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Predicting Daily Water Table Fluctuations in Karstic Aquifers from GIS-Based Modelling, Climatic Settings and Extraction Wells

Author

Listed:
  • Concepcion Pla

    (Universidad de Alicante
    Unidad Asociada UA-CSIC, Universidad de Alicante)

  • Javier Valdes-Abellan

    (Universidad de Alicante)

  • Antonio Jose Tenza-Abril

    (Universidad de Alicante)

  • David Benavente

    (Universidad de Alicante
    Unidad Asociada UA-CSIC, Universidad de Alicante)

Abstract

In semiarid regions, karstic aquifers are in some cases essential since they often constitute the only source of water supply. The increasing demand for water in these regions is responsible for the decreasing water table levels. As a consequence, groundwater management becomes indispensable. A robust black-box model of the Solana aquifer, a large karstic aquifer in Alicante province, is developed considering GIS-based modelling of the studied area, climatic settings and anthropic disturbances (water extractions and irrigation returns). The proposed model accurately predicts water table levels evolution (with EF index of 0.97 and RMSE of 0.09) and assesses the recharge rates. The model aims to become a useful tool in order to better understand the characteristics of karstic aquifers. A distinctive feature of the model is that it estimates the heterogeneous effective porosities along the depth profiles of the aquifer, which provides an advantage related to detect changes in the hydraulic transmissivity within karstic formations.

Suggested Citation

  • Concepcion Pla & Javier Valdes-Abellan & Antonio Jose Tenza-Abril & David Benavente, 2016. "Predicting Daily Water Table Fluctuations in Karstic Aquifers from GIS-Based Modelling, Climatic Settings and Extraction Wells," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2531-2545, May.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:7:d:10.1007_s11269-016-1302-1
    DOI: 10.1007/s11269-016-1302-1
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    1. Adrian Werner & Darren Alcoe & Carlos Ordens & John Hutson & James Ward & Craig Simmons, 2011. "Current Practice and Future Challenges in Coastal Aquifer Management: Flux-Based and Trigger-Level Approaches with Application to an Australian Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(7), pages 1831-1853, May.
    2. Akram Sedki & Driss Ouazar, 2011. "Simulation-Optimization Modeling for Sustainable Groundwater Development: A Moroccan Coastal Aquifer Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(11), pages 2855-2875, September.
    3. Yan-Fang Sang & Zhonggen Wang & Changming Liu, 2015. "Wavelet Neural Modeling for Hydrologic Time Series Forecasting with Uncertainty Evaluation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 1789-1801, April.
    4. R. Rejani & Madan Jha & Sudhindra Panda, 2009. "Simulation-Optimization Modelling for Sustainable Groundwater Management in a Coastal Basin of Orissa, India," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(2), pages 235-263, January.
    5. Wallis, K.J. & Candela, L. & Mateos, R.M. & Tamoh, K., 2011. "Simulation of nitrate leaching under potato crops in a Mediterranean area. Influence of frost prevention irrigation on nitrogen transport," Agricultural Water Management, Elsevier, vol. 98(10), pages 1629-1640, August.
    6. Lior Netzer & Noam Weisbrod & Daniel Kurtzman & Ahmed Nasser & Ellen Graber & Daniel Ronen, 2011. "Observations on Vertical Variability in Groundwater Quality: Implications for Aquifer Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(5), pages 1315-1324, March.
    7. Pallavi Chattopadhyay & Nimisha Vedanti & V. Singh, 2015. "A Conceptual Numerical Model to Simulate Aquifer Parameters," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(3), pages 771-784, February.
    8. J. Sreekanth & Bithin Datta, 2011. "Comparative Evaluation of Genetic Programming and Neural Network as Potential Surrogate Models for Coastal Aquifer Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(13), pages 3201-3218, October.
    9. Purna Nayak & Y. Rao & K. Sudheer, 2006. "Groundwater Level Forecasting in a Shallow Aquifer Using Artificial Neural Network Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(1), pages 77-90, February.
    10. A. Manglik & S. Rai, 2000. "Modeling of Water Table Fluctuations in Response to Time-varying Recharge and Withdrawal," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 14(5), pages 339-347, October.
    11. Samad Emamgholizadeh & Khadije Moslemi & Gholamhosein Karami, 2014. "Prediction the Groundwater Level of Bastam Plain (Iran) by Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5433-5446, December.
    12. Fayez Abdulla & Tamer Eshtawi & Hamed Assaf, 2009. "Assessment of the Impact of Potential Climate Change on the Water Balance of a Semi-arid Watershed," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(10), pages 2051-2068, August.
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