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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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In this paper, stochastically generated rainfall and corresponding evapotranspiration time series, generated by means of vine copulas, are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically generated time series used. Still, the developed model has great potential for hydrological impact analysis.
Articles | Volume 22, issue 2
Hydrol. Earth Syst. Sci., 22, 1263–1283, 2018
https://doi.org/10.5194/hess-22-1263-2018
Hydrol. Earth Syst. Sci., 22, 1263–1283, 2018
https://doi.org/10.5194/hess-22-1263-2018

Research article 20 Feb 2018

Research article | 20 Feb 2018

A coupled stochastic rainfall–evapotranspiration model for hydrological impact analysis

Minh Tu Pham et al.

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Cited articles

Aas, K., Czado, C., Frigessi, A., and Bakken, H.: Pair-copula constructions of multiple dependence, Insurance: Mathematics and Economics, 44, 182–198, 2009.
Abbott, M., Bathurst, J., Cunge, J., O'Connell, P., and Rasmussen, J.: An introduction to the European Hydrological System – Système Hydrologique Européen, SHE, 1: History and philosophy of a physically-based, distributed modelling system, J. Hydrol., 87, 45–59, 1986.
Akaike, H.: Information theory and an extension of the maximum likelihood principle, in: Second International Symposium on Information Theory, Budapest, Akadémiai Kiado, 1973.
Arnold, J. G., Srinivasan, R., Muttiah, R. S., and Williams, J. R.: Large area hydrologic modeling and assessment. Part I: Model development, J. Am. Water Resour. As., 34, 73–89, 1998.
Bedford, T. and Cooke, R. M.: Vines – a new graphical model for dependent random variables, Ann. Stat., 30, 1031–1068, 2002.
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Short summary
In this paper, stochastically generated rainfall and corresponding evapotranspiration time series, generated by means of vine copulas, are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically generated time series used. Still, the developed model has great potential for hydrological impact analysis.
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