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基于贝叶斯理论的水文不确定性分析研究进展

梁忠民 戴荣 李彬权

梁忠民, 戴荣, 李彬权. 基于贝叶斯理论的水文不确定性分析研究进展[J]. 水科学进展, 2010, 21(2): 274-281.
引用本文: 梁忠民, 戴荣, 李彬权. 基于贝叶斯理论的水文不确定性分析研究进展[J]. 水科学进展, 2010, 21(2): 274-281.
LIANG Zhong-min, DAI Rong, LI Bin-quan. A review of hydrological uncertainty analysis based on Bayesian theory[J]. Advances in Water Science, 2010, 21(2): 274-281.
Citation: LIANG Zhong-min, DAI Rong, LI Bin-quan. A review of hydrological uncertainty analysis based on Bayesian theory[J]. Advances in Water Science, 2010, 21(2): 274-281.

基于贝叶斯理论的水文不确定性分析研究进展

基金项目: 国家重点基础研究发展计划(973)资助项目(2007CB714104);国家自然科学基金资助项目(50779013);教育部博士点基金资助项目(20070294018)
详细信息
    作者简介:

    梁忠民(1962- ),男,辽宁凤城人,教授,博士生导师,主要从事水文及水资源方面研究.E-mail:zmliang@hhu.edu.cn

  • 中图分类号: P333.6;G353.11

A review of hydrological uncertainty analysis based on Bayesian theory

Funds: The study is financially supported by the NationalBasic Research Program of China (No.2007CB714104) and the Nationa.Natu-ra.Science Foundation of China (No.50779013)
  • 摘要: 水文过程受众多自然和人为因素影响,决定了其变化的极端复杂性,表现为确定性的动态规律与不确定性的统计规律共存。水文不确定性分析的理论和方法在认识水文规律中发挥着重要作用,其中贝叶斯作为一种主要理论方法在水文水资源相关问题的研究中得到了较广泛的应用。本文评述了贝叶斯理论在水文频率分析、水文预报、确定性和不确定性方法耦合等研究中的进展,对基于贝叶斯理论的水文不确定性重点研究内容进行了展望。
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  • 收稿日期:  2009-01-18
  • 刊出日期:  2010-03-25

基于贝叶斯理论的水文不确定性分析研究进展

    基金项目:  国家重点基础研究发展计划(973)资助项目(2007CB714104);国家自然科学基金资助项目(50779013);教育部博士点基金资助项目(20070294018)
    作者简介:

    梁忠民(1962- ),男,辽宁凤城人,教授,博士生导师,主要从事水文及水资源方面研究.E-mail:zmliang@hhu.edu.cn

  • 中图分类号: P333.6;G353.11

摘要: 水文过程受众多自然和人为因素影响,决定了其变化的极端复杂性,表现为确定性的动态规律与不确定性的统计规律共存。水文不确定性分析的理论和方法在认识水文规律中发挥着重要作用,其中贝叶斯作为一种主要理论方法在水文水资源相关问题的研究中得到了较广泛的应用。本文评述了贝叶斯理论在水文频率分析、水文预报、确定性和不确定性方法耦合等研究中的进展,对基于贝叶斯理论的水文不确定性重点研究内容进行了展望。

English Abstract

梁忠民, 戴荣, 李彬权. 基于贝叶斯理论的水文不确定性分析研究进展[J]. 水科学进展, 2010, 21(2): 274-281.
引用本文: 梁忠民, 戴荣, 李彬权. 基于贝叶斯理论的水文不确定性分析研究进展[J]. 水科学进展, 2010, 21(2): 274-281.
LIANG Zhong-min, DAI Rong, LI Bin-quan. A review of hydrological uncertainty analysis based on Bayesian theory[J]. Advances in Water Science, 2010, 21(2): 274-281.
Citation: LIANG Zhong-min, DAI Rong, LI Bin-quan. A review of hydrological uncertainty analysis based on Bayesian theory[J]. Advances in Water Science, 2010, 21(2): 274-281.
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