Global-scale gradient-based groundwater models are a new endeavor for hydrologists who wish to improve global hydrological models (GHMs). In particular, the integration of such groundwater models into GHMs improves the simulation of water flows between surface water and groundwater and of capillary rise and thus evapotranspiration. Currently, these models are not able to simulate water table depth adequately over the entire globe. Unsatisfactory model performance compared to well observations suggests that a higher spatial resolution is required to better represent the high spatial variability of land surface and groundwater elevations. In this study, we use New Zealand as a testbed and analyze the impacts of spatial resolution on the results of global groundwater models. Steady-state hydraulic heads simulated by two versions of the global groundwater model G 3 M, at spatial resolutions of 5 arc-minutes (9 km) and 30 arc-seconds (900 m), are compared with observations from the Canterbury region. The output of three other groundwater models with different spatial resolutions is analyzed as well. Considering the spatial distribution of residuals, general patterns of unsatisfactory model performance remain at the higher resolutions, suggesting that an increase in model resolution alone does not fix problems such as the systematic overestimation of hydraulic head. We conclude that (1) a new understanding of how low-resolution global groundwater models can be evaluated is required, and (2) merely increasing the spatial resolution of global-scale groundwater models will not improve the simulation of the global freshwater system.

Abstract. 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 as well as model assumptions required due to the necessarily coarse spatial resolution. The impact of data quality is presented by showing the sensitivity of a groundwater model to changes in the only available global hydraulic conductivity data-set. To better understand the sensitivity of model output to uncertain spatially distributed parameter inputs, 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 G3M. 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 of simulating the direction of flow between the two compartments. Mountainous and dry regions show a high variance in simulated head due to numerical difficulties of the model, limiting the reliability of computed sensitivities in these regions. This instability is likely caused by the uncertainty in surface water body elevation. We conclude that maps of spatially distributed sensitivities can help to understand complex behaviour 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.

We investigate the "macronutrient-access hypothesis", which states that the balance between stoichiometric macronutrient demand and accessible macronutrients controls nutrient assimilation by aquatic heterotrophs. Within this hypothesis, we consider bioavailable dissolved organic carbon (bDOC), reactive nitrogen (N) and reactive phosphorus (P) to be the macronutrients accessible to heterotrophic assimilation. Here, reactive N and P are the sums of dissolved inorganic N (nitrate-N, nitrite-N, ammonium-N), soluble-reactive P (SRP), and bioavailable dissolved organic N (bDON) and P (bDOP). Previous data from various freshwaters suggests this hypothesis, yet clear experimental support is missing. We assessed this hypothesis in a proof-of-concept experiment for waters from four small agricultural streams. We used seven different bDOC:reactive N and bDOC:reactive P ratios, induced by seven levels of alder leaf leachate addition. With these treatments and a stream-water specific bacterial inoculum, we conducted a 3-day experiment with three independent replicates per combination of stream water, treatment, and sampling occasion. Here, we extracted dissolved organic matter (DOM) fluorophores by measuring excitation-emission matrices with subsequent parallel factor decomposition (EEM-PARAFAC). We assessed the true bioavailability of DOC, DON, and the DOM fluorophores as the concentration difference between the beginning and end of each experiment. Subsequently, we calculated the bDOC and bDON concentrations based on the bioavailable EEM-PARAFAC fluorophores, and compared the calculated bDOC and bDON concentrations to their true bioavailability. Due to very low DOP concentrations, the DOP determination uncertainty was high, and we assumed DOP to be a negligible part of the reactive P. For bDOC and bDON, the true bioavailability measurements agreed with the same fractions calculated indirectly from bioavailable EEM-PARAFAC fluorophores (bDOC r2 = 0.96, p < 0.001; bDON r2 = 0.77, p < 0.001). Hence we could predict bDOC and bDON concentrations based on the EEM-PARAFAC fluorophores. The ratios of bDOC:reactive N (sum of bDON and DIN) and bDOC:reactive P (equal to SRP) exerted a strong, predictable stoichiometric control on reactive N and P uptake (R2 = 0.80 and 0.83). To define zones of C:N:P (co-)limitation of heterotrophic assimilation, we used a novel ternary-plot approach combining our data with literature data on C:N:P ranges of bacterial biomass. Here, we found a zone of maximum reactive N uptake (C:N:P approx. > 114: < 9:1), reactive P uptake (C:N:P approx. > 170:21: < 1) and reactive N and P co-limitation of nutrient uptake (C:N:P approx. > 204:14:1). The “macronutrient-access hypothesis” links ecological stoichiometry and biogeochemistry, and may be of importance for nutrient uptake in many freshwater ecosystems. However, this experiment is only a starting point and this hypothesis needs to be corroborated by further experiments for more sites, by in-situ studies, and with different DOC sources.

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 gradientbased 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, indicat-ing 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.

Anthropogenic nutrient inputs led to severe degradation of surface water resources, affecting aquatic ecosystem health and functioning. Ecosystem functions such as nutrient cycling and ecosystem metabolism are not only affected by the over-abundance of a single macronutrient but also by the stoichiometry of the reactive molecular forms of dissolved organic carbon (rOC), nitrogen (rN), and phosphorus (rP). So far, studies mainly considered only single macronutrients or used stoichiometric ratios such as N:P or C:N independent from each other. We argue that a mutual assessment of reactive nutrient ratios rOC:rN:rP relative to organismic demands enables us to refine the definition of nutrient depletion versus excess and to understand their linkages to catchment-internal biogeochemical and hydrological processes. Here we show that the majority (94 %) of the studied 574 German catchments show a depletion or co-depletion in rOC and rP, illustrating the ubiquity of excess N in anthropogenically influenced landscapes. We found an emerging spatial pattern of depletion classes linked to the interplay of agricultural sources and subsurface denitrification for rN and topographic controls of rOC. We classified catchments into stoichio-static and stochio-dynamic catchments based on their degree of intra-annual variability of rOC:rN:rP ratios. Stoichio-static catchments (36% of all catchments) tend to have higher rN median concentrations, lower temporal rN variability and generally low rOC medians. Our results demonstrate the severe extent of imbalances in rOC:rN:rP ratios in German rivers due to human activities. This likely affects the inland-water nutrient retention efficiency, their level of eutrophication, and their role in the global carbon cycle. Thus, it calls for a more holistic catchment and aquatic ecosystem management integrating rOC:rN:rP stoichiometry as a fundamental principle.