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Modeling Nitrate Concentration In Ground Water Using Regression And Neural Networks

Author

Listed:
  • Ramasamy, Nacha
  • Krishnan, Palaniappa
  • Bernard, John C.
  • Ritter, William F.

Abstract

Nitrate concentration in ground water is a major problem in specific agricultural areas. Using regression and neural networks, this study models nitrate concentration in ground water as a function of iron concentration in ground water, season and distance of the well from a poultry house. Results from both techniques are comparable and show that the distance of the well from a poultry house has a significant effect on nitrate concentration in groundwater.

Suggested Citation

  • Ramasamy, Nacha & Krishnan, Palaniappa & Bernard, John C. & Ritter, William F., 2003. "Modeling Nitrate Concentration In Ground Water Using Regression And Neural Networks," Staff Papers 15825, University of Delaware, Department of Food and Resource Economics.
    • Handle: RePEc:ags:udelsp:15825
    DOI: 10.22004/ag.econ.15825
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    Cited by:

    1. Jaber Alkasseh & Mohd Adlan & Ismail Abustan & Hamidi Aziz & Abu Hanif, 2013. "Applying Minimum Night Flow to Estimate Water Loss Using Statistical Modeling: A Case Study in Kinta Valley, Malaysia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1439-1455, March.
    2. Sayed Farhad MOUSAVI & Mohammad Javad AMIRI, 2012. "Modelling nitrate concentration of groundwater using adaptive neural-based fuzzy inference system," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 7(2), pages 73-83.

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