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Streamflow simulation and skewness preservation based on the bootstrapped stochastic models
Authors:Byung Sik?Kim  author-information"  >  author-information__contact u-icon-before"  >  mailto:hydrokbs@orgio.net"   title="  hydrokbs@orgio.net"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Hung Soo?Kim,Byung Ha?Seoh
Affiliation:(1) Department of Civil Engineering, Inha University, Incheon, 402–751, Korea;(2) Department of Civil Engineering, Inha University, Incheon, 402–751, Korea;(3) Department of Civil Engineering, Inha University, Incheon, 402–751, Korea
Abstract:The stochastic model has been widely used for the simulation study. However, there was a difficulty in the reproduction of the skewness of observed series and so the stochastic model for the skewness preservation was appeared. While the skewness in the residuals of the stochastic model has been considered for the skewness preservation this study uses a random resampling technique of residuals from the stochastic models for the simulation study and for the investigation of the skewness coefficient. The main advantage of this resampling scheme, called the bootstrap method is that it does not rely on the assumption of population distribution and this study uses the combined model of the stochastic and bootstrapped models. The stochastic and bootstrapped stochastic (or combined) models are used for the investigations of skewness preservation and of the reproduction of probability density function between the simulated series. The models are applied to the annual and monthly streamflows of Yongdam site in Korea and Yakima river, Washington, USA for the streamflow simulation study then the statistics and probability density functions for the observed and simulated streamflows are compared. As the results the bootstrapped stochastic model reproduces the skewness and probability density function much better than the stochastic model. This evidences suggest that the bootstrapped stochastic model might be more appropriate than the stochastic model for the preservation of skewness and for simulation purposes of the series.
Keywords:Stochastic model  Resampling  Bootstrap method  Skewness
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