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中文摘要：
文章基于马尔可夫链（McMc）采样法，耦合地下水数值模拟的MODFLOW软件，提出了贝叶斯方法，用于水文地质参数识别这一复杂的非线性优化问题。采取单分量自适应Metropolis（SCAM）采样算法并加入了权重因子，从而大大提高了该方法解决高维参数问题的效率。通过两个实例研究，验证了该方法具有独特的寻优性能和效率。结果表明，贝叶斯方法适用于复杂地下水问题的参数识别，并体现出了出色的全局寻优性。
英文摘要：
The Bayesian method is introduced into the field of groundwater to identify hydrogeological parameters, which is usually a complicated nonlinear problem. A Bayesian hydrogeological parameter identification algorithm is proposed based on the MCMC sampler which is eoupled with the groundwater modeling software, Modflow. The efficiency of identifying high dimensional parameters is greatly improved by using the SCAM sampler and a weighting factor. Two examples are presented to illustrate the distinctive optimization performance of this algorithm. The results indicate that the proposed algorithm is capable for complex groundwater problem and shows outstanding advantage of global optimization.
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