Original title: Data-Driven Approaches for Improved Evapotranspiration Modelling with Limited Data
Authors: Považanová, Barbora ; Čistý, Milan
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně,Fakulta stavební
Abstract: This study uses data-driven methods to estimate FAO Penman-Monteith Reference Evapotranspiration (ETo) using only temperature data. Reference evapotranspiration, as an important variable for estimating actual evapotranspiration, is crucial in various water management tasks. However, some data for the Penman-Monteith equation is often unavailable. Thus, the need to use alternative methods emerges. The research shows DDM's effectiveness particularly when feature engineering was used. The study tested standard equations (Hargreaves Samani) and a proposed CatBOOST model with feature engineering to model ETo. The CatBOOST model achieved a higher R2 of 0.94 than the standard equations' R2 of 0.86. This result underscores DDM’s potential to refine evapotranspiration modelling for wide applications in water resource management, irrigation, and agriculture.
Keywords: data-driven methods; minimal input data; Reference evapotranspiration
Host item entry: Juniorstav 2024: Proceedings 26th International Scientific Conference Of Civil Engineering, ISBN 978-80-86433-83-7

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: https://hdl.handle.net/11012/245469

Permalink: http://www.nusl.cz/ntk/nusl-614392


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