Skip to main content
SpringerLink
Log in

Multi-Resolution Cointegration Prediction for Runoff and Sediment Load

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

With the wavelet transform method, the multi-resolution analysis of runoff and sediment load at Huaxian hydrological station located in the lower reaches of the Weihe River in China is presented to find the varying quasic-periodic waveforms existing in different decomposed time scales. The cointegration theory is introduced to reveal the long-term balance relationship and short-term fluctuations of the original and decomposed runoff and sediment load time series. Thus, considering the decomposed sediment load components in different time scales as the input data series, and the corresponding decomposed runoff component acting as the output data series, the multi-resolution cointegration method is produced. The results show that the multi-resolution cointegration method has the higher prediction accuracy, and the prediction errors are almost less than 5 %.

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
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Abiyev RH (2011) Fuzzy wavelet neural network based on fuzzy clustering and gradient techniques for time series prediction. Neural Comput & Applic 20(2):249–259

    Article  Google Scholar 

  • Aman MK (2015) Wavelet genetic algorithm-support vector regression (wavelet GA-SVR) for monthly flow forecasting. Water Resour Manag 29(4):1283–1293

    Article  Google Scholar 

  • Braga ACFM, da Silva RM, Santos CAG, de Oliverira Galvão C, Nobre P (2013) Downscaling of a global climate model for estimation of runoff, sediment yield and dam storage: a case study of Pirapama basin. Brazil J Hydrol 498:46–58

    Article  Google Scholar 

  • Carriquiry JD, Sanchez A (1999) Sedimentation in the Colorado River delta and upper Gulf of California after nearly a century of discharge loss. Mar Geol 158:125–145

    Article  Google Scholar 

  • Compagnucci RH, Blanco SA, Figliola MA, Jacovkis PM (2000) Variability in subtropical Andean Argentinean Atuel fiver: a wavelet approach. Environmetrics 11:251–269

    Article  Google Scholar 

  • Dai SB, Lu XX (2014) Sediment load change in the Yangtze River (Changjiang): a review. Geomorphology 215:60–73

    Article  Google Scholar 

  • Engle RF, Granger CWJ (1987) Cointegration and error correction: representation, estimation and testing. Econometrica 55:251–276

    Article  Google Scholar 

  • Fanos AM (1995) The impact of human activities on the erosion and accretion of the Nile Delta coast. J Coast Res 11(3):821–833

    Google Scholar 

  • Fukhrudin KM, Assefa MM, Patrick B, Karen BG (2013) Modeling the impact of land use changes on runoff and sediment yield in the Le Sueur watershed, Minnesota using GeoWEPP. Catena 107:35–45

    Article  Google Scholar 

  • Gaucherel C (2002) Use of wavelet transform for temporal characterization of remote watersheds. J Hydrol 269:101–121

    Article  Google Scholar 

  • Gebremicael TG, Mohamed YA, Betrie GD, van der Zaag P, Teferi E (2013) Trend analysis of runoff and sediment fluxes in the Upper Blue Nile basin: a combined analysis of statistical tests, physically-based models and landuse maps. J Hydrol 482:57–68

    Article  Google Scholar 

  • Han ZHY, Wei YM, Jiao YL, Fan Y, Zhang JT (2004) On the cointegration and causality between Chinese GDP and energy consumption. Syst Eng 22(12):17–21

    Google Scholar 

  • He L, Huang GH, Zeng GM, Lu HW (2008) Wavelet-based multiresolution analysis for data cleaning and its application to water quality management system. Expert Syst Appl 35:1301–1310

    Article  Google Scholar 

  • Kulwinder SP, Rashmi B (2013) Wavelet and statistical analysis of river water quality parameters. Appl Math Comput 219:10172–10182

    Article  Google Scholar 

  • Mallat SG (1998) A wavelet tour of signal processing, 2nd edn. Academic, San Diego

    Google Scholar 

  • Mu XM, Wang WL, Xu XX (1999) The influence of the soil and water conservation on the surface runoff in the watersheds in the gully plateau region of Loess Plateau. J Hydraul Eng (2):71–75

  • Sadeghi SHR, Seghaleh Bashari M, Rangavar AS (2013) Plot sizes dependency of runoff and sediment yield estimates from a small watershed. Catena 102:55–61

    Article  Google Scholar 

  • Seung-Hoon Y (2007) Urban water consumption and regional economic growth: the case of Taejeon, Korea. Water Resour Manag 21:1353–1361

    Article  Google Scholar 

  • Shi CHX, Zhou YY, Fan XL, Shao WW (2012) A study on the annual runoff changes and its relationship with water and soil conservation practices and climate changes in the middle Yellow River basin. Catena 100:31–41

    Article  Google Scholar 

  • Venkata Ramana R, Krishna B, Kumar SR, Pandey NG (2013) Monthly rainfall prediction using wavelet neural network analysis. Water Resour Manag 27:3697–3711

    Article  Google Scholar 

  • Wang XY, Zhao XP, Liu ZW, Dong SQ (2011) Research on lake eutrophication predictioning methods based on grey theory. Comput Simul 28(1):17–19

    Google Scholar 

  • Xu LQ, Liu SHY (2013) Study of short-term water quality prediction model based on wavelet neural network. Math Comput Model 58:807–813

    Article  Google Scholar 

  • Xu JX, Sun J (2003) Influence of precipitation and human activities on water fluxes from the Yellow River into the sea in the past 50 years. Adv Water Sci 14(6):690–695

    Google Scholar 

  • Yilmaz S, Oysal Y (2010) Fuzzy wavelet neural network models for prediction and identification of dynamical systems. IEEE Trans Neural Netw 21(10):1599–1609

    Article  Google Scholar 

  • Zhang LY, Zhang LP, Cao FL, Song XY (2006a) Annual runoff forecasting research based on the theory of cointegration and error correction model. Eng J Wuhan Univ 39(6):6–11

    Google Scholar 

  • Zhang Q, Xu CHY, Becker S, Jiang T (2006b) Sediment and runoff changes in the Yangtze River basin during past 50 years. J Hydrol 331:511–523

    Article  Google Scholar 

  • Zhang Y, Xu JH, Lu GG (2008) Dynamic analysis of water footprint and resources utility efficiency of Xinjiang in northwest of China arid areas. J Desert Res 28(4):775–783

    Google Scholar 

  • Zhang XM, Cao WH, Yu XX, Wu SH (2009) Effect of LUCC on runoff regulation in watershed in loess gullied-hilly region of China. J Hydraul Eng 40(6):641–650

    Google Scholar 

  • Zhang JP, Ding ZHH, Yuan WL, Zuo QT (2013) Research on the relationship between rainfall and reference crop evapotranspiration with multi-time scales. Paddy Water Environ 11:473–482

    Article  Google Scholar 

  • Zhang JP, Zhao Y, Ding ZHH (2014a) Research on the relationships between rainfall and meteorological yield in irrigation district. Water Resour Manag 28:1689–1702

    Article  Google Scholar 

  • Zhang X, Yu GQ, Li ZHB, Li P (2014b) Experimental study on slope runoff, erosion and sediment under different vegetation types. Water Resour Manag 28(9):2415–2433

    Article  Google Scholar 

  • Zhao FF, Xu ZX (2009) Hydrological response to climate change in headwater catchment of the Yellow River Basin. Res Sci 31(5):722–730

    Google Scholar 

  • Zhao RR, Chen HC, Zhu SL, Zhao LQ (2007) Analysis on variations of runoff and reasons of headwater region of the Yellow River. Yellow River 29(4):15–16

    Google Scholar 

Download references

Acknowledgments

This research is supported by the National Natural Sciences Foundation of China (Project No. 51309202, 51379216) and Open Laboratory of Science and Water Conservancy of Key Disciplines in Henan Province, and also by Program for Innovative Research Team (in Science and Technology) in University of Henan Province (No. 13IRTSTHN030).

Compliance with Ethical Standards

The authors declare that they have no conflict of interest. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee. This article does not contain any studies performed by any of the authors. Informed consent was obtained from all individual participants included in the study.

Author information

Authors and Affiliations

  1. Laboratory of Science and Water Conservancy of Key Disciplines in Henan Province, Zhengzhou University, Zhengzhou, 450001, China

    Jinping Zhang

  2. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China

    Yong Zhao & Weihua Xiao

  3. Institute of Water Resources and Environment, Zhengzhou University, High-tech District, No. 100 Science Road, Zhengzhou city, 450001, Henan Province, China

    Jinping Zhang

Authors
  1. Jinping Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weihua Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jinping Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, J., Zhao, Y. & Xiao, W. Multi-Resolution Cointegration Prediction for Runoff and Sediment Load. Water Resour Manage 29, 3601–3613 (2015). https://doi.org/10.1007/s11269-015-1018-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-015-1018-7

Keywords

Search

Navigation