Parametrization of the priestley taylor model and its comparison with artificial intelligence machine learning and statistical models for evapotranspiration estimation over sugarcane and chickpea crops

dc.contributor.guide	Nain, A. S.
dc.coverage.spatial
dc.creator.researcher	Satpathi, Anurag
dc.date.accessioned	2025-12-12T08:40:11Z
dc.date.available	2025-12-12T08:40:11Z
dc.date.awarded	2023
dc.date.completed	2023
dc.date.registered	2020
dc.description.abstract	Available newline
dc.description.note
dc.format.accompanyingmaterial	CD
dc.format.dimensions
dc.format.extent	95 p. p.
dc.identifier.researcherid
dc.identifier.uri	http://hdl.handle.net/10603/680335
dc.language	English
dc.publisher.institution	Department of Agrometeorology
dc.publisher.place	Pantnagar
dc.publisher.university	G.B.Pant University of Agriculture and Technology
dc.relation	Reference given
dc.rights	university
dc.source.university	University
dc.subject.keyword	Agricultural Sciences
dc.subject.keyword	Agriculture
dc.subject.keyword	Agriculture Multidisciplinary
dc.subject.keyword	Life Sciences
dc.subject.keyword	Meteorology
dc.title	Parametrization of the priestley taylor model and its comparison with artificial intelligence machine learning and statistical models for evapotranspiration estimation over sugarcane and chickpea crops
dc.title.alternative
dc.type.degree	Ph.D.