Estimation of the Extreme Flow Distributions by Stochastic Models |
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Authors: | Yuanzhang Li K M Lal Saxena Shuzheng Cong |
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Institution: | (1) Allied Technology Group &, Walter Reed Army Inst. of Research, Washington, D.C 20307, USA;(2) Dept. Of Math. & Stat., University of Nebraska, Lincoln, NE, 68588;(3) National Weather Service, 11904 Crimson Lane, Silver Spring, MD, 20904 |
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Abstract: | The t-year event is a commonly used characteristic to describe the extreme flood peak in hydrological designs. The annual maximum series (AMS) and the partial duration series (PDS) are two basic approaches in flood analyses. In this paper, we first derive the distribution of the maximum extreme or the joint distribution of two or more maximum extremes from historical records based on a stochastic model, and then estimate statistical characteristics, including the t-year event, from the distribution. In addition to the two classical approaches (AMS and PDS), two additional approaches are proposed for estimating the unknown parameters in this paper. The first one uses two or more annual maximums (MAMS) as the sample to estimate the distribution of the maximum extremes. The second one uses multi-variate shock model to estimate the distribution of the maximum extremes for a multi-modal streamflow. The distribution of the extreme streamflow and the associated characteristics in the Bird Creek in Avant, Oklahoma, in the St. Johns River in Deland, Florida, and in the West Walker River in Coleville, California are estimated by using the stochastic model. To investigate further the performance of the estimation, the stochastic models based on AMS, MAMS and PDS related are also applied to the simulated data. The results show that the stochastic model and the related methods are reliable. |
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Keywords: | distribution of extremes multi-annual-maximum multi-variate-shock model stochastic model |
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