Enhancing irrigation water management based on ETo prediction using machine learning to mitigate climate change

Mohamed A. Youssefa Department of Agricultural Engineering, Faculty of Agriculture, Ain Shams University, Cairo, EgyptView further author information

R. Troy Petersb Department of Biological Systems Engineering, Washington State University, Pullman, Washington, USAView further author information

Mohammed El-Shirbenyc National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt;d Arab Organization for Agricultural Development (AOAD), Cairo, EgyptView further author information

Ahmed M. Abd-ElGawade Plant Production Department, College of Food & Agriculture Sciences, King Saud University, Riyadh, Saudi ArabiaView further author information

Younes M. Rashadf Plant Protection and Biomolecular Diagnosis Department, Arid Lands Cultivation Research Institute (ALCRI), City of Scientific Research and Technological Applications (SRTA-City), New BorgEl-Arab, EgyptCorrespondence[email protected]

https://orcid.org/0000-0002-7702-8023 View further author information

Mohamed Hafezg Land and Water Technologies Department, Arid Lands Cultivation Research Institute (ALCRI), City of Scientific Research and Technological Applications (SRTA-City), New BorgEl-Arab, EgyptView further author information

Yasser Arafaa Department of Agricultural Engineering, Faculty of Agriculture, Ain Shams University, Cairo, EgyptView further author information

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Enhancing irrigation water management based on ETo prediction using machine learning to mitigate climate change

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Enhancing irrigation water management based on ETo prediction using machine learning to mitigate climate change

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