Development of a large flood regionalisation model considering spatial dependence : application to ungauged catchments in Australia

Khaled Haddad, Ataur Rahman

Research output: Contribution to journalArticlepeer-review

Abstract

Estimation of large floods is imperative in planning and designing large hydraulic structures. Due to the limited availability of observed flood data, estimating the frequencies of large floods requires significant extrapolation beyond the available data. This paper presents the development of a large flood regionalisation model (LFRM) based on observed flood data. The LFRM 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. The LFRM is enhanced by adding a spatial dependence model, which accounts for the net information available for regional analysis. It was found that the LFRM, which accounts for spatial dependence and that pools 1 or 3 maxima from a site, was able to estimate the 1 in 1000 annual exceedance probability flood quantile with consistency, showing a positive bias on average (5–7%) and modest median relative errors (30–33%).
Original languageEnglish
Article number677
Number of pages16
JournalWater
Volume11
Issue number4
DOIs
Publication statusPublished - 2019

Open Access - Access Right Statement

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Keywords

  • Australia
  • flood forecasting
  • floods
  • hydraulic engineering
  • watersheds

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