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http://dx.doi.org/10.3741/JKWRA.2008.41.9.943

Identification of Uncertainty in Fitting Rating Curve with Bayesian Regression  

Kim, Sang-Ug (SNU BK21 SIR Group, Seoul National University)
Lee, Kil-Seong (Dept. of Civil and Environmental Engineering, Seoul National University)
Publication Information
Journal of Korea Water Resources Association / v.41, no.9, 2008 , pp. 943-958 More about this Journal
Abstract
This study employs Bayesian regression analysis for fitting discharge rating curves. The parameter estimates using the Bayesian regression analysis were compared to ordinary least square method using the t-distribution. In these comparisons, the mean values from the t-distribution and the Bayesian regression are not significantly different. However, the difference between upper and lower limits are remarkably reduced with the Bayesian regression. Therefore, from the point of view of uncertainty analysis, the Bayesian regression is more attractive than the conventional method based on a t-distribution because the data size at the site of interest is typically insufficient to estimate the parameters in rating curve. The merits and demerits of the two types of estimation methods are analyzed through the statistical simulation considering heteroscedasticity. The validation of the Bayesian regression is also performed using real stage-discharge data which were observed at 5 gauges on the Anyangcheon basin. Because the true parameters at 5 gauges are unknown, the quantitative accuracy of the Bayesian regression can not be assessed. However, it can be suggested that the uncertainty in rating curves at 5 gauges be reduced by Bayesian regression.
Keywords
discharge rating curve; uncertainty; Bayesian regression; t-distribution; heteroscedasticity; ordinary least square;
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Times Cited By KSCI : 2  (Citation Analysis)
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