A new flood regionalisation model for large flood estimation in Australia

Khaled Haddad, Md. Jalal Uddin, Ataur Rahman, George Kuczera, Erwin Weinmann

    Research output: Chapter in Book / Conference PaperConference Paperpeer-review

    Abstract

    Estimation of large to rare floods is needed in the design of major water infrastructure such as large bridges, weirs and dam spillways. This paper presents a simple Large Flood Regionalisation Model (LFRM) which is relatively easy to apply in practice. The proposed method assumes that the maximum observed flood data over a large number of sites in a region can be pooled together by accounting for the at-site variations in the mean and coefficient of variation (CV) and inter-station correlation among the flood series data. For application of the LFRM to the ungauged catchment case, prediction equations need to be developed. In this study, a generalised least squares regression (GLSR) combined with the region-of-influence (ROI) approach is used for developing the prediction equations for the mean and CV of the annual maximum flood series as a function of easily obtainable catchment characteristics. The LFRM is developed and tested in this paper using data from 626 catchments across the Australian continent.
    Original languageEnglish
    Title of host publicationConference Proceedings. Vol. 2, SGEM 2011: 11th International Multidisciplinary Scientific Geoconference: Modern Management of Mine Producing, Geology and Environmental Protection: 20-25 June 2011, Bulgaria
    PublisherStef92 Technology
    Pages761-768
    Number of pages8
    Publication statusPublished - 2011
    EventInternational Multidisciplinary Scientific GeoConference -
    Duration: 20 Jun 2011 → …

    Publication series

    Name
    ISSN (Print)1314-2704

    Conference

    ConferenceInternational Multidisciplinary Scientific GeoConference
    Period20/06/11 → …

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