KWRRI Research Reports
The U. S. Geological survey recently used the method of residuals to delineate seven flood regions for the State of Kentucky. As an alternative approach, the FASTCLUS clustering procedure of the Statistical Analysis system (SAS) is used in this study to delineate five to six cluster regions in conjunction with statistical properties of the AMF series, like the coefficient of variation as estimated using method of L-moments, LCV, the parameters of the EVl and GEV flood frequency distributions, and the specific mean annual flood, QSP. For both cluster and USGS flood regions, regionalized flood frequency growth curves are developed and their performance evaluated using Monte Carlo simulation techniques. Flood regions are.then evaluated and compared ·using trends in the hydrological characteristics of important.variables, performance of the regionalized flood frequency growth curves, discriminant analysis and regression equations relating flood quantiles to watershed physical characteristics. Results show that the cluster regions are more distinguishable in terms of their flood characteristics than the USGS regions. The.regionalized flood frequency growth curves of the EVl and GEV model are more distinct for the cluster regions than the USGS regions, although their performance in terms of bias and RMSE are comparable. The standard errors associated with the regression equations, developed for predicting the EVl and GEV flood quantiles, are similar for cluster and USGS regions.
Digital Object Identifier (DOI)
The work upon which this report is based was supported in part by funds provided by the United States Department of the Interior, Washington, D.C., as authorized by the Water Resources Research Act of 1984. Public Law 98-242.
This research study was conducted under a USGS research grant awarded through the Kentucky Water Resources Research Institute, University of Kentucky, Lexington, Kentucky.
Bhaskar, Nageshwar Rao; O'Connor, Carol Alf; Myers, Harold Andrew; and Puckett, William Paul, "Regionalization of Flood Data Using Probability Distributions and Their Parameters" (1989). KWRRI Research Reports. 33.