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
    Country/TerritoryItaly
    CityIsle of Capri, Naples
    Period14/10/0816/10/08

    Keywords

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

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