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Dynamic Management Zones for Irrigation Scheduling
dc.contributor.author | Fontanet, Mireia | |
dc.contributor.author | Scudiero, Elia | |
dc.contributor.author | Skaggs, Todd H. | |
dc.contributor.author | Fernàndez-Garcia, Daniel | |
dc.contributor.author | Ferrer, Francesc | |
dc.contributor.author | Rodrigo, Gema | |
dc.contributor.author | Bellvert, Joaquim | |
dc.contributor.other | Producció Vegetal | ca |
dc.date.accessioned | 2020-05-18T15:05:29Z | |
dc.date.available | 2022-05-07T22:45:14Z | |
dc.date.issued | 2020-05-07 | |
dc.identifier.citation | Fontanet, 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.issn | 0378-3774 | ca |
dc.identifier.uri | http://hdl.handle.net/20.500.12327/803 | |
dc.description.abstract | Irrigation 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.extent | 47 | ca |
dc.language.iso | eng | ca |
dc.publisher | Elsevier | ca |
dc.relation.ispartof | Agricultural Water Management | ca |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | ca |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Dynamic Management Zones for Irrigation Scheduling | ca |
dc.type | info:eu-repo/semantics/article | ca |
dc.description.version | info:eu-repo/semantics/acceptedVersion | ca |
dc.rights.accessLevel | info:eu-repo/semantics/openAccess | |
dc.relation.projectID | EC/H2020/823965/EU/Accounting for Climate Change in Water and Agriculture Management/ACCWA | ca |
dc.subject.udc | 631 | ca |
dc.identifier.doi | https://doi.org/10.1016/j.agwat.2020.106207 | ca |
dc.contributor.group | Ús Eficient de l'Aigua en Agricultura | ca |
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