Technical Papers
Oct 26, 2013

Quantifying the Uncertainty of Design Floods under Nonstationary Conditions

Publication: Journal of Hydrologic Engineering
Volume 19, Issue 7

Abstract

Estimating design quantiles for extreme floods in river basins under nonstationary conditions is an emerging field. Nonstationarities could arise from a variety of human and natural factors such as urbanization and climate change. Concepts of return period, design quantile (return level), and risk have already been developed for situations in which increasing or decreasing trends and abrupt shifts in extreme events are present. Because of limited data records, sampling variability, model errors, and the errors in projections into the future, significant uncertainties in the estimates of design floods of future projects will arise. To address the issue of uncertainty resulting from limited sample size of the observations, three methods have been developed for computing confidence intervals for the design quantile corresponding to a desired return period under a nonstationary framework, including (a) delta, (b) bootstrap, and (c) profile likelihood methods. These methods have been developed assuming a generalized extreme value distribution with nonstationary parameters. The applicability and comparison of the proposed methods for determining the confidence interval of quantiles have been demonstrated by using the annual flood maxima of the Assunpink Creek in New Jersey. The delta method, with numerically derived local derivatives, and the approximate bootstrap can be computationally efficient. The profile likelihood method, which is known to be more accurate, is quite burdensome computationally but provides more realistic asymmetric confidence intervals.

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Acknowledgments

The writers acknowledge P2C2, Multicentury Streamflow Records Derived from Watershed Modeling and Tree Ring Data, in addition to the National Science Foundation (ATM-0823480). We thank Dr. D. Cooley for his valuable suggestions.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 19Issue 7July 2014
Pages: 1438 - 1446

History

Received: Jul 6, 2013
Accepted: Oct 24, 2013
Published online: Oct 26, 2013
Discussion open until: Mar 26, 2014
Published in print: Jul 1, 2014

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Jayantha Obeysekera, M.ASCE [email protected]
Chief Modeler, Hydrologic and Environmental Systems Modeling, South Florida Water Management District, 3301 Gun Club Rd., West Palm Beach, FL 33406 (corresponding author). E-mail: [email protected]
Jose D. Salas, M.ASCE [email protected]
Professor Emeritus, Dept. of Civil and Environmental Engineering, Colorado State Univ., Fort Collins, CO 80523. E-mail: [email protected]

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