Integrated water resources management

development of data parsimonious models for reservoir planning

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Data parsimonious models are developed which offer the realistic possibility for reservoir storage-yield-reliability (S-Y-R) planning analysis at ungauged sites. One of the models was based on multiple linear regression analysis and the second set of models were designed using artificial neural networks (ANNs); both models use input variables comprising runoff summary statistics, e.g. the CV of annual runoff, and reservoir systems variables such as the demand and reliability index. The models performed satisfactorily when tested using independent data sets not utilised during their development. Finally, algorithms for obtaining the runoff summary statistics at ungauged sites are presented. Copyright © 2009 IAHS Press.

    Original languageEnglish
    Title of host publicationRole of Hydrology in Water Resources Management
    EditorsHans-Jürgen Liebscher, Robin Clarke, John Rodda, Gert Schultz, Andreas Schumann, Lucio Ub
    PublisherIAHS Press
    Pages144-150
    Number of pages7
    Volume327
    ISBN (Print)9781901502947
    Publication statusPublished - 2009
    EventUNESCO/IAHS International Symposium on The Role of Hydrology in Water Resources Management - Isle of Capri, Naples, Italy
    Duration: 14 Oct 200816 Oct 2008

    Publication series

    NameIAHS Red Book Series
    Number327

    Conference

    ConferenceUNESCO/IAHS International Symposium on The Role of Hydrology in Water Resources Management
    CountryItaly
    CityIsle of Capri, Naples
    Period14/10/0816/10/08

    Fingerprint

    runoff
    artificial neural network
    regression analysis
    water resources management
    planning
    statistics
    demand
    analysis
    index

    Keywords

    • Artificial neural networks
    • Multiple regression
    • Over-year capacity
    • Sequent peak algorithm
    • Storage-yield-reliability
    • Ungauged sites
    • Within-year capacity

    Cite this

    Adeloye, A. (2009). Integrated water resources management: development of data parsimonious models for reservoir planning. In H-J. Liebscher, R. Clarke, J. Rodda, G. Schultz, A. Schumann, & L. Ub (Eds.), Role of Hydrology in Water Resources Management (Vol. 327, pp. 144-150). (IAHS Red Book Series; No. 327). IAHS Press.
    Adeloye, Adebayo. / Integrated water resources management : development of data parsimonious models for reservoir planning. Role of Hydrology in Water Resources Management. editor / Hans-Jürgen Liebscher ; Robin Clarke ; John Rodda ; Gert Schultz ; Andreas Schumann ; Lucio Ub. Vol. 327 IAHS Press, 2009. pp. 144-150 (IAHS Red Book Series; 327).
    @inproceedings{a40fc59938e44b6083f3451e6d3214a4,
    title = "Integrated water resources management: development of data parsimonious models for reservoir planning",
    abstract = "Data parsimonious models are developed which offer the realistic possibility for reservoir storage-yield-reliability (S-Y-R) planning analysis at ungauged sites. One of the models was based on multiple linear regression analysis and the second set of models were designed using artificial neural networks (ANNs); both models use input variables comprising runoff summary statistics, e.g. the CV of annual runoff, and reservoir systems variables such as the demand and reliability index. The models performed satisfactorily when tested using independent data sets not utilised during their development. Finally, algorithms for obtaining the runoff summary statistics at ungauged sites are presented. Copyright {\circledC} 2009 IAHS Press.",
    keywords = "Artificial neural networks, Multiple regression, Over-year capacity, Sequent peak algorithm, Storage-yield-reliability, Ungauged sites, Within-year capacity",
    author = "Adebayo Adeloye",
    year = "2009",
    language = "English",
    isbn = "9781901502947",
    volume = "327",
    series = "IAHS Red Book Series",
    publisher = "IAHS Press",
    number = "327",
    pages = "144--150",
    editor = "Liebscher, {Hans-J{\"u}rgen } and Clarke, {Robin } and Rodda, {John } and Schultz, {Gert } and Schumann, {Andreas } and Ub, {Lucio }",
    booktitle = "Role of Hydrology in Water Resources Management",

    }

    Adeloye, A 2009, Integrated water resources management: development of data parsimonious models for reservoir planning. in H-J Liebscher, R Clarke, J Rodda, G Schultz, A Schumann & L Ub (eds), Role of Hydrology in Water Resources Management. vol. 327, IAHS Red Book Series, no. 327, IAHS Press, pp. 144-150, UNESCO/IAHS International Symposium on The Role of Hydrology in Water Resources Management, Isle of Capri, Naples, Italy, 14/10/08.

    Integrated water resources management : development of data parsimonious models for reservoir planning. / Adeloye, Adebayo.

    Role of Hydrology in Water Resources Management. ed. / Hans-Jürgen Liebscher; Robin Clarke; John Rodda; Gert Schultz; Andreas Schumann; Lucio Ub. Vol. 327 IAHS Press, 2009. p. 144-150 (IAHS Red Book Series; No. 327).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    TY - GEN

    T1 - Integrated water resources management

    T2 - development of data parsimonious models for reservoir planning

    AU - Adeloye, Adebayo

    PY - 2009

    Y1 - 2009

    N2 - Data parsimonious models are developed which offer the realistic possibility for reservoir storage-yield-reliability (S-Y-R) planning analysis at ungauged sites. One of the models was based on multiple linear regression analysis and the second set of models were designed using artificial neural networks (ANNs); both models use input variables comprising runoff summary statistics, e.g. the CV of annual runoff, and reservoir systems variables such as the demand and reliability index. The models performed satisfactorily when tested using independent data sets not utilised during their development. Finally, algorithms for obtaining the runoff summary statistics at ungauged sites are presented. Copyright © 2009 IAHS Press.

    AB - Data parsimonious models are developed which offer the realistic possibility for reservoir storage-yield-reliability (S-Y-R) planning analysis at ungauged sites. One of the models was based on multiple linear regression analysis and the second set of models were designed using artificial neural networks (ANNs); both models use input variables comprising runoff summary statistics, e.g. the CV of annual runoff, and reservoir systems variables such as the demand and reliability index. The models performed satisfactorily when tested using independent data sets not utilised during their development. Finally, algorithms for obtaining the runoff summary statistics at ungauged sites are presented. Copyright © 2009 IAHS Press.

    KW - Artificial neural networks

    KW - Multiple regression

    KW - Over-year capacity

    KW - Sequent peak algorithm

    KW - Storage-yield-reliability

    KW - Ungauged sites

    KW - Within-year capacity

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    M3 - Conference contribution

    SN - 9781901502947

    VL - 327

    T3 - IAHS Red Book Series

    SP - 144

    EP - 150

    BT - Role of Hydrology in Water Resources Management

    A2 - Liebscher, Hans-Jürgen

    A2 - Clarke, Robin

    A2 - Rodda, John

    A2 - Schultz, Gert

    A2 - Schumann, Andreas

    A2 - Ub, Lucio

    PB - IAHS Press

    ER -

    Adeloye A. Integrated water resources management: development of data parsimonious models for reservoir planning. In Liebscher H-J, Clarke R, Rodda J, Schultz G, Schumann A, Ub L, editors, Role of Hydrology in Water Resources Management. Vol. 327. IAHS Press. 2009. p. 144-150. (IAHS Red Book Series; 327).