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Low Flow Frequency Analysis Using Bayesian MCMC method

Congress: 2008
Author(s):
BK21 Safe and Sustainable Infrastructure Research Post-Doc. course

Keyword(s): Uncertainty, Bayesian MCMC, MLE, Low flow frequency analysis, Prior distribution, Weibull distribution
AbstractThis study uses the Bayesian Markov Chain Monte Carlo(MCMC) method with and maximum likelihood estimation(MLE) method using a quadratic approximation to perform the low flow frequency analysis using a two-parameter Weibull distribution. The two types of prior distributions, a non-data-based distribution and data-based distribution using regional information collected from neighbouring stations, are used to establish a posterior distribution. Eight case studies using the synthetic data with a sample size of 100, generated from two-parameter Weibull distribution,are performed to compare with results of analysis using MLE and Bayesian MCMC. These examples illustrate the advantages of Bayesian MCMC and the limitation of MLE based on a quadratic approximation. From the point of view of uncertainty analysis, Bayesian MCMC is more effective than MLE using a quadratic approximation when the sample size is small.
2011 IWRA - International Water Resources Association office@iwra.org - http://www.iwra.org - Admin