Articles | Volume 19, issue 4
Hydrol. Earth Syst. Sci., 19, 2101–2117, 2015
https://doi.org/10.5194/hess-19-2101-2015
Hydrol. Earth Syst. Sci., 19, 2101–2117, 2015
https://doi.org/10.5194/hess-19-2101-2015
Research article
30 Apr 2015
Research article | 30 Apr 2015

Virtual laboratories: new opportunities for collaborative water science

S. Ceola et al.

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Cited articles

Andreassian, V., Hall, A., Chahinian, N., and Schaake, J.: Large Sample Basin Experiments for Hydrological Model Parameterization: Results of the Model Parameter Experiment – MOPEX – IAHS Proceedings & Reports No. 307, IAHS Press, 2006.
Arheimer, B., Wallman, P., Donnelly, C., Nyström, K., and Pers, C.: E-HypeWeb: Service for Water and Climate Information – and Future Hydrological Collaboration across Europe?, in: Environmental Software Systems. Frameworks of eEnvironment, edited by: Hřebíček, J., Schimak, G., and Denzer, R., Vol. 359 of IFIP Advances in Information and Communication Technology, 657–666, Springer Berlin Heidelberg, https://doi.org/10.1007/978-3-642-22285-6_71, 2011.
Berghuijs, W. R., Woods, R. A., and Hrachowitz, M.: A precipitation shift from snow towards rain leads to a decrease in streamflow, Nat. Clim. Change, 4, 583–586, https://doi.org/10.1038/nclimate2246, 2014.
Bergström, S.: Development and application of a conceptual runoff model for Scandinavian catchments – SMHI Reports RHO No.7, Tech. rep., SMHI, Norrköping, 1976.
Beven, K. J.: Uniqueness of place and process representations in hydrological modelling, Hydrol. Earth Syst. Sci., 4, 203–213, https://doi.org/10.5194/hess-4-203-2000, 2000.
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We present the outcomes of a collaborative hydrological experiment undertaken by five different international research groups in a virtual laboratory. Moving from the definition of accurate protocols, a rainfall-runoff model was independently applied by the research groups, which then engaged in a comparative discussion. The results revealed that sharing protocols and running the experiment within a controlled environment is fundamental for ensuring experiment repeatability and reproducibility.