Skip to main content
SpringerLink
Log in

Simulation and prediction of shallow groundwater depth in the North China Plain based on regional periodic characteristics

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

The North China Plain is the political and economic center of China, and it is also the area most seriously affected by groundwater exploitation. Therefore, it is crucial to model and predict groundwater levels in the North China Plain. In this study, using data from groundwater monitoring stations in the North China Plain from 2010 to 2018, wavelet analysis was applied to study the periodicity of shallow groundwater depths in the region, and a spectrum analysis model was established to simulate and predict the groundwater depth in the North China Plain. The results showed a strong correlation between the first significant period and the distance of the station from the Yellow River. The periodic characteristics obtained by the wavelet analysis were substituted into the spectrum analysis model. This improvement significantly increased the accuracy of the modeling results. Moreover, the application of the improved model showed that the groundwater depth in the North China Plain will increase the following year, except for most of Beijing and the coastal areas. Through the study, we understood the dynamic and periodic characteristics of the groundwater level, and proposed a combined method of wavelet analysis and spectrum analysis for groundwater level simulation and prediction, and these results have important guiding for the comprehensive development and protection of groundwater.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Cao G, Zheng C (2016) Signals of short-term climatic periodicities detected in the groundwater of North China Plain. Hydrol Process 30(4):515–533

    Google Scholar 

  • Chen B (1988) Groundwater dynamics and its prediction. Science Press, Beijing (in Chinese)

    Google Scholar 

  • Chen F, Hou J, Yu L, Liu J, Tang S, Ding Y, Liu J (2016) Analysis on the treatment of groundwater overdraft in China. Water Res Plan Des 11:3–7 (in Chinese)

    Google Scholar 

  • Cheng T, Shao J, Cui Y, Mo Z, Han Z, Li L (2014) Parallel simulation of groundwater flow in the North China Plain. J Earth Sci 25(6):1059–1066 (in Chinese)

    Article  Google Scholar 

  • Chiaudani A, Di Curzio D, Palmucci W (2017) Statistical and fractal approaches on long time-series to surface-water/groundwater relationship assessment: a central Italy alluvial plain case study. Water 9(11):850

    Article  Google Scholar 

  • Ebrahimi H, Rajaee T (2017) Simulation of groundwater level variations using wavelet combined with neural network, linear regression and support vector machine. Global Planet Change 148:181–191

    Article  Google Scholar 

  • Fei Y, Miao J, Zhang Z, Chen Z, Song H, Yang M (2009) Analysis on evolution of groundwater depression cones and its leading factors in North China Plain. Res Sci 31(3):394–399 (in Chinese)

    Google Scholar 

  • Feng H, Zhang G, Wang D, Yan M (2014) Analysis on driving forces for groundwater flow field evolution in Shijiazhuang Area in recent 50 years. J Hydraul Eng 45(02):180–186 (in Chinese)

    Google Scholar 

  • Garamhegyi T, Kovacs J (2018) Investigation of the climate-driven periodicity of shallow groundwater level fluctuations in a Central-Eastern European agricultural region. Hydrogeol J 26(3):677–688

    Article  Google Scholar 

  • Guo L, Gong H, Zhu F, Guo X, Zhou C, Qiu L (2014) Periodic characteristics of groundwater level and precipitation based on wavelet analysis. Geography and Geo-Information Science, 30(02):35–38+127. (in Chinese)

  • Hall D, Fitzpatrick C (1999) Spectral analysis of pressure variations during combined air and water backwash of rapid gravity filters. Water Res 33(17):3666–3672

    Article  Google Scholar 

  • Jain S, Nayak P, Sudheer K (2008) Models for estimating evapotranspiration using artificial neural networks, and their physical interpretation. Hydrol Process 22(13):2225–2234

    Article  Google Scholar 

  • Jiang W (2018) Study on dynamic characteristics and prediction of groundwater in Chengdu Plain. Dissertation, Chengdu University of Technology. (in Chinese)

  • Kumar P, Foufoula-Georgiou E (1993) A multicomponent decomposition of spatial rainfall fields: 2. Self-Similarity in Fluctuations. Water Resour Res 29(8):2533–2544

    Article  Google Scholar 

  • Li L (2013) Construction and application of numerical model of groundwater flow in large area of North China Plain. Dissertation, China University of Geosciences. (in Chinese)

  • Li P, Lu W, Yang Z (2005) Application of spectrum analysis method to the prediction of groundwater regime in west Jilin province. Hydrogeol Eng Geol 32(4):69–73 (in Chinese)

    Google Scholar 

  • Li M, Xiao C, Liang X, Hu B (2016) Analysis of dynamic characteristics and driving factors of groundwater depth under changing environment. Water Conserv Hydropower Technol 49(11):1–7 (in Chinese)

    Google Scholar 

  • Liu C, Yu J, Kendy E (2001) Groundwater exploitation and its impact on the environment in the North China Plain. Water Int 26(2):265–272

    Article  Google Scholar 

  • Mallat SG (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(4):674–693

    Article  Google Scholar 

  • Mikayelyan VG (2020) The Gibbs phenomenon for Stromberg wavelets. Proc Jpn Acad Series A Math Sci 96(3):23–27

    Google Scholar 

  • Nakken M (1999) Wavelet analysis of rainfall-runoff variability isolating climatic from anthropogenic patterns. Environ Model Softw 14(4):283–295

    Article  Google Scholar 

  • Qian Y, Zhang Z, Fei Y, Chen J, Zhang F, Wang Z (2014) Analysis of sustainable utilization potential of shallow groundwater in North China Plain. Chin J Eco-Agric 22(08):890–897 (in Chinese)

    Google Scholar 

  • Rezaie-balf M, Naganna SR, Ghaemi A, Deka PC (2017) Alireza Wavelet coupled MARS and M5 Model Tree approaches for groundwater level forecasting. J Hydrol 553:356–373

    Article  Google Scholar 

  • Sahoo S, Russo TA, Elliott J (2017) Machine learning algorithms for modeling groundwater level changes in agricultural regions of the US. Water Resour Res 53(5):3878–3895

    Article  Google Scholar 

  • Shi J, Li G, Liang X, Chen Z, Shao J, Song X (2014) Evolution Mechanism and Control of Groundwater in the North China Plain. Acta Geoscientia Sinica 35(5):527–534 (in Chinese)

    Google Scholar 

  • Shih D (2018) Storage in confined aquifer: Spectral analysis of groundwater in responses to Earth tides and barometric effect. Hydrol Process 32(12):1927–1935

    Article  Google Scholar 

  • Velasco EM, Gurdak JJ, Dickinson JE, Ferré TPA, Corona CR (2017) Interannual to multidecadal climate forcings on groundwater resources of the U.S. West Coast. J Hydrol Reg Stud 11:250–265

    Article  Google Scholar 

  • Wang W, Zhang R (2008) Multi-time-scale analysis of ground water level series with wavelet transform. Eng J Wuhan Univ 41(2): l–4 (in Chinese)

  • Wang S, Song X, Wang Q, Xiao G, Liu C (2008a) Dynamic features of shallow groundwater in North China Plain. Acta Geogr Sin 63(5):462–472 (in Chinese)

    Google Scholar 

  • Wang S, Song X, Wang Q, Xiao G (2008b) Liu C (2008) Dynamic changes of shallow groundwater level in the North China Plain. Acta Geogr Sin 05:435–445 (in Chinese)

    Google Scholar 

  • Wang S, Song X, Wang Q, Tang C, Liu C (2014) Periodic characteristics of micro-dynamic variation of groundwater level in the North China Plain. J Hydrogeol Eng Geol 41(03):6–12 (in Chinese)

    Google Scholar 

  • Wu D, Wang J, Teng Y (2004) Application of wavelet decomposition and wavelet transform method to forecasting of groundwater regime. J Hydraul Eng 5:39–45 (in Chinese)

    Google Scholar 

  • Xu C (2017) Analysis of groundwater dynamic change and its Influencing factors in Guangping County, Handan City. Dissertation, China University of Geosciences (in Chinese)

  • Yadav B, Gupta PK, Patidar N, Himanshu SK (2020) Ensemble modelling framework for groundwater level prediction in urban areas of India. Sci Total Environ 712(10):135539

    Article  Google Scholar 

  • Yang G, Meng J, Su X (2011) A briefly review of evaluation index and method of groundwater overdraft. Water Sav Irrig 8:34–38 (in Chinese)

    Google Scholar 

Download references

Acknowledgements

Many thanks to Dan Lou and Zhuoran Wang for their assistance with the data analyses. We would like to thank Editage (www.editage.cn) for English language editing.

Funding

This work was supported by the National Key R&D Program of China (2018YFC0407701), Natural Science Foundation of Jiangsu (BK20181035), and Fundamental Research Funds for the Central Universities (B200202025). This study does not necessarily reflect the views of the funding agencies.

Author information

Authors and Affiliations

  1. College of Hydrology and Water Resources, Hohai University, Nanjing, 210098, Jiangsu, China

    Long Sun, Tema Koketso Ealotswe, Lei Wei, Peicen Jin, Ziyi Song & Chengpeng Lu

  2. Water Information Center, Ministry of Water Resources, Beijing, 100053, China

    Long Sun

  3. Nanjing Automation Institute of Water Conservancy and Hydrology, Ministry of Water Resources, Nanjing, 210012, Jiangsu, China

    Yongbing Zhang

  4. Water Resources Bureau of Jining, Jining, 272000, Shandong, China

    Haiyang Si

Authors
  1. Long Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yongbing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Haiyang Si
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tema Koketso Ealotswe
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lei Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Peicen Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ziyi Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Chengpeng Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed extensively to the work presented in this paper. L.S, L.W, and Z.S performed the modeling and data curation; Y.B.Z and Y.Z analyzed the results; C.L provided funding acquisition; L.S, L.W, and P.J wrote the paper; C.L and T.K.E performed the review and editing.

Corresponding author

Correspondence to Chengpeng Lu.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, L., Zhang, Y., Si, H. et al. Simulation and prediction of shallow groundwater depth in the North China Plain based on regional periodic characteristics. Environ Earth Sci 80, 635 (2021). https://doi.org/10.1007/s12665-021-09933-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-021-09933-8

Keywords

Search

Navigation