Accuracy Assessment of Peak Discharge Models
Publication: Journal of Hydrologic Engineering
Volume 10, Issue 1
Abstract
Goodness-of-fit statistics that accompany model calibration may not be good indicators of prediction accuracy. The difference between model calibration and validation accuracy has not been studied under the assumption that they are similar. Two methods of assessing prediction accuracy are compared. Split-sample testing and jackknifing are evaluated as a function of the sample size, the number of predictor variables, and the calibration accuracy. The relationship of split-sample testing is very sensitive to the sample size and the level of calibration accuracy. For small samples, split-sample testing is quite poor because of the loss of accuracy when the sample size is halved. The prediction accuracy decreases as the number of predictors increases because of the loss of degrees of freedom. Applications to regression analyses for a 10-year peak discharge prediction are provided. The results of an application to measured peak discharge data agree with simulation results. Future peak discharge studies should report both the calibration and jackknifing goodness-of-fit statistics.
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References
Dillow, J. J. A. (1996). “Technique for estimating magnitude and frequency of peak flows in Maryland.” WRI 95-4154, U.S. Geological Survey, Towson, Md.
Haan, C. T. (1977). Statistical methods in hydrology, Iowa State University Press, Ames, Iowa.
Helsel, D. R., and Hirsch, R. M. (1992). Statistical methods in water resources, Elsevier Science, Amsterdam, The Netherlands.
Hosking, J. R. M., and Wallis, J. R. (1997). Regional frequency analysis, Cambridge University Press, New York.
Jennings, M. E., Thomas, W. O., Jr., and Riggs, H. C. (1994). “Nationwide summary of U. S. Geological Survey regional regression equations for estimating magnitude and frequency of floods for ungauged sites, 1993.” WRI Rept. 94-4002, U.S. Geological Survey, Reston, VA.
Klinesmith, D. E. and McCuen, R. H. (2004). “Discharge and sediment rating curve accuracy.” J. Floodplain Manage., 4(1), 1–10.
McCarthy, P. J. (1976). “The use of balanced half-sample replication in cross-validation studies.” J. Am. Stat. Assoc., 44, 596–604.
McCuen, R. H. (1993). Microcomputer applications in statistical hydrology, Prentice-Hall, Upper Saddle River, N.J.
McCuen, R. H. (2003). Modeling hydrologic change: Statistical methods, Lewis∕CRC Press, Boca Raton, Fla.
McNemar, Q. (1969). Psychological statistics 4th Ed., Wiley, New York.
Miller, R. G., Jr. (1964). “A trustworthy jackknife.” Ann. Math. Stat., 35, 1594–1605.
Miller, R. G., Jr. (1974). “The jackknife—A review,” Biometrika, 61, 1–15.
Mosteller, F. and Tukey, J. W. (1977). Data analysis and regression, Addison–Wesley Reading, Mass.
Shao, J. and Tu, D. (1995). The jackknife and bootstrap, Springer, Amsterdam, The Netherlands.
Wainer, H. and Thissen, D. (1975). “When jackknifing fails (or does it?).” Psychometrika, 40, 113–114.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 10 • Issue 1 • January 2005
Pages: 16 - 22
Copyright
© 2004 ASCE.
History
Received: Dec 11, 2002
Accepted: Mar 28, 2004
Published online: Jan 1, 2005
Published in print: Jan 2005
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