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Realistic forecasting of groundwater level, based on the eigenstructure of aquifer dynamics

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  • Bidwell, V.J.

Abstract

Short-term management of groundwater resources, especially during droughts, can be assisted by forecasts of groundwater levels. Such forecasts need to account for the dynamic response of the aquifer to likely recharge scenarios and recent but unknown abstractions. This paper describes a method for formulating ARMAX forecast equations from a linear system description based on the eigenvalues and eigenvectors (eigenstructure) of aquifer dynamics. For the piezometric response of a heterogeneous aquifer to a fixed spatial distribution of land surface recharge, with time-varying magnitude, only a few eigenvalues are significant. The resulting model is demonstrated with monthly values of land surface recharge and groundwater level data from a 2000km2 alluvial aquifer in Canterbury, New Zealand.

Suggested Citation

  • Bidwell, V.J., 2005. "Realistic forecasting of groundwater level, based on the eigenstructure of aquifer dynamics," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 69(1), pages 12-20.
    • Handle: RePEc:eee:matcom:v:69:y:2005:i:1:p:12-20
    DOI: 10.1016/j.matcom.2005.02.023
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    Cited by:

    1. James Griffiths & Jing Yang & Ross Woods & Christian Zammit & Rasool Porhemmat & Ude Shankar & Channa Rajanayaka & Jeffrey Ren & Nicholas Howden, 2023. "Parameterization of a National Groundwater Model for New Zealand," Sustainability, MDPI, vol. 15(17), pages 1-20, September.
    2. Mahdi Soleimani Motlagh & Hoda Ghasemieh & Ali Talebi & Khodayar Abdollahi, 2017. "Identification and Analysis of Drought Propagation of Groundwater During Past and Future Periods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 109-125, January.
    3. John F. Raffensperger & Mark W. Milke & E. Grant Read, 2009. "A Deterministic Smart Market Model for Groundwater," Operations Research, INFORMS, vol. 57(6), pages 1333-1346, December.
    4. Chattopadhyay, Pallavi Banerjee & Rangarajan, R., 2014. "Application of ANN in sketching spatial nonlinearity of unconfined aquifer in agricultural basin," Agricultural Water Management, Elsevier, vol. 133(C), pages 81-91.

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