A RICp criterion for periodicity analysis of hydrological time series

Identification of periodicity in hydrological time series is important for understanding the complex variability of hydrological processes. Previous studies mainly focused on the comparison, improvement and development of different methods for the identification of periodicity. However, these methods have big subjectivity in the selection of significance levels, which may lead to pseudo-periodic components in the identification results. In this article, a new criterion called RICp (R for correlation coefficient, IC for information criterion, and subscript p for periodicity) is proposed to accurately identify periodic components in hydrological time series and evaluate their statistical significance. The RICp is based on the idea of Akaike information criterion, and it is established by consisting of a fitting accuracy index and an uncertainty measurement. The fitting accuracy index is based on the correlation coefficient, and the uncertainty measurement is based on the form of information entropy. Different synthetic time series, which are composed of multiple periodic components and Pearson-III noise data, are used to verify the superiority of the RICp method. The performance of RICp is compared with the moving correlation coefficient-based method for periodicity identification (MCCP), harmonic analysis method (HAM), and maximum entropy spectral analysis (MESA), by checking the accuracy and reliability of the identification results. The results suggest that in HAM and MCCP methods, more pseudo-periodic components are identified compared to other methods. Differently, the number of periodic components identified by MESA is less than the true value, as some significant periodic components can be missed. By comparison, the RICp performs the best among these four methods. The advantage of RICp is that it can describe the periodicity and also evaluate its statistical significance level. The RICp method is further applied to analyze the surface water resource time series in six secondary water resource regions in Southwest Rivers basin, by comparing with HAM and MESA. Results further verified the advantages of the RICp method developed. It also indicates that the runoff in the basin generally has a 9-year periodic pattern; the precipitation has the same periodicity as the runoff except Lancang River region, which can be attributed to the 11-year periodic cycle of the Indian Ocean monsoon.