Open data make it possible to set up multi-basin models for large domains across environmental, climate and administrative boundaries. This study presents new methods for evaluating a number of aspects of multi-basin model performance, while exploring the performance of the E-HYPE_v2.1 model for several evaluation criteria in 181 independent river gauges across the European continent. Embedded model assumptions on dominant flow generating mechanisms are analysed by correlating physiographical characteristics to the flow regime. The results indicate that the model captures the spatial variability of flow and is therefore suitable for predictions in ungauged basins. The model shows good performance of long-term means and seasonality, while short-term daily variability is less well represented, especially for Mediterranean and mountainous areas. Major identified shortcomings refer to the resolution of precipitation patterns, aquifer exchanges, water extractions and regulation. This will guide the work with the next model version for which improvements in input data, processes and calibration have been identified to potentially contribute most to improved model performance.

Impacts of climate change at 1.5, 2 and 3 °C mean global warming above preindustrial level are investigated and compared for runoff, discharge and snowpack in Europe. Ensembles of climate projections representing each of the warming levels were assembled to describe the hydro-meteorological climate at 1.5, 2 and 3 °C. These ensembles were then used to force an ensemble of five hydrological models and changes to hydrological indicators were calculated. It is seen that there are clear changes in local impacts on evapotranspiration, mean, low and high runoff and snow water equivalent between a 1.5, 2 and 3 °C degree warmer world. In a warmer world, the hydrological impacts of climate change are more intense and spatially more extensive. Robust increases in runoff affect the Scandinavian mountains at 1.5 °C, but at 3 °C extend over most of Norway, Sweden and northern Poland. At 3 °C, Norway is affected by robust changes in all indicators. Decreases in mean annual runoff are seen only in Portugal at 1.5 °C warming, but at 3 °C warming, decreases to runoff are seen around the entire Iberian coast, the Balkan Coast and parts of the French coast. In affected parts of Europe, there is a distinct increase in the changes to mean, low and high runoff at 2 °C compared to 1.5 °C, strengthening the case for mitigation to lower levels of global warming. Between 2 and 3 °C, the changes in low and high runoff levels continue to increase, but the changes to mean runoff are less clear. Changes to discharge in Europe’s larger rivers are less distinct due to the lack of homogenous and robust changes across larger river catchments, with the exception of Scandinavia where discharges increase with warming level.

Recent advancements in catchment hydrology (such as understanding catchment similarity, accessing new data sources, and refining methods for parameter constraints) make it possible to apply catchment models for ungauged basins over large domains. Here we present a cutting-edge case study applying catchment-modelling techniques with evaluation against river flow at the global scale for the first time. The modelling procedure was challenging but doable, and even the first model version showed better performance than traditional gridded global models of river flow. We used the open-source code of the HYPE model and applied it for >130 000 catchments (with an average resolution of 1000 km²), delineated to cover the Earth's landmass (except Antarctica). The catchments were characterized using 20 open databases on physiographical variables, to account for spatial and temporal variability of the global freshwater resources, based on exchange with the atmosphere (e.g. precipitation and evapotranspiration) and related budgets in all compartments of the land (e.g. soil, rivers, lakes, glaciers, and floodplains), including water stocks, residence times, and the pathways between various compartments. Global parameter values were estimated using a stepwise approach for groups of parameters regulating specific processes and catchment characteristics in representative gauged catchments. Daily and monthly time series (>10 years) from 5338 gauges of river flow across the globe were used for model evaluation (half for calibration and half for independent validation), resulting in a median monthly KGE of 0.4. However, the World-Wide HYPE (WWH) model shows large variation in model performance, both between geographical domains and between various flow signatures. The model performs best (KGE >0.6) in the eastern USA, Europe, South-East Asia, and Japan, as well as in parts of Russia, Canada, and South America. The model shows overall good potential to capture flow signatures of monthly high flows, spatial variability of high flows, duration of low flows, and constancy of daily flow. Nevertheless, there remains large potential for model improvements, and we suggest both redoing the parameter estimation and reconsidering parts of the model structure for the next WWH version. This first model version clearly indicates challenges in large-scale modelling, usefulness of open data, and current gaps in process understanding. However, we also found that catchment modelling techniques can contribute to advance global hydrological predictions. Setting up a global catchment model has to be a long-term commitment as it demands many iterations; this paper shows a first version, which will be subjected to continuous model refinements in the future. WWH is currently shared with regional/local modellers to appreciate local knowledge.

Although many potential evapotranspiration (PET) formulas are available, there is still a lack of knowledge on when and where to use them in catchment modeling world‐wide. Here we experimented with three different formulas in a global hydrological model (the World‐wide HYPE), using 15 years of observations from 5,338 streamflow gauges and global evapotranspiration from Earth‐observations (MOD16). We tested model performance in a multi‐process approach to select the best formula for catchments covering the global landmass. From comparing the results with land‐cover, climate classification, water‐energy limitations, we found that climate is the main driver behind the spatial patterns in model performance. Hargreaves was the best PET formula in 50% of the catchments, most of them located in the Amazonas, central Europe, and Oceania; Jensen‐Haise was better for catchments in northern latitudes (36%). Finally, Priestley‐Taylor was the best formula for India and latitudes above 65° North. The selection of a PET formula seems to be more critical in tropical regions close to the equator, where the differences in performance are above 50%. This is also where PET is highest. We found a strong connection between the five main Köppen regions and the PET formulas, further supported by landcover analysis. Hence, the PET formulas differed in their capacity to provide useful input to the water balance modeling, with complex formulas only giving improved predictions in temperate and polar regions; however, for the rest of the globe simpler formulas were better. We thus recommend to apply different PET formulas based on climatic regions world‐wide.