Assessment of the Significance of Sample Serial Correlation by the Bootstrap Test

This article proposes to use the computer-based bootstraptechnique to test the significance of the lag-k sampleserial correlation coefficient (r _k) of a time series.The bootstrap approach is free of sample distribution types, freeof restrictive assumptions, and easy to understand and implement. Monte Carlo simulation indicates that the bootstrap test has thesame power as the conventional parametric test for assessing thesignificance of a lag-one serial correlation coefficient (r ₁). The usefulness of the bootstrap test is demonstrated by applying it to assess the significance of r _k of the annual mean flow data of twenty pristine river basins in Ontario, Canada.     

基于Mann—Kendall检验的嘎呀河流域降水变化趋势及突变分析

基于Mann—Kendall检验方法,时嘎呀河流域降水量数据进行分析,发现年降水量总体呈现下降趋势,在研究时段内年径流量各雨量站均存在突变点,就流域而言．1985年为整个流域降水量的突变点。汛期降水量整体呈现下降趋势,非汛期降水量整体呈现上升趋势,老庙、天桥岭、汪清、仲坪和西大坡站汛期降水量变化对年降水量变化具有决定性作用。该流域汛期降水量突变点为1982年,非汛期无明显突变点。