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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hess-2019-111
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-111
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 01 Apr 2019

Submitted as: research article | 01 Apr 2019

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Hydrology and Earth System Sciences (HESS).

Global catchment modelling using World-Wide HYPE (WWH), open data and stepwise parameter estimation

Berit Arheimer1, Rafael Pimentel1,2, Kristina Isberg1, Louise Crochemore1, Jafet C. M. Andersson1, Abdulghani Hasan1,3, and Luis Pineda1,4 Berit Arheimer et al.
  • 1Swedish Meteorological and Hydrological Institute (SMHI), Folkborgsvägen 17, 60176 Norrköping, Sweden
  • 2University of Cordoba, Edf. Leonardo Da Vinci, Campus de Rabanales, 14071, Córdoba, Spain
  • 3Lund University, Box 117, SE-221 00, Lund, Sweden
  • 4Proyecto Yachay, Hacienda San José, Urcuquí, Ecuador

Abstract. Recent advancements in catchment hydrology (such as understanding hydrological processes, 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 at the global scale for the first time. The modelling procedure was challenging but doable and even the first model version show 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 Earths 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, interfacial fluxes, and the pathways between various compartments. Global parameter values were estimated using a step-wise approach for groups of parameters regulating specific processes and catchment characteristics in representative gauged catchments. Daily 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 an average 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 in 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 calibration and reconsidering parts of the model structure for the next WWH version. The calibration cycle should be repeated a couple of times to find robust values under new fixed parameter conditions. For the next iteration, special focus will be given to precipitation, evapotranspiration, soil storage, and dynamics from hydrological features, such as lakes, reservoirs, glaciers, and floodplains. This first model version clearly indicates challenges in large scale modelling, usefulness of open data and current gaps in processes understanding. Parts of the WWH can be shared with other modellers working at the regional scale to appreciate local knowledge, establish a critical mass of experts and improve the model in a collaborative manner. Setting up a global catchment model has to be a long-term commitment of continuous model refinements to achieve successful and truly useful results.

Berit Arheimer et al.
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Short summary
How far can we reach in predicting river flow globally, using integrated catchment modelling and open global data? For the first time, a catchment model was applied world-wide covering the entire globe with relatively high resolution. The results show that stepwise calibration provided better performance than traditional modelling of the globe. The study highlights that open data and models are crucial to advance hydrological sciences by sharing knowledge and enabling transparent evaluation.
How far can we reach in predicting river flow globally, using integrated catchment modelling and...
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