Abstract
Precipitation is an important part of the hydrologic cycle, and its complexity is closely related to surface runoff and changing groundwater dynamics, which in turn influences the accuracy of precipitation forecasts. In this study, we used the Lempel–Ziv algorithm (LZA) and a multi-scaling approach to assess precipitation complexity for 1958–2011 by analyzing time series data from 28 gauging stations located throughout Jilin province, China. The spatial distribution of normalized precipitation complexity was measured by LZA, a symbolic dynamics algorithm, and by a multi-scaling approach, which is described by fractals. In addition, the advantages and limitations of these two methods were investigated. The results indicate that both methods are applicable and consistent for calculating precipitation complexity, and that the degree of relief is a primary factor controlling precipitation complexity in the mountainous area; in the plain terrain, however, the prominent influencing factor is climate.
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Acknowledgments
This study was funded by the National Nature Science Foundation of China (No. 41572216). The co-authors would like to express their appreciation to Dr. Chen S. M. for reviewing an early version of this manuscript and for his constructive suggestions.
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Zhang, Q., Liang, X., Fang, Z. et al. Complexity analysis of precipitation using the Lempel–Ziv algorithm and a multi-scaling approach: a case study in Jilin province, China. Stoch Environ Res Risk Assess 31, 1697–1707 (2017). https://doi.org/10.1007/s00477-016-1314-7
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DOI: https://doi.org/10.1007/s00477-016-1314-7