IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v30y2016i5p1851-1865.html
   My bibliography  Save this article

Investigating Chaos and Nonlinear Forecasting in Short Term and Mid-term River Discharge

Author

Listed:
  • Mohammad Zounemat-Kermani

Abstract

In the present study, an attempt is made to investigate and identify chaos using various techniques as well as river flow forecasting in short-term (daily) and mid-term (monthly) scales using nonlinear local approximation method (NLA) and ARIMA method. Daily and monthly flow data of Daintree River in Australia from 1969 to 2011 are used. In this respect, seven nonlinear dynamic methods including (1) average mutual information function; (2) phase space reconstruction; (3) false nearest neighbour algorithm; (4) method of surrogate data; (5) correlation dimension method; (6) Lyapunov exponent method; and (7) nonlinear local approximation are employed. The Takens’ theorem, mutual information and false nearest neighbour are used to determine the delay time and embedding dimension for the phase space reconstruction. The correlation dimensions obtained for the short term and mid-term river flow are 6.7 and 3.3, respectively. The finite dimensions obtained for the short term and mid-term river flow time series indicate the possible existence of chaos. The comparative analyses show that the NLA method is superior to ARIMA in mid-term scale while both models are acceptable for short term scale forecasting. Copyright Springer Science+Business Media Dordrecht 2016

Suggested Citation

  • Mohammad Zounemat-Kermani, 2016. "Investigating Chaos and Nonlinear Forecasting in Short Term and Mid-term River Discharge," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1851-1865, March.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:5:p:1851-1865
    DOI: 10.1007/s11269-016-1258-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-016-1258-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11269-016-1258-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wen-chuan Wang & Kwok-wing Chau & Dong-mei Xu & Xiao-Yun Chen, 2015. "Improving Forecasting Accuracy of Annual Runoff Time Series Using ARIMA Based on EEMD Decomposition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2655-2675, June.
    2. R. Arunkumar & V. Jothiprakash, 2013. "Chaotic Evolutionary Algorithms for Multi-Reservoir Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5207-5222, December.
    3. Ozgur Kisi & Alireza Nia & Mohsen Gosheh & Mohammad Tajabadi & Azadeh Ahmadi, 2012. "Intermittent Streamflow Forecasting by Using Several Data Driven Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(2), pages 457-474, January.
    4. Qiang Zhang & Ben-De Wang & Bin He & Yong Peng & Ming-Lei Ren, 2011. "Singular Spectrum Analysis and ARIMA Hybrid Model for Annual Runoff Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(11), pages 2683-2703, September.
    5. Niranjan Pramanik & Rabindra Panda & Dhrubajyoti Sen, 2010. "One Dimensional Hydrodynamic Modeling of River Flow Using DEM Extracted River Cross-sections," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(5), pages 835-852, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohammad Zounemat-Kermani, 2016. "Investigating Chaos and Nonlinear Forecasting in Short Term and Mid-term River Discharge," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1851-1865, March.
    2. Farshid Rezaei & Rezvane Ghorbani & Najmeh Mahjouri, 2022. "Improving Daily and Monthly River Discharge Forecasts using Geostatistical Ensemble Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(13), pages 5063-5089, October.
    3. Gavin Boyd & Dain Na & Zhong Li & Spencer Snowling & Qianqian Zhang & Pengxiao Zhou, 2019. "Influent Forecasting for Wastewater Treatment Plants in North America," Sustainability, MDPI, vol. 11(6), pages 1-14, March.
    4. Fang-Fang Li & Zhi-Yu Wang & Xiao Zhao & En Xie & Jun Qiu, 2019. "Decomposition-ANN Methods for Long-Term Discharge Prediction Based on Fisher’s Ordered Clustering with MESA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3095-3110, July.
    5. Benyou Jia & Slobodan P. Simonovic & Pingan Zhong & Zhongbo Yu, 2016. "A Multi-Objective Best Compromise Decision Model for Real-Time Flood Mitigation Operations of Multi-Reservoir System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3363-3387, August.
    6. P. V. Timbadiya & K. M. Krishnamraju, 2023. "A 2D hydrodynamic model for river flood prediction in a coastal floodplain," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(2), pages 1143-1165, January.
    7. Xianming Dou & Yongguo Yang & Jinhui Luo, 2018. "Estimating Forest Carbon Fluxes Using Machine Learning Techniques Based on Eddy Covariance Measurements," Sustainability, MDPI, vol. 10(1), pages 1-26, January.
    8. Xue-hua Zhao & Xu Chen, 2015. "Auto Regressive and Ensemble Empirical Mode Decomposition Hybrid Model for Annual Runoff Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2913-2926, June.
    9. Salman Sharifazari & Shahab Araghinejad, 2015. "Development of a Nonparametric Model for Multivariate Hydrological Monthly Series Simulation Considering Climate Change Impacts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5309-5322, November.
    10. Quande Qin & Huangda He & Li Li & Ling-Yun He, 2020. "A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1249-1273, April.
    11. Vidhi Vig & Anmol Kaur, 2022. "Time series forecasting and mathematical modeling of COVID-19 pandemic in India: a developing country struggling to cope up," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 2920-2933, December.
    12. Dibyendu Samantaray & Chandranath Chatterjee & Rajendra Singh & Praveen Gupta & Sushma Panigrahy, 2015. "Flood risk modeling for optimal rice planning for delta region of Mahanadi river basin in India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 76(1), pages 347-372, March.
    13. Wen-chuan Wang & Kwok-wing Chau & Dong-mei Xu & Lin Qiu & Can-can Liu, 2017. "The Annual Maximum Flood Peak Discharge Forecasting Using Hermite Projection Pursuit Regression with SSO and LS Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 461-477, January.
    14. Baoying Shan & Ping Guo & Shanshan Guo & Zhong Li, 2019. "A Price-Forecast-Based Irrigation Scheduling Optimization Model under the Response of Fruit Quality and Price to Water," Sustainability, MDPI, vol. 11(7), pages 1-21, April.
    15. Mustafa Turan & Mehmet Yurdusev, 2014. "Predicting Monthly River Flows by Genetic Fuzzy Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4685-4697, October.
    16. Liangxu Liu & Xueyong Zhao & Qinglan Meng & He Zhao & Xiaoqian Lu & Junkai Gao & Xueli Chang, 2017. "Annual Precipitation Fluctuation and Spatial Differentiation Characteristics of the Horqin Region," Sustainability, MDPI, vol. 9(1), pages 1-16, January.
    17. Y. Liu & B. Wang & H. Zhan & Y. Fan & Y. Zha & Y. Hao, 2017. "Simulation of Nonstationary Spring Discharge Using Time Series Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4875-4890, December.
    18. Hadi Sanikhani & Ozgur Kisi, 2012. "River Flow Estimation and Forecasting by Using Two Different Adaptive Neuro-Fuzzy Approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(6), pages 1715-1729, April.
    19. Taymoor Awchi, 2014. "River Discharges Forecasting In Northern Iraq Using Different ANN Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(3), pages 801-814, February.
    20. Ali Danandeh Mehr & Vahid Nourani, 2018. "Season Algorithm-Multigene Genetic Programming: A New Approach for Rainfall-Runoff Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(8), pages 2665-2679, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:30:y:2016:i:5:p:1851-1865. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.