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Complexity research of regional groundwater depth series based on multiscale entropy: a case study of Jiangsanjiang Branch Bureau in China

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Abstract

To describe the complexity features of regional groundwater depth series, using Jiansanjiang Branch Bureau in China as an example, the complexity of monthly groundwater depth series were analyzed with the multiscale entropy (MSE) method and the complexity spatial distribution maps of 15 farms and their subarea were drawn by GIS technology. The results of this paper show that the complexities of monthly groundwater depth series have the following characteristics: southern area is the most complicated, middle area is the least complicated, northern area is in the middle of these two. Human production activities are the main driving factor causing complexity of regional groundwater depth series. The multi-dimensional variation of groundwater depth status can be reflected by the MSE method which is constant and accurate, and needs less data. The research achievements reveal the complexity and areal variation of local groundwater resources system, and provide the scientific basis for rationally utilizing and developing groundwater resources in Jiansanjiang Branch Bureau and even in the whole Sanjiang Plain in China.

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References

  • Bates JE, Shepard HK (1993) Measuring complexity using information fluctuation. Phys Lett A 6:416–425

    Article  Google Scholar 

  • Cao L, Yu GR (2011) Study on chaos characters of Yangtze River daily flow time series: union confirmation of embedded dimension and embedded lag time in phase space. Water Conserv Sci Technol Econ 7:9–11

    Google Scholar 

  • Costa MD, Goldberger AL, Peng CK (2002) Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett 89:068102-1–068102-4

    Google Scholar 

  • Costa MD, Peng CK, Goldberger AL (2008) Multiscale analysis of heart rate dynamics: entropy and time irreversibility measures. Cardiovasc Eng 2:88–93

    Google Scholar 

  • Feng GZ, Song SB, Li PC (1998) A statistical measure of complexity in hydrological systems. J Hydraul Eng 11:76–81

    Google Scholar 

  • Jiang L, Ai B, Qi T (2010) Application of fractal theory to software complexity. J Comput Appl 10:2730–2734

    Google Scholar 

  • Li ZW, Zhang YK (2008) Multi-scale entropy analysis of Mississippi River flow. Stoch Env Res Risk Assess 4:507–512

    Article  Google Scholar 

  • Liu MM, Ai LM (2011) Application of multi-scale entropy for detecting driving fatigue in EEG. Comput Technol Dev 8:209–212

    Google Scholar 

  • Liu HL, Huang H, Liu KB (2010) On the method of practical symbolic dynamics for EEG analysis. J Biomed Eng 2:407–410

    Google Scholar 

  • Liu XM, Wang SC, Zhao J (2011) Infrared image matching tracking algorithm based on image multi-scale entropy. Control Decis 5:768–772

    Google Scholar 

  • Sang YF, Wang D, Wu JC et al (2010) Quantitative characterization of complicated characteristics of hydrologic series. J China Hydrol 5(1–6):56

    Google Scholar 

  • Tong QY, Kong J, Xu JH (1998) New method of analyzing EEG complexity. Chin J Biomed Eng 3:222–226

    Google Scholar 

  • Xie ZM (2009) Multiscale entropy method for analysis of complex geophysical signals. Technol Earthq Disaster Prev 4:380–385

    Google Scholar 

  • Zhang L, Zou HJ, Guo WZ et al (2009) An intelligent fault diagnosis method based on multiscale entropy and SVMs. Lect Notes Comput Sci 5553:724–732

    Article  Google Scholar 

Download references

Acknowledgments

This study is supported by the National Natural Science Foundation of China (No. 41071053), Special Fund of China Postdoctoral Science Foundation (No. 201003410), Specialized Research Fund for the Doctoral Program of Higher Education of China (No. 20102325120009), Natural Science Foundation of Heilongjiang Province of China (No. C201026), Postdoctoral Scientific Research Start-up Fund of Heilongjiang Province of China (No. LBH-Q11154) and Doctoral Start-up Fund of Northeast Agricultural University of China (No. 2009RC37).

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Correspondence to Dong Liu.

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Liu, M., Liu, D. & Liu, L. Complexity research of regional groundwater depth series based on multiscale entropy: a case study of Jiangsanjiang Branch Bureau in China. Environ Earth Sci 70, 353–361 (2013). https://doi.org/10.1007/s12665-012-2132-y

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  • DOI: https://doi.org/10.1007/s12665-012-2132-y

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