WIT Press


An Insight Into Flood Frequency For Design Floods

Price

Free (open access)

Paper DOI

10.2495/FRIAR080161

Volume

118

Pages

10

Page Range

155 - 164

Published

2008

Size

370 kb

Author(s)

M. Mohssen

Abstract

The maximum annual flood (MAF) series of peak flows have been commonly used in the literature to estimate the parameters of a statistical model in order to estimate design floods for the proper protection and management of flows during extreme events. The use of maximum annual flows restricts the size of the available sample to the number of available years of observed flows, and ignores the fact that flood events which are not the highest in some years, can be higher than the highest flows of other years. The partial duration flood (PDF) series, which includes flood events above a specified threshold, has been addressed in the literature as a more efficient alternative. A new relation between the return periods of the PDF and the MAF series have been derived based on the assumption that flood events are independent, without the need to assume that their arrival follows a Poisson process. The General Extreme Value (GEV) distributions, including the Gumbel as a special case, in addition to the Generalized Pareto (GP) distribution have been fitted and applied to the flood events of the Tokomairiro River, New Zealand. The use of the PDF series, with 115 flood events in 21 years, resulted in smoother and more homogeneous series, and produced higher design floods than the MAF series. The new derived equation for the relation between PDF and annual return periods resulted in smaller design floods for return periods up to 10 years, while design floods for higher return periods were almost the same as the values obtained from the available relation in the literature. Keywords: flood frequency, partial duration series, design floods, generalized extreme value, Generalized Pareto, extreme flows.

Keywords

flood frequency, partial duration series, design floods, generalized extreme value, Generalized Pareto, extreme flows.