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dc.contributor.authorFontanet, Mireia
dc.contributor.authorScudiero, Elia
dc.contributor.authorSkaggs, Todd H.
dc.contributor.authorFernàndez-Garcia, Daniel
dc.contributor.authorFerrer, Francesc
dc.contributor.authorRodrigo, Gema
dc.contributor.authorBellvert, Joaquim
dc.contributor.otherProducció Vegetalca
dc.date.accessioned2020-05-18T15:05:29Z
dc.date.available2022-05-07T22:45:14Z
dc.date.issued2020-05-07
dc.identifier.citationFontanet, Mireia, Elia Scudiero, Todd H. Skaggs, Daniel Fernàndez-Garcia, Francesc Ferrer, Gema Rodrigo, and Joaquim Bellvert. 2020. "Dynamic Management Zones For Irrigation Scheduling". Agricultural Water Management 238: 106207. doi:10.1016/j.agwat.2020.106207.ca
dc.identifier.issn0378-3774ca
dc.identifier.urihttp://hdl.handle.net/20.500.12327/803
dc.description.abstractIrrigation scheduling decision-support tools can improve water use efficiency by matching irrigation recommendations to prevailing soil and crop conditions within a season. Yet, little research is available on how to support real-time precision irrigation that varies within-season in both time and space. We investigate the integration of remotely sensed NDVI time-series, soil moisture sensor measurements, and root zone simulation forecasts for in-season delineation of dynamic management zones (MZ) and for a variable rate irrigation scheduling in order to improve irrigation scheduling and crop performance. Delineation of MZ was conducted in a 5.8-ha maize field during 2018 using Sentinel-2 NDVI time-series and an unsupervised classification. The number and spatial extent of MZs changed through the growing season. A network of soil moisture sensors was used to interpret spatiotemporal changes of the NDVI. Soil water content was a significant contributor to changes in crop vigor across MZs through the growing season. Real-time cluster validity function analysis provided in-season evaluation of the MZ design. For example, the total within-MZ daily soil moisture relative variance decreased from 85% (early vegetative stages) to below 25% (late reproductive stages). Finally, using the Hydrus-1D model, a workflow for in-season optimization of irrigation scheduling and water delivery management was tested. Data simulations indicated that crop transpiration could be optimized while reducing water applications between 11 and 28.5% across the dynamic MZs. The proposed integration of spatiotemporal crop and soil moisture data can be used to support management decisions to effectively control outputs of crop × environment × management interactions.ca
dc.format.extent47ca
dc.language.isoengca
dc.publisherElsevierca
dc.relation.ispartofAgricultural Water Managementca
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleDynamic Management Zones for Irrigation Schedulingca
dc.typeinfo:eu-repo/semantics/articleca
dc.description.versioninfo:eu-repo/semantics/acceptedVersionca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.relation.projectIDEC/H2020/823965/EU/Accounting for Climate Change in Water and Agriculture Management/ACCWAca
dc.subject.udc631ca
dc.identifier.doihttps://doi.org/10.1016/j.agwat.2020.106207ca
dc.contributor.groupÚs Eficient de l'Aigua en Agriculturaca


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