A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series
Water Resources Research
By: T.A. Cohn, J.F. England, C. E. Berenbrock, R.R. Mason, J.R. Stedinger, and J.R. Lamontagne
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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.
| 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 |
| Google Analytic Metrics | Metrics page |