Technical Papers
Oct 6, 2021

Revisiting the Application of Halphen Distributions in Flood Frequency Analysis

Publication: Journal of Hydrologic Engineering
Volume 26, Issue 12

Abstract

Flood frequency analysis is the foundation for hydrological and hydraulic design, and fundamental to frequency analysis is the selection of a suitable probability distribution. This study therefore revisits the Halphen frequency distribution family, with parameters estimated by the maximum likelihood estimation (MLE) method and goodness-of-fit evaluated by the Kolmogorov-Smirnov (KS) test. Besides revising the Halphen family, this study (1) proposes the study of kurtosis to assist the selection of a probability density function; (2) applies the kernel density function as the parent distribution function to evaluate flood risk (using 100-year event as an example); and (3) evaluates the mixed Halphen distribution for the heavy-tailed peak flow falling into the Halphen-B region. Using 198 peak flow datasets selected from 18 hydrologic regions in 48 states in the continental US, the study showed that: (1) Halphen-A/Halphen-B distributions were the preferred distributions for 190 datasets; (2) the moment-ratio diagram was found to be a reliable indicator for selecting the appropriate distribution; (3) kurtosis may be a tool to assist with the distribution selection; (4) comparison and risk assessment indicated that the identified Halphen distributions may properly model the flood frequency distribution; and (5) overall, the study validated the applicability of Halphen distributions for flood frequency analysis.

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Data Availability Statement

Some or all of the data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

References

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 26Issue 12December 2021

History

Received: Apr 7, 2021
Accepted: Jul 15, 2021
Published online: Oct 6, 2021
Published in print: Dec 1, 2021
Discussion open until: Mar 6, 2022

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Authors

Affiliations

Lan Zhang, Ph.D., M.ASCE [email protected]
Dewberry, 8401 Arlington Blvd., Fairfax, VA 22031 (corresponding author). Email: [email protected]
Professor, Dept. of Biological and Agricultural Engineering, Zachry Dept. of Civil Engineering, Texas A&M Univ., College Station, TX 77843-2117. ORCID: https://orcid.org/0000-0003-1299-1457. Email: [email protected]

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