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Artificial neural networks approach in evapotranspiration modeling: a review

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Abstract

The use of artificial neural networks (ANNs) in estimation of evapotranspiration has received enormous interest in the present decade. Several methodologies have been reported in the literature to realize the ANN modeling of evapotranspiration process. The present review discusses these methodologies including ANN architecture development, selection of training algorithm, and performance criteria. The paper also discusses the future research needs in ANN modeling of evapotranspiration to establish this methodology as an alternative to the existing methods of evapotranspiration estimation.

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Authors and Affiliations

  1. Division of Resource Management, Central Research Institute for Dryland Agriculture, Hyderabad, Andhra Pradesh, 500 059, India

    M. Kumar

  2. Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, West Bengal, 721 302, India

    N. S. Raghuwanshi & R. Singh

Authors
  1. M. Kumar
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  2. N. S. Raghuwanshi
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  3. R. Singh
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Correspondence to M. Kumar.

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Communicated by S. Raine.

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Kumar, M., Raghuwanshi, N.S. & Singh, R. Artificial neural networks approach in evapotranspiration modeling: a review. Irrig Sci 29, 11–25 (2011). https://doi.org/10.1007/s00271-010-0230-8

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  • DOI: https://doi.org/10.1007/s00271-010-0230-8

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