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Prediction of Inflow at Three Gorges Dam in Yangtze River with Wavelet Network Model

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  • Wensheng Wang
  • Juliang Jin
  • Yueqing Li

Abstract

A wavelet network model is developed to predict the inflow of Three Gorges dam in Yangtze River, China. The model makes use of the multi-resolution analysis of wavelet analysis and the nonlinear capability of artificial neural network. The short and long term input runoff of Three Gorges dam, such as annual mean discharge, seasonal mean discharge of 10 days period, daily mean discharge and annual maximum flood peak discharge, have been predicted with the wavelet network model (WNM). At the same time a kind of threshold auto-regressive model (TAR) has also applied for those predictions. The comparison of WNM with TAR has been executed. The results show that the accuracy of model predictions with WNM is generally better than that with TAR. The suggested wavelet network model is functional and feasible for runoff prediction. Copyright Springer Science+Business Media B.V. 2009

Suggested Citation

  • Wensheng Wang & Juliang Jin & Yueqing Li, 2009. "Prediction of Inflow at Three Gorges Dam in Yangtze River with Wavelet Network Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(13), pages 2791-2803, October.
    • Handle: RePEc:spr:waterr:v:23:y:2009:i:13:p:2791-2803
    DOI: 10.1007/s11269-009-9409-2
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    References listed on IDEAS

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    1. Mehmetcik Bayazit & Hafzullah Aksoy, 2001. "Using wavelets for data generation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(2), pages 157-166.
    2. Ahmed El-Shafie & Mahmoud Taha & Aboelmagd Noureldin, 2007. "A neuro-fuzzy model for inflow forecasting of the Nile river at Aswan high dam," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(3), pages 533-556, March.
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    1. Falamarzi, Yashar & Palizdan, Narges & Huang, Yuk Feng & Lee, Teang Shui, 2014. "Estimating evapotranspiration from temperature and wind speed data using artificial and wavelet neural networks (WNNs)," Agricultural Water Management, Elsevier, vol. 140(C), pages 26-36.
    2. Ozgur Kisi, 2011. "Wavelet Regression Model as an Alternative to Neural Networks for River Stage Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(2), pages 579-600, January.
    3. Muhammad Shoaib & Asaad Y. Shamseldin & Sher Khan & Mudasser Muneer Khan & Zahid Mahmood Khan & Tahir Sultan & Bruce W. Melville, 2018. "A Comparative Study of Various Hybrid Wavelet Feedforward Neural Network Models for Runoff Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 83-103, January.
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    5. Salvatore Campisi-Pinto & Jan Adamowski & Gideon Oron, 2012. "Forecasting Urban Water Demand Via Wavelet-Denoising and Neural Network Models. Case Study: City of Syracuse, Italy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(12), pages 3539-3558, September.
    6. Huaizhi Su & Xiaoqun Yan & Hongping Liu & Zhiping Wen, 2017. "Integrated Multi-Level Control Value and Variation Trend Early-Warning Approach for Deformation Safety of Arch Dam," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 2025-2045, April.
    7. Rajeev Sahay & Ayush Srivastava, 2014. "Predicting Monsoon Floods in Rivers Embedding Wavelet Transform, Genetic Algorithm and Neural Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 301-317, January.
    8. R. Venkata Ramana & B. Krishna & S. Kumar & N. Pandey, 2013. "Monthly Rainfall Prediction Using Wavelet Neural Network Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3697-3711, August.
    9. Seyed Akrami & Vahid Nourani & S. Hakim, 2014. "Development of Nonlinear Model Based on Wavelet-ANFIS for Rainfall Forecasting at Klang Gates Dam," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2999-3018, August.
    10. J. Drisya & D. Sathish Kumar & Thendiyath Roshni, 2021. "Hydrological drought assessment through streamflow forecasting using wavelet enabled artificial neural networks," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 3653-3672, March.
    11. Sajjad Abdollahi & Jalil Raeisi & Mohammadreza Khalilianpour & Farshad Ahmadi & Ozgur Kisi, 2017. "Daily Mean Streamflow Prediction in Perennial and Non-Perennial Rivers Using Four Data Driven Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4855-4874, December.
    12. Wensheng Wang & Shixiong Hu & Yueqing Li, 2011. "Wavelet Transform Method for Synthetic Generation of Daily Streamflow," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(1), pages 41-57, January.
    13. Padam Jee Omar & Shishir Gaur & S. B. Dwivedi & P. K. S. Dikshit, 2020. "A Modular Three-Dimensional Scenario-Based Numerical Modelling of Groundwater Flow," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 1913-1932, April.

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