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Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: A review

Agricultural robots; Evapotranspiration; Neural networks; Water supply; Weather forecasting; Artificial intelligence techniques; Extreme learning machine; Fao penman monteiths; Food and agriculture organizations; Irrigation projects; Penman-Monteith equations; Reference evapotranspiration; Weather p...

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Main Authors: Abdullah S.S., Malek M.A.
Other Authors: 57213171981
Format: Review
Published: Inderscience Publishers 2023
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spelling my.uniten.dspace-229982023-05-29T14:14:01Z Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: A review Abdullah S.S. Malek M.A. 57213171981 55636320055 Agricultural robots; Evapotranspiration; Neural networks; Water supply; Weather forecasting; Artificial intelligence techniques; Extreme learning machine; Fao penman monteiths; Food and agriculture organizations; Irrigation projects; Penman-Monteith equations; Reference evapotranspiration; Weather parameters; Learning systems; artificial intelligence; artificial neural network; climate conditions; empirical analysis; evapotranspiration; Food and Agricultural Organization; machine learning; Penman-Monteith equation; prediction; United Nations Evapotranspiration is a fundamental requirement in the planning and management of irrigation projects. Methods of predicting evapotranspiration (ET) are numerous, but the Food and Agriculture Organization (FAO) of the United Nations adopted the FAO Penman-Monteith (PM) equation, as the method which provides the most accurate results for the prediction of reference evapotranspiration (ET0) in all regions and for all weather conditions. The main identified drawback in the application of this method is the wide variety of weather parameters required for the prediction. To overcome this problem, artificial neural networks (ANNs) models have been proposed to simulate the nonlinear, dynamic ET0 processes. This paper highlights both the traditional empirical PM method, and the enhancement obtained by the utilisation of ANN techniques in predicting ET0. � 2016 Inderscience Enterprises Ltd. Final 2023-05-29T06:14:01Z 2023-05-29T06:14:01Z 2016 Review 10.1504/IJW.2016.073741 2-s2.0-84953339870 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953339870&doi=10.1504%2fIJW.2016.073741&partnerID=40&md5=69ecfe4c19a9417cb6c485bd92c53a61 https://irepository.uniten.edu.my/handle/123456789/22998 10 1 55 66 Inderscience Publishers Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Agricultural robots; Evapotranspiration; Neural networks; Water supply; Weather forecasting; Artificial intelligence techniques; Extreme learning machine; Fao penman monteiths; Food and agriculture organizations; Irrigation projects; Penman-Monteith equations; Reference evapotranspiration; Weather parameters; Learning systems; artificial intelligence; artificial neural network; climate conditions; empirical analysis; evapotranspiration; Food and Agricultural Organization; machine learning; Penman-Monteith equation; prediction; United Nations
author2 57213171981
author_facet 57213171981
Abdullah S.S.
Malek M.A.
format Review
author Abdullah S.S.
Malek M.A.
spellingShingle Abdullah S.S.
Malek M.A.
Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: A review
author_sort Abdullah S.S.
title Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: A review
title_short Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: A review
title_full Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: A review
title_fullStr Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: A review
title_full_unstemmed Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: A review
title_sort empirical penman-monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: a review
publisher Inderscience Publishers
publishDate 2023
_version_ 1806427320463917056
score 13.214268

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