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Prévisions à court terme du niveau des aquifères : le cas de la nappe de Beauce

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  • Liliane Bonnal
  • Pascal Favard

Abstract

The objective of this article is to establish short term forecasts (one year), on the level of groundwater using conventional time series models. The interest of this work is to give policy makers reliable information on the evolution of groundwater levels. The forecasts which are essentially based on previous levels of groundwater are quite satisfactory. Indeed, the maximum forecast error is about half percent.
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Suggested Citation

  • Liliane Bonnal & Pascal Favard, 1999. "Prévisions à court terme du niveau des aquifères : le cas de la nappe de Beauce," Post-Print hal-01200917, HAL.
    • Handle: RePEc:hal:journl:hal-01200917
    Note: View the original document on HAL open archive server: https://hal.science/hal-01200917
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    1. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    2. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    3. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
    4. Christophe Bontemps & Stéphane Couture & Pascal Favard, 2003. "Estimation de la demande en eau d'irrigation sous incertitude," Économie rurale, Programme National Persée, vol. 276(1), pages 17-24.
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