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dc.contributor.authorCabello Franco, Emilio José
dc.contributor.authorAntón García, Daniel
dc.contributor.authorRamírez Juidias, Emilio
dc.contributor.authorPerea Torres, Francisco
dc.date.accessioned2026-07-01T07:48:24Z
dc.date.available2026-07-01T07:48:24Z
dc.date.issued2025
dc.identifier.citationCabello Franco, E. J., Antón García, D., Ramírez Juidias, E., y Perea Torres, F. (2025). Optimizing water demand in citrus orchards: a novel model using evolutionary algorithms on Sentinel-1 time series data. Cogent Food and Agriculture, 11(1). https://doi.org/10.1080/23311932.2025.2544960es
dc.identifier.issn2331-1932
dc.identifier.urihttp://hdl.handle.net/20.500.12251/4407
dc.description.abstractCitrus fruits are crucial globally, impacting economies and livelihoods. However, climate change is affecting water availability and usage, posing challenges for managing water in citrus crops. This paper introduces CARP-flux, a new model designed to assess water needs in citrus orchards, specifically addressing the limitations of traditional methods under changing climates. The study was conducted in El Hundido, an irrigation village located in the Vega del Guadalquivir Valley near Cantillana, Seville (Spain), acknowledged as a significant citrus trade area at both the European and national levels. To adjust the model to contemporary climate conditions, time-series data from the Sentinel-1 Interferometric Wide (IW) satellite (VV and VH polarizations) from 2021 and 2022 were employed. Employing genetic algorithms and the Weibull distribution, the study incorporated 3D radiation models from backscatter data, a spatial interpretation of water and radiation dynamics, which, in turn, validated CARP-flux’s performance. This model proved effective in identifying land-use changes and evaluating radiation intensity, which are critical factors for understanding crop water needs in climate change scenarios. CARP-flux offers a precise alternative to the conventional Hargreaves technique for citrus groves, which underestimates water requirements in irrigated and humid regions with ample soil moisture, such as the Vega del Guadalquivir. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.es
dc.language.isoenges
dc.publisherInforma Healthcarees
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleOptimizing water demand in citrus orchards: a novel model using evolutionary algorithms on Sentinel-1 time series dataes
dc.typearticle
dc.identifier.doi10.1080/23311932.2025.2544960
dc.identifier.urlhttps://www.scopus.com/results/results.uri?s=AU-ID%2857194707076%29&sot=aut&sdt=a&origin=AuthorProfile&src=s&sort=plf-f&limit=100&sessionSearchId=6241a1f33b3a2321e6e20eb2efe27a2a
dc.issue.number1es
dc.journal.titleCogent Food and Agriculturees
dc.rights.accessRightsopenAccesses
dc.subject.keywordAlgoritmoses
dc.subject.keywordDescarbonizaciónes
dc.subject.keywordEmisiones de CO2es
dc.subject.keywordDióxido de carbonoes
dc.subject.keywordHuella de carbonoes
dc.subject.keywordCambio climáticoes
dc.subject.keywordMachine Learninges
dc.subject.keywordRedes neuronales artificialeses
dc.subject.keywordBig Dataes
dc.subject.unesco3308 Ingeniería y Tecnología del Medio Ambientees
dc.subject.unesco1203.17 Informáticaes
dc.subject.unesco1203.26 Simulaciónes
dc.subject.unesco3305.15 Ingeniería Hidráulicaes
dc.subject.unesco3305.31 Mecánica del Suelo (Construcción)es
dc.subject.unesco3305.90 Transmisión de Calor en la Edificaciónes
dc.volume.number11


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