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Stochastic assessment of Phien generalized reservoir storage–yield–probability models using global runoff data records

Publication Type : Journal Article

Publisher : Journal of Hydrology

Source : Journal of Hydrology, Volume 529, p.1433 - 1441 (2015)

Url : http://www.sciencedirect.com/science/article/pii/S0022169415006101

Keywords : Generalised storage–yield function, Phien models, Reservoir capacity, SPA

Campus : Coimbatore

School : School of Engineering

Department : Civil

Verified : No

Year : 2015

Abstract : pSummary This study has carried out an assessment of Phien generalised storage–yield–probability (S–Y–P) models using recorded runoff data of six global rivers that were carefully selected such that they satisfy the criteria specified for the models. Using stochastic hydrology, 2000 replicates of the historic records were generated and used to drive the sequent peak algorithm (SPA) for estimating capacity of hypothetical reservoirs at the respective sites. The resulting ensembles of reservoir capacity estimates were then analysed to determine the mean, standard deviation and quantiles, which were then compared with corresponding estimates produced by the Phien models. The results showed that Phien models produced a mix of significant under- and over-predictions of the mean and standard deviation of capacity, with the under-prediction situations occurring as the level of development reduces. On the other hand, consistent over-prediction was obtained for full regulation for all the rivers analysed. The biases in the reservoir capacity quantiles were equally high, implying that the limitations of the Phien models affect the entire distribution function of reservoir capacity. Due to very high values of these errors, it is recommended that the Phien relationships should be avoided for reservoir planning./p

Cite this Research Publication : A. J. Adeloye, Soundharajan B., Musto, J. N., and Chiamsathit, C., “Stochastic assessment of Phien generalized reservoir storage–yield–probability models using global runoff data records”, Journal of Hydrology, vol. 529, pp. 1433 - 1441, 2015.

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