and to preserve high resolution information from the finer grid-scale of the groundwater model for the 0.5° resolution. The coupling across scales is challenging mostly because of its implications for gaining and losing surface water bodies. Results of a sensitivity analysis for an uncoupled steady-state simulation are discussed along with the implications for a fully transient model. In addition, an alternative approach for simulating flows between groundwater and surface water bodies is presented.To validate the transient simulations, we compare model results to time series of observed groundwater head. Furthermore, we present a comparison of total water storage change to GRACE. We discuss how the results are influenced by using a gradient-based instead of the linear reservoir approach for modeling groundwater in global hydrological models. [ABSTRACT FROM AUTHOR]