Abstract
Abstract. 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.
Highlights
Global hydrological models with various properties and structures are provided by several modelling communities
The merging of several data sources resulted in consistency between available information on waterbodies, topographic data, and the river network, so that this information can be used in catchment modelling and provide results of river flow at a resolution of some 1000 km2 globally
For World-Wide HYPE, the Yangtze River came out as no. 11 and Mekong as no. 12, and it should be noted that the river flow to the Río de la Plata was separated into the Paraná River and the Uruguay River
Summary
Global hydrological models with various properties and structures are provided by several modelling communities 2015), it is well recognized that uncertainties associated with existing models are high when simulating the water cycle at the global scale (e.g. Wood et al, 2011). Some communities suggest hyper-resolution (Bierkens et al, 2015), while others propose better coupling with Earth observations (Sood and Smakhtin, 2015). We argue for improving global hydrological-model performance by applying methods from the catchment modelling community. Having catchments as a calculation unit makes it possible to apply an ecosystem approach and account for co-evolution of processes at the landscape scale The structure of the catchment model is usually a function of the modellers’ hydrological understanding, and it is admitted that model parameters cannot be measured directly in many cases, but have to be estimated (Wagener, 2003)
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