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Development of a Large Flood Regionalisation Model Considering Spatial Dependence—Application to Ungauged Catchments in Australia

1
Environment and Infrastructure Division, Cumberland Council, Merrylands, NSW 2170, Australia
2
School of Computing, Engineering and Mathematics, Western Sydney University; Locked Bag 1797, Penrith NSW 2750, Australia
*
Author to whom correspondence should be addressed.
Water 2019, 11(4), 677; https://doi.org/10.3390/w11040677
Received: 12 February 2019 / Revised: 19 March 2019 / Accepted: 29 March 2019 / Published: 1 April 2019
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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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%). View Full-Text
Keywords: large floods; spatial dependence; Generalized Extreme Value; regional flood frequency analysis; ungauged catchments large floods; spatial dependence; Generalized Extreme Value; regional flood frequency analysis; ungauged catchments
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Haddad, K.; Rahman, A. Development of a Large Flood Regionalisation Model Considering Spatial Dependence—Application to Ungauged Catchments in Australia. Water 2019, 11, 677.

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