Estimation of future Reference Crop Evapotranspiration Using Soft Computing Techniques

  • Authors

    • L Gowri
    • K Sasireka
    2018-07-20
    https://doi.org/10.14419/ijet.v7i3.12.16438
  • Evapotranspiration, Artificial Neural Network (ANN), FAO-modified Penman method, Thronthwaite method, Hargreaves method.

  • Abstract

    Estimation of Evapotranspiration forms the basis for computation of irrigation requirement of crop, and also it is considered as one of the vital component of hydrological cycle. This study describes the conceptual outline and implementation to test the ability of an artificial neural network (ANN) for accurate estimation of reference evapotranspiration (ETo). There are many conventional methods like FAO modified Penman method, temperature-based and radiation-based empirical methods are used to estimate (ETo). Among the conventional methods, Thronthwaite method and Hargreaves method perform well in the selected region.  An ANN network is trained to recognize patterns of the daily meteorological variables and their corresponding evapotranspiration which is estimated using FAO-modified Penman method. The advantage of using ANN technique is the network’s ability to use minimum number of meteorological parameters, hence economical.

     

  • References

    1. [1] D. M. Amatya, R. W. Skagga, and J. D. Gregory, Journal of Irrigation and Drainage Engineering, ASCE, 121(6), 427- 435 (1995).

      [2] J. Doorenbos, WO. Pruitt, Irrigation and Drainage Paper 24, Food and Agriculture Organization of the United Nations. Rome. Italy, pp. 144 (1977).

      [3] J. A. Freeman, and D. M. Skapura (1991) Addison-Wesley Publishing Company, New York, (1991).

      [4] G.H. Hargreaves, Transaction of the American Society of Agricultural Engineers 18, 980-984 (1975).

      [5] L. Jiang, and S. Islam, Water Resour. Res 37(2): .329-340 (2001).

      [6] V. Jothiprakash, MR. Ramachandran,P. Shamuganathan, Journal of Institution of Engineers (India) 18,17-20 (2002)

      [7] V. Jothiprakash, M.G. Devamane, and K. Sasireka, Journal of Institution of Engineers (India), Vol, 88, Dec(AG), 19-26. ( 2007)

      [8] V. Jothiprakash, M.G. Devamane, and K. Sasireka, Journal of Institution of Engineers (India) Vol. 89, Dec(AG), 22-27 (2008).

      [9] M. Kumar, N. S. Raghuwanshi, and R. Singh, Irrig. Sci., 29(1), 11–25 (2011).

      [10] S. Mohan, and Rama Prasad, Research Report No WRI Department of Civil Engineering, Indian Institute of Science, Bangalore (1987).

      [11] J. Shiri, et al. Comput. Electron. Agric., 108, 230–241 (2014).

      [12] Shahaboddin Shamshirband, Mohsen Amirmojahedi, Milan Goci, Shatirah Akib, Dalibor Petkovi, Jamshid Piri,; and Slavisa Trajkovic, J. Irrig. Drain Eng., 142(2): 04015044, (2016).

      [13] CW. Thronthwaite, Geographical Review 38: 55-94 (1948).

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  • How to Cite

    Gowri, L., & Sasireka, K. (2018). Estimation of future Reference Crop Evapotranspiration Using Soft Computing Techniques. International Journal of Engineering & Technology, 7(3.12), 606-611. https://doi.org/10.14419/ijet.v7i3.12.16438

    Received date: 2018-07-28

    Accepted date: 2018-07-28

    Published date: 2018-07-20