The Uniformization of Annual Maximum 1・2・3 Day Precipitations and its Nonstationary Frequency Analysis

本研究通过使用统一的年度最大值1 - 2 - 3天预测进行操作，进行非静态频率分析。研究结果的摘要如下：1。接近参数时间系列（1）1964年至1992年29年前、台风、克隆和非分离的年度最大1、2和3天预测是长野、松本、伊达、苏瓦和卡鲁泽站使用的，如真实数据。这是一个不固定的时间序列，它是不固定的。（2） When time expresses t， Gumbel distribution， which is assumed as the population distribution， has the nonstationary scale parameter a （t） and location parameter b （t）。这些参数的时间序列被移动了5年的部分数据（它被称为参数时间序列）被周期分量和趋势分量近似。（3） The nonstationary parameter time series of Gumbel distribution were approximated by the logistic curve similarly. 2。非稳态液压变量的估计（1）使用参数时间系列中的第一组液压变量的计算。（2）已估计，以及水文变量的时间系列已绘制。这是不稳定的。（2）使用参数时间序列中的参数时间序列中的水学变量。（3）已估计，以及水文变量的时间序列相似地绘制。这是一个非政府组织。对参数时间系列稳定性的测试在本研究中移动的部分数据的长度为5年。这一稳定性是通过模拟进行的。结果表明，在5年内移动部分数据并没有给出参数时间序列的充分估计值。

This study put in operation the nonstationary frequency analysis by using the uniformized annual maximum 1・2・3 day precipitations. The summary of research results is as follows.1. The approximation of parameter time series(1) The annual maximum 1・2・3 day precipitations of front, typhoon, cyclone and non-separation for 29 years from 1964 to 1992 were used in Nagano, Matsumoto, Iida, Suwa and Karuizawa stations as real data. These precipitation time series had the nonstationarity.(2) When time expresses t, Gumbel distribution, which is assumed as the population distribution, has the nonstationary scale parameter a (t) and location parameter b (t). The time series of these parameters obtained by 5 year moving partial data (it is called parameter time series) were approximated by the periodic component and the trend component.(3) The nonstationary parameter time series of Gumbel distribution were approximated by the logistic curve similarly.2. The estimation of nonstationary hydrological variable(1) The hydrological variables of exceedance by using the parameter time series in 1.(2) were estimated, and the time series of hydrological variable were drawn. It had the nonstationality.(2) The hydrological variables of exceedance by using the parameter time series in 1.(3) were estimated, and the time series of hydrological variable were drawn similarly. It had the nonstationality too.3. The examination of the stability of parameter time seriesThe length of moving partial data was 5 years in this study. This stability was examined by simulation. The result said that 5 year moving partial data did not give the sufficient estimated value of parameter time series.