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Contrast of evolution models for agricultural contaminants in ground waters by means of fuzzy logic and data mining

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Environmental Geology

Abstract

This work aims at contrasting, by means of a set of fuzzy logic- and data mining-based algorithms, the functioning model of a detritic aquifer undergoing overexploitation and nitrate excess input coming from strawberry and citrus intensive crops in its recharge zone. To provide researchers unskilled in data mining techniques with an easy and intuitive interpretation, the authors have developed a computer tool based on fuzzy logic that allows immediate qualitative analysis of the data contained in a data mass from the water chemical analyses, and serves as a contrast to functioning models previously proposed with classical statistics.

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Authors and Affiliations

  1. Escuela Politécnica Superior, Universidad de Huelva, Ctra Palos de la Frontera, s/n., 21819, Palos de la Frontera, Huelva, Spain

    J.M. Andujar, J. Aroba, M.L. la de Torre & J.A. Grande

Authors
  1. J.M. Andujar
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  2. J. Aroba
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  3. M.L. la de Torre
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  4. J.A. Grande
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Corresponding author

Correspondence to M.L. la de Torre.

Additional information

M.L. de la Torre and J.A. Grande belongs to Water Resources and Quality Research Group. J.M. Andujar and J. Aroba belongs to Control and Robotics Research Group

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Andujar, J., Aroba, J., de Torre, M.l. et al. Contrast of evolution models for agricultural contaminants in ground waters by means of fuzzy logic and data mining. Environ Geol 49, 458–466 (2006). https://doi.org/10.1007/s00254-005-0103-2

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  • DOI: https://doi.org/10.1007/s00254-005-0103-2

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