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A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series

Water Resources Research

By:
, , , , ,
DOI: 10.1002/wrcr.20392

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Abstract

he Grubbs-Beck test is recommended by the federal guidelines for detection of low outliers in flood flow frequency computation in the United States. This paper presents a generalization of the Grubbs-Beck test for normal data (similar to the Rosner (1983) test; see also Spencer and McCuen (1996)) that can provide a consistent standard for identifying multiple potentially influential low flows. In cases where low outliers have been identified, they can be represented as “less-than” values, and a frequency distribution can be developed using censored-data statistical techniques, such as the Expected Moments Algorithm. This approach can improve the fit of the right-hand tail of a frequency distribution and provide protection from lack-of-fit due to unimportant but potentially influential low flows (PILFs) in a flood series, thus making the flood frequency analysis procedure more robust.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series
Series title:
Water Resources Research
DOI:
10.1002/wrcr.20392
Volume
49
Issue:
8
Year Published:
2013
Language:
English
Publisher:
Wiley
Contributing office(s):
Water Resources Division
Description:
12 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Water Resources Research
First page:
5047
Last page:
5058