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

Adebayo Adeloye, Soundharajan Bankaru Swamy, Chuthamat Chiamsathit

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)1433-1441
Number of pages9
JournalJournal of Hydrology
Volume529
Issue numberPart 3
Early online date24 Aug 2015
DOIs
Publication statusPublished - Oct 2015

Fingerprint

runoff
prediction
river
hydrology
global model

Keywords

  • Generalised storage-yield function
  • Phien models
  • Reservoir capacity
  • SPA

ASJC Scopus subject areas

  • Water Science and Technology

Cite this

Adeloye, Adebayo ; Bankaru Swamy, Soundharajan ; Chiamsathit, Chuthamat. / Stochastic assessment of Phien generalized reservoir storage-yield-probability models using global runoff data records. In: Journal of Hydrology. 2015 ; Vol. 529, No. Part 3. pp. 1433-1441.
@article{9697d9d821e34022b1314d48874a690f,
title = "Stochastic assessment of Phien generalized reservoir storage-yield-probability models using global runoff data records",
abstract = "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.",
keywords = "Generalised storage-yield function, Phien models, Reservoir capacity, SPA",
author = "Adebayo Adeloye and {Bankaru Swamy}, Soundharajan and Chuthamat Chiamsathit",
year = "2015",
month = "10",
doi = "10.1016/j.jhydrol.2015.08.038",
language = "English",
volume = "529",
pages = "1433--1441",
journal = "Journal of Hydrology",
issn = "0022-1694",
publisher = "Elsevier",
number = "Part 3",

}

Stochastic assessment of Phien generalized reservoir storage-yield-probability models using global runoff data records. / Adeloye, Adebayo; Bankaru Swamy, Soundharajan; Chiamsathit, Chuthamat.

In: Journal of Hydrology, Vol. 529, No. Part 3, 10.2015, p. 1433-1441.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Stochastic assessment of Phien generalized reservoir storage-yield-probability models using global runoff data records

AU - Adeloye, Adebayo

AU - Bankaru Swamy, Soundharajan

AU - Chiamsathit, Chuthamat

PY - 2015/10

Y1 - 2015/10

N2 - 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.

AB - 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.

KW - Generalised storage-yield function

KW - Phien models

KW - Reservoir capacity

KW - SPA

UR - http://www.scopus.com/inward/record.url?scp=84945493170&partnerID=8YFLogxK

U2 - 10.1016/j.jhydrol.2015.08.038

DO - 10.1016/j.jhydrol.2015.08.038

M3 - Article

VL - 529

SP - 1433

EP - 1441

JO - Journal of Hydrology

JF - Journal of Hydrology

SN - 0022-1694

IS - Part 3

ER -