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Forecasting monthly riverflow time series

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  • Noakes, Donald J.
  • McLeod, A. Ian
  • Hipel, Keith W.

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  • Noakes, Donald J. & McLeod, A. Ian & Hipel, Keith W., 1985. "Forecasting monthly riverflow time series," International Journal of Forecasting, Elsevier, vol. 1(2), pages 179-190.
    • Handle: RePEc:eee:intfor:v:1:y:1985:i:2:p:179-190
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    Cited by:

    1. Ferreira, R.S. & Barroso, L.A. & Carvalho, M.M., 2012. "Demand response models with correlated price data: A robust optimization approach," Applied Energy, Elsevier, vol. 96(C), pages 133-149.
    2. Felipe Nazaré & Luiz Barroso & Bernardo Bezerra, 2021. "A Probabilistic and Value-Based Planning Approach to Assess the Competitiveness between Gas-Fired and Renewables in Hydro-Dominated Systems: A Brazilian Case Study," Energies, MDPI, vol. 14(21), pages 1-21, November.
    3. T. Manouchehri & A. R. Nematollahi, 2019. "Periodic autoregressive models with closed skew-normal innovations," Computational Statistics, Springer, vol. 34(3), pages 1183-1213, September.
    4. Eugen Ursu & Pierre Duchesne, 2009. "Estimation and model adequacy checking for multivariate seasonal autoregressive time series models with periodically varying parameters," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(2), pages 183-212, May.
    5. Paulo Vitor Larroyd & Renata Pedrini & Felipe Beltrán & Gabriel Teixeira & Erlon Cristian Finardi & Lucas Borges Picarelli, 2022. "Dealing with Negative Inflows in the Long-Term Hydrothermal Scheduling Problem," Energies, MDPI, vol. 15(3), pages 1-19, February.
    6. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    7. Mohammad Ebrahim Banihabib & Reihaneh Bandari & Richard C. Peralta, 2019. "Auto-Regressive Neural-Network Models for Long Lead-Time Forecasting of Daily Flow," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 159-172, January.
    8. Lohmann, Timo & Hering, Amanda S. & Rebennack, Steffen, 2016. "Spatio-temporal hydro forecasting of multireservoir inflows for hydro-thermal scheduling," European Journal of Operational Research, Elsevier, vol. 255(1), pages 243-258.
    9. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    10. Konrad Bogner & Katharina Liechti & Luzi Bernhard & Samuel Monhart & Massimiliano Zappa, 2018. "Skill of Hydrological Extended Range Forecasts for Water Resources Management in Switzerland," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(3), pages 969-984, February.
    11. Ooms, M. & Franses, Ph.H.B.F., 1998. "A seasonal periodic long memory model for monthly river flows," Econometric Institute Research Papers EI 9842, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. PEREAU Jean-Christophe & URSU Eugen, 2015. "Application of periodic autoregressive process to the modeling of the Garonne river flows," Cahiers du GREThA (2007-2019) 2015-14, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    13. Lima, L.M. Marangon & Popova, E. & Damien, P., 2014. "Modeling and forecasting of Brazilian reservoir inflows via dynamic linear models," International Journal of Forecasting, Elsevier, vol. 30(3), pages 464-476.

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