Comparative study of conventional and artificial neural network-based ETo estimation models

Author:

Kumar M.,Bandyopadhyay A.,Raghuwanshi N. S.,Singh R.

Publisher

Springer Science and Business Media LLC

Subject

Soil Science,Water Science and Technology,Agronomy and Crop Science

Reference30 articles.

1. Allen RG (1986) A Penman for all seasons. J Irrig Drain Eng 112(4):348–368

2. Allen RG, Jensen ME, Wright JL, Burman RD (1989) Operational estimates of reference evapotranspiration. J Agron 81:650–662

3. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration—guidelines for computing crop water requirements.” Irrig. and Drain. Paper 56, Food and Agriculture Organization of the United Nations (FAO), Rome, Italy

4. Allen RG, Walter IA, Elliott R, Mecham B, Jensen ME, Itenfisu D, Howell TA, Snyder R, Brown P, Echings S, Spofford T, Hattendorf M, Cuenca RH, Wright JL, Martin D (2000) Issues, requirements and challenges in selecting and specifying a standardized ET equation.” Proc., 4th National Irrigation Symp., Am. Soc. Agric. Engrs. (ASAE), St. Joseph, MI, USA

5. ASCE Task Committee on Application of Artificial Neural Networks in Hydrology. (2000a) Artificial neural networks in hydrology—I: preliminary concepts. J Hydrol Eng 5(2):115–123

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