Local Polynomial–Based Flood Frequency Estimator for Mixed Population
Publication: Journal of Hydrologic Engineering
Volume 15, Issue 9
Abstract
Floods are often generated by more than one physical mechanism, e.g., rainfall and snowmelt. Consequently, traditional flood frequency methods that use a single distribution may not adequately describe the observed flood variability. Mixed distribution models have been proposed but they have two major drawbacks when applied to observed data: (1) determining the appropriate number of components or flood mechanisms and (2) identifying the probability distribution to be used for each component. Further, available flood data are often not sufficient for detecting mixture populations. As a result, mixed-distribution models can be difficult to apply in practice. In this paper we present a nonparametric approach based on local polynomial regression for estimating a flood quantile function that is data driven, flexible, and can capture any arbitrary features present in the data, alleviating the drawbacks of the traditional methods. We applied the proposed method to a suite of synthetic data from mixture of conventional distributions and to flood records that exhibit mixed population characteristics from Gila River basin of southeast and central Arizona. It is found that the proposed method provides a better fit to both the synthetic and historical data. Although the proposed method is presented in the context of mixed population flood frequency estimation, the data-driven nature of the method lends itself as a simple, robust, and attractive alternative to traditional flood frequency estimation.
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Acknowledgments
The first writer thanks Royal Irrigation Department, Thailand, for their support. Partial support for the second and third writers from National Science Foundation through Grant No. NSFEAR 9973125 is thankfully acknowledged. We thank the reviewers and the associate editor for insightful comments that greatly improved the paper.
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Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 15 • Issue 9 • September 2010
Pages: 680 - 691
Copyright
© 2010 ASCE.
History
Received: Oct 13, 2008
Accepted: Mar 11, 2010
Published online: Mar 16, 2010
Published in print: Sep 2010
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