Modified weighted function method with the incorporation of historical floods into systematic sample for parameter estimation of Pearson type three distribution
Modified weighted function method with the incorporation of historical floods into systematic sample for parameter estimation of Pearson type three distribution
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DOI：
10.1016/j.jhydrol.2015.05.023
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发表时间：
2015-08
影响因子：
6.4
通讯作者：
Jun Wang;Zhongmin Liang;Yiming Hu;Dong Wang
中科院分区：
文献类型：
--
作者：
Jun Wang;Zhongmin Liang;Yiming Hu;Dong Wang
将历史洪水和古植被信息转化为系统的观测数据（即简单样本），是丰富数据集、提高参数估计精度，进而提高水文频率分析可靠性的非常有用的方法。本文给出了在非简单样本下（在系统记录的样本中加入历史洪水资料）用修正加权函数（MWF）法估计皮尔逊三型分布（PE 3）参数的公式，称为MWFIHF，从而使MWF法适用于非简单样本。利用蒙特卡罗方法模拟了大量的非简单样本，研究了MWFIHF的统计特性。结果表明，所提出的MWFIHF公式是令人满意的。此外，将MWFIHF的结果与原始加权函数（WF）和线性矩（LM）的结果进行了比较。结果表明，MWFIHF在统计无偏性和有效性方面明显上级WF，略优于LM。这三种方法也被用来分析在中国各地的26个站点收集的洪水极值数据。它还表明，MWFIHF非常适合大多数这些真实的洪水极端事件。© 2015 Elsevier BV版权所有。
Incorporating the historical flood and paleoflood information to systematical observed data (ie simple sample) is extremely useful approach for enriching the datasets and improving the accuracy of parameter estimation, in turn to improve the reliability of hydrological frequency analysis. In this paper, the formulas for using Modified Weighted Function (MWF) method to estimate parameters of Pearson Type Three Distribution (PE3) in term of non-simple sample (with the incorporation of historical flood information to systematically recorded sample) are developed, called as MWFIHF, which makes MWF method available for non-simple sample. Monte Carlo experiment is carried out to simulate a large number of non-simple samples upon which statistical properties of MWFIHF are investigated. The results show that the proposed formulas for MWFIHF are satisfactory. Besides, the results of MWFIHF are compared to that of the original Weighted Function (WF) and Linear moments (LM). It indicates that MWFIHF is obviously superior to WF and slightly better than LM in terms of statistical unbiasness and effectiveness. These three approaches are also used to analyze flood extremes data collected at 26 gauges around China. It also demonstrates that, MWFIHF fits well to most of these real flood extremes events.© 2015 Elsevier BV All rights reserved.