A generalized Grubbs‐Beck test statistic for detecting multiple potentially influential low outliers in flood series. Issue 8 (19th August 2013)

• Record Type: Journal Article
• Authors: Cohn, T. A.; England, J. F.; Berenbrock, C. E.; Mason, R. R.; Stedinger, J. R.; Lamontagne, J. R.
• Is Part Of: Water resources research. Volume 49:Issue 8(2013:Aug.)
• Page Start: 5047
• Page End: 5058
• Publication Date: 2013-08-19
• Subjects: Hydrology -- Periodicals; 333.91
• DOI: 10.1002/wrcr.20392
• Languages: English
• ISSNs: 0043-1397

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>[1] The 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.</p> </abstract>