Estimation of reference evapotranspiration via machine learning algorithms in humid and semiarid environments in Khyber Pakhtunkhwa, Pakistan-Reference-Cited by-同舟云学术

Estimation of reference evapotranspiration via machine learning algorithms in humid and semiarid environments in Khyber Pakhtunkhwa, Pakistan

Published:2022-06-23 Issue: Volume: Page:
ISSN:1735-1472
Container-title:International Journal of Environmental Science and Technology
language:en
Short-container-title:Int. J. Environ. Sci. Technol.

Author:

Gul S.^ORCID,Ren J.,Wang K.,Guo X.

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

General Agricultural and Biological Sciences,Environmental Chemistry,Environmental Engineering

Link

https://link.springer.com/content/pdf/10.1007/s13762-022-04334-1.pdf

Reference63 articles.

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3. Allen RG, Raes D PLS, Smith M (1998) Crop evapotranspiration-guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Fao, Rome 300:D05109

4. Amatya D, Skaggs R, Gregory J (1995) Comparison of methods for estimating REF-ET. J Irrig Drain Eng 121:427–435

5. Antonopoulos VZ, Antonopoulos AV (2017) Daily reference evapotranspiration estimates by artificial neural networks technique and empirical equations using limited input climate variables. Comput Electron Agric 132:86–96

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