Abstract. Observed streamflow data from 966 medium sized catchments (1000-5000 km 2 ) around the globe were used to comprehensively evaluate the daily runoff estimates of six global hydrological models (GHMs) and four land surface models (LSMs) produced as part of tier-1 of the eartH2Observe project. The models were all driven by the WATCH Forcing Data ERA-Interim (WFDEI) meteorological dataset, but used different datasets for non-meteorologic inputs and were run at various spatial and temporal resolutions, although all data were re-sampled to a common 0.5• spatial and daily temporal resolution. For the evaluation, we used a broad range of performance metrics related to important aspects of the hydrograph. We found pronounced intermodel performance differences, underscoring the importance of hydrological model uncertainty in addition to climate input uncertainty, for example in studies assessing the hydrological impacts of climate change. The uncalibrated GHMs were found to perform, on average, better than the uncalibrated LSMs in snow-dominated regions, while the ensemble mean was found to perform only slightly worse than the best (calibrated) model. The inclusion of less-accurate models did not appreciably degrade the ensemble performance. Overall, we argue that more effort should be devoted on calibrating and regionalizing the parameters of macro-scale models. We further found that, despite adjustments using gauge observations, the WFDEI precipitation data still contain substantial biases that propagate into the simulated runoff. The early bias in the spring snowmelt peak exhibited by most models is probably primarily due to the widespread precipitation underestimation at high northern latitudes.

Abstract. The dataset presented here consists of an ensemble of 10 global hydrological and land surface models for the period 1979–2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution). The current dataset serves as a state of the art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i) snow-dominated regions and (ii) tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB) showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3 yr−1 (334 kg m−2 yr−1), while the ensemble mean of total evaporation was 537 kg m−2 yr−1. All data are made available openly through a Water Cycle Integrator portal (WCI, wci.earth2observe.eu), and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. The DOI for the data is https://doi.org/10.1016/10.5281/zenodo.167070.

Abstract. When assessing global water resources with hydrological models, it is essential to know about methodological uncertainties. The values of simulated water balance components may vary due to different spatial and temporal aggregations, reference periods, and applied climate forcings, as well as due to the consideration of human water use, or the lack thereof. We analyzed these variations over the period 1901–2010 by forcing the global hydrological model WaterGAP 2.2 (ISIMIP2a) with five state-of-the-art climate data sets, including a homogenized version of the concatenated WFD/WFDEI data set. Absolute values and temporal variations of global water balance components are strongly affected by the uncertainty in the climate forcing, and no temporal trends of the global water balance components are detected for the four homogeneous climate forcings considered (except for human water abstractions). The calibration of WaterGAP against observed long-term average river discharge Q significantly reduces the impact of climate forcing uncertainty on estimated Q and renewable water resources. For the homogeneous forcings, Q of the calibrated and non-calibrated regions of the globe varies by 1.6 and 18.5 %, respectively, for 1971–2000. On the continental scale, most differences for long-term average precipitation P and Q estimates occur in Africa and, due to snow undercatch of rain gauges, also in the data-rich continents Europe and North America. Variations of Q at the grid-cell scale are large, except in a few grid cells upstream and downstream of calibration stations, with an average variation of 37 and 74 % among the four homogeneous forcings in calibrated and non-calibrated regions, respectively. Considering only the forcings GSWP3 and WFDEI_hom, i.e., excluding the forcing without undercatch correction (PGFv2.1) and the one with a much lower shortwave downward radiation SWD than the others (WFD), Q variations are reduced to 16 and 31 % in calibrated and non-calibrated regions, respectively. These simulation results support the need for extended Q measurements and data sharing for better constraining global water balance assessments. Over the 20th century, the human footprint on natural water resources has become larger. For 11–18% of the global land area, the change of Q between 1941–1970 and 1971–2000 was driven more strongly by change of human water use including dam construction than by change in precipitation, while this was true for only 9–13 % of the land area from 1911–1940 to 1941–1970.

Within the last decades, the water temperature of several European lakes has risen. It is assumed that these temperature increases are due to a reconfiguration of the heat‐balance components. This study explores the dominant modifications of heat exchange with the atmosphere and their temporal evolutions. The objective is to identify the primary changes in heat fluxes and the sequence of events of the reconfiguration for the period 1984–2011. For this purpose, a model was applied to Lake Constance to estimate the contributions of the individual heat fluxes to the total heat balance. The results show that increasing absorption of solar radiation (+0.21 ± 0.13 W m−2 yr−1) and of longwave radiation (+0.25 ± 0.11 W m−2 yr−1) was responsible for the lake surface warming of 0.046 ± 0.011°C yr−1. Heat losses to the atmosphere by longwave emission (−0.24 ± 0.06 W m−2 yr−1) and by latent heat flux (−0.27 ± 0.12 W m−2 yr−1) have intensified in parallel due to higher lake surface temperatures. The heat budget is in a quasi‐steady state, whereas incoming solar radiation and the warmer atmosphere increased the lake surface temperature; the warmer surface emits more longwave radiation and more water is evaporated. At each level of the slowly increasing water temperature, the heat fluxes are balanced. The overall change of the total heat content, however, is relatively little. Although the cooling effect of inflowing rivers decreased, this contribution is also small.

Abstract. The dataset presented here consists of an ensemble of ten global hydrological and land surface models for the period 1979–2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution). The current dataset serves as a state-of-the-art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i) snow-dominate regions and (ii) tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not being reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB) showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3/yr (334 kg/m2/yr) while the ensemble mean of total evaporation was 537 kg/m2/yr. All data are made available openly through a Water Cycle Integrator portal (WCI, wci.earth2observe.eu), and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. The doi for the data is: doi:10.5281/zenodo.167070