Record Display for the EPA National Library Catalog

RECORD NUMBER: 36 OF 407

OLS Field Name OLS Field Data
Main Title Computer Program for Statistical Analysis of Annual Flood Data by the Log-Pearson Type III Method.
Author Bower, C. Edward ; Pabs, Arthur F. ; Larso, Steven P. ;
CORP Author Minnesota Univ., Minneapolis. Water Resources Research Center.
Year Published 1971
Report Number WRRC-Bull-39; OWRR-A-020-MINN; 13805,; A-020-MINN(2)
Stock Number PB-203 422
Additional Subjects ( Floods ; Computer programming) ; Water flow ; Frequency distribution ; Computer programs ; FORTRAN ; Probability distribution functions ; Statistical analysis ; Mathematical models ; FORTRAN 4 programming language ; FLOOD computer program ; Computerized simulation
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
NTIS  PB-203 422 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 06/23/1988
Collation 31p
Abstract
The Federal Water Resources Council has recommended the adoption of the log-Pearson Type III method of establishing flood flow frequencies. The computer program developed in this study was written in Fortran IV language to facilitate log-Pearson Type III method computations. Annual floods are sorted in decreasing magnitude and then logarithms, mean, standard deviation and skewness of the logarithms are computed. The magnitude of the 100, 50, etc., year flood are determined with the aid of tables. The initial computer printout consists of sorted values of the floods, empirical values of recurrence interval and probability, and the logarithms of the floods. Application of the method to selected streams in the United States indicates that difficulties may be encountered when a given set of data contains one or more very low floods or outliers. The log-Pearson Type III distribution appears to have a substantial advantage over the Gumble and log-normal distributions that have been used for flood frequency analysis because it can be used for data having either a plus or a minus skewness. Also, it reduces to the log-normal distribution for zero skewness where the data fit this distribution. However, it will require a data screening procedure and sufficient use to indicate desirable restrictions on skewness values for short records and perhaps for various regions. (Author)