水文时间序列若干问题的研究

发布时间：2018-06-23 00:07

  本文选题：参数估计 + 非参数核估计　； 参考：《安庆师范大学》2016年硕士论文

【摘要】：水文时间序列是一个错综复杂的不确定性研究系统,它的主要研究内容有水文模拟、水文频率计算和水文预报等三大模块知识。本文在学习、总结和引用国内外学者对水文学统计理论研究的基础上,分析、对比、总结并在水文频率计算方面应用了参数估计和非参数估计两大类模型,而且应用时间序列相关模型以及水文模拟相关知识进行了水文预报。本文的研究内容和结论如下:参数估计的几大类方法对比分析及应用。水文水资源系统的参数估计方法有矩法、权函数法、概率权重法、线性矩法和适线法等;经过无偏性检验可知权函数法的无偏性最好,然后依次是线性矩法、概率权重法和常规矩法;且它们的稳健性能的排名分别为线性矩法、权函数法、概率权重法和常规矩法;另外,适线法适合在水文工程上的机器模拟;因此,我们用无偏性与稳健性都较好的线性矩法来估计皮尔逊Ⅲ型分布,进而求出其频率对应表。非参数核密度估计及应用。水文频率计算中非参数核估计无需假定总体分布类型,只需要利用最小二乘交叉验证法(简称LSCV法)求取恰当的窗宽以及恰当的核函数,便可求出水文频率密度函数。进而,由非参数核密度估计对长江安庆站52年的最大洪峰流量进行估计,得到其洪水频率函数,并与参数估计的结果进行对比,可知在总体分布类型不确定时用非参数法更适合,而确定时二者偏差不大,但参数法更具有针对性。时间序列分析法建模。针对长江安庆水文站1959年至2010年这52年间的历年月流量数据进行了季节调整以及趋势分解;并对其总流量数据进行了描述性时序分析、平稳性检验、模型判定,最终建立水文预报的ARMA模型;最后利用水文模拟中的蒙特卡洛法对该水文预报模型进行稳健性检验,可知模型可靠,可以用来对安庆的水文环境进行预报。
[Abstract]:Hydrological time series is a complicated uncertainty research system. Its main research contents include three modules: hydrological simulation hydrological frequency calculation and hydrological forecasting. On the basis of studying, summarizing and quoting domestic and foreign scholars' research on hydrological statistics theory, this paper analyzes, compares, sums up and applies two kinds of models, parameter estimation and non-parameter estimation, in hydrologic frequency calculation. Moreover, hydrological prediction is carried out by using time series correlation model and hydrologic simulation knowledge. The contents and conclusions of this paper are as follows: comparison and application of several methods for parameter estimation. The parameter estimation methods of hydrology and water resources system include moment method, weight function method, probability weight method, linear moment method and line fitting method, etc. The unbiased test shows that the weight function method is the best, followed by the linear moment method. The probability weight method and the regular rule method are ranked as linear moment method, weight function method, probability weight method and regular rule method respectively. In addition, the line fitting method is suitable for the machine simulation of hydrological engineering. We estimate Pearson type 鈪，

本文编号：2054825