| 摘要: |
| 【目的】对条件概率模型在非一致性水文序列频率计算中的应用进行研究，为变化环境下的水文频率分析提供依据。【方法】基于条件概率模型，以渭河流域林家村、张家山和状头3个具有跳跃变异的水文站年平均流量系列为研究对象，选择两参数对数正态分布、三参数对数正态分布、Gumbel分布和P-Ⅲ型分布4种分布模型，采用模拟退火粒子群算法进行参数估计，以效率系数R2等指标进行拟合优度评价并选取最佳模型，最后采用学生化残差分析所选模型的合理性。【结果】3个水文站序列的理论频率曲线与经验点据配合的效率系数均高于0.96，最佳模型的学生化残差均服从标准正态分布，表明基于条件概率模型的计算结果合理可靠。【结论】条件概率模型的物理意义明确、理论严密、拟合效果较优，是一种对具有跳跃变异的非一致性水文序列进行频率分析的有效途径。 |
| 关键词: 条件概率模型 非一致性 水文序列 频率分析 跳跃变异 |
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| 基金项目:国家自然科学基金项目（51179160）；国家自然科学基金青年科学基金项目（51409222）；水利部公益性行业科研经费专项（201301075）；中央高校基本科研业务费专项（2014YB048）；西北农林科技大学博士科研启动基金项目（2013BSJJ101） |
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| Application of conditional probability model in frequency calculation of inconsistent hydrologic series |
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LI Lingjie,KANG Yan,SONG Songbai,et al
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| Abstract: |
| 【Objective】This study investigated the application of conditional probability model in frequency analysis of inconsistent hydrologic series to provide basis for hydrologic frequency analysis in a changing environment.【Method】The method based on conditional probability model was applied to analyze annual average discharge series with jump variation at three gauge stations of Linjiacun,Zhangjiashan and Zhuangtou in Wei River basin.Four hydrological frequency distribution curves including two-parameter lognormal distribution,three-parameter lognormal distribution,Gumbel distribution and P-Ⅲ distribution were selected and their parameters were estimated by simulated annealing-particle swarm algorithm.Indicators such as the efficiency coefficient R2 were adopted to evaluate the fitness of models and studentized residuals were analyzed for optimal model rationality.【Result】The efficiency coefficients of series at three gauge stations between theoretical and empirical frequencies all exceeded 0.96,and the studentized residuals of optimal model obeyed the normal distribution.The results based on conditional probability model were reasonable and reliable.【Conclusion】With definitely physical significance,rigorous theory and better imitative effect,conditional probability model provides an effective way for frequency analysis of inconsistent hydrologic series. |
| Key words: conditional probability model inconsistent hydrologic series frequency analysis jump variation |
