资源环境科技发展态势分析平台

The detrended fluctuation analysis (DFA) and multifractal DFA, which can detect nonstationarities of time series with trends, were applied to study long-term persistence (LTP) and multifractal behaviour of 100 stations of daily precipitation and 145 stations of streamflow time series of Canada. Results show that all precipitation time series showed LTP at both small and large time scales, while streamflow time series generally showed nonstationary behaviour at small time scales and LTP at large time scales. The significant multifractal behaviour of Canadian precipitation and streamflow data can be accurately described by the universal multifractal model and the modified multiplicative cascade model. Precipitation over central Canada showed stronger multifractality than that of western and eastern Canada, while multifractality of streamflow data is less spatially homogeneous. The multifractal strength of precipitation is generally smaller than that of streamflow. Eleven (9) out of 100 precipitation stations showed positive (negative) temporal trends in parameters derived using the universal multifractal model, and about half of the stations whose streamflow data exhibited statistically significant abrupt change points showed a weakening or strengthening in the multifractal strength moving from the pre-change to the post-change periods. Differences in the multifractal strength between Canadian precipitation and streamflow data suggest that the persistence of streamflow was not only because streamflow is more autocorrelated than precipitation but also it is more consistently affected by human activities such as streamflow regulation.