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Long-term periodic structure and seasonal-trend decomposition of water level in Lake Baiyangdian, Northern China

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Abstract

Water level, as an intuitive factor of hydrologic conditions, is of great importance for lake management. In this study, periodic structures of water level and its fluctuations in Lake Baiyangdian are analyzed based on wavelet analysis and seasonal-trend decomposition using local error sum of squares (STL). Data of monthly time series are divided into three types with emphasis on anthropogenic influence from water allocation. It is found that intra-annual characteristics of water level fluctuations are the common periodic structures. Water allocation alters the periodic structures by decreasing and weakening the oscillations of water level, compared with the slight effects of natural hydrologic water supplies and short-term climate changes. An irregular water level decline and short-term oscillation with irregular periodicity are deduced from seasonal-trend decomposition analysis using STL. With seasonality depicted monthly, the influence of water allocation implies irregular oscillations with high-frequency components, especially for monthly changes. The water level fluctuations are influenced by seasonal changes, as demonstrated by three types of time series. The impacts of water allocation on seasonality show the differences with continuous single-peak oscillations representing no influences and continuous double-peak oscillations representing frequent influences. Furthermore, the accumulation of water allocation shows a slight rising trend in average monthly level fluctuations over the last several years. The study helps understand periodic structures and long-term trend changes of water level fluctuations, which will facilitate lake management of Lake Baiyangdian.

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Acknowledgments

This research was financially supported by the National Water Pollution Control Major Project of China (No. 2008ZX07209–009), The national Science Foundation for Innovative Research Group (No. 51121003), and the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT0809). We thank C. Torrence and G. Compo for assistance in the Wavelet analysis and to P. Wessa for guiding in algorithm programming of Decomposition by Loess.

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Authors and Affiliations

  1. Key Laboratory for Water and Sediment Sciences of Ministry of Education, School of Environment, Beijing Normal University, No. 19 Xinjiekouwai Street, Haidian District, Beijing, 100875, China

    F. Wang, X. Wang & Z. F. Yang

  2. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China

    X. Wang, Y. Zhao & Z. F. Yang

  3. School of Physical Education, Shanxi University, Taiyuan, 030006, China

    F. Wang

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  1. F. Wang
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  3. Y. Zhao
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  4. Z. F. Yang
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Correspondence to X. Wang.

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Wang, F., Wang, X., Zhao, Y. et al. Long-term periodic structure and seasonal-trend decomposition of water level in Lake Baiyangdian, Northern China. Int. J. Environ. Sci. Technol. 11, 327–338 (2014). https://doi.org/10.1007/s13762-013-0362-5

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  • DOI: https://doi.org/10.1007/s13762-013-0362-5

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