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dc.contributor.authorJiménez-Donaire, María del Pilar
dc.contributor.authorGiráldez Cervera, Juan Vicente
dc.contributor.authorVanwalleghem, Tom
dc.date.accessioned2020-09-17T09:00:11Z
dc.date.available2020-09-17T09:00:11Z
dc.date.issued2020
dc.identifier.urihttp://hdl.handle.net/10396/20450
dc.description.abstractThe early and accurate detection of drought episodes is crucial for managing agricultural yield losses and planning adequate policy responses. This study aimed to evaluate the potential of two novel indices, static and dynamic plant water stress, for drought detection and yield prediction. The study was conducted in SW Spain (Córdoba province), covering a 13-year period (2001–2014). The calculation of static and dynamic drought indices was derived from previous ecohydrological work but using a probabilistic simulation of soil moisture content, based on a bucket-type soil water balance, and measured climate data. The results show that both indices satisfactorily detected drought periods occurring in 2005, 2006 and 2012. Both their frequency and length correlated well with annual precipitation, declining exponentially and increasing linearly, respectively. Static and dynamic drought stresses were shown to be highly sensitive to soil depth and annual precipitation, with a complex response, as stress can either increase or decrease as a function of soil depth, depending on the annual precipitation. Finally, the results show that both static and dynamic drought stresses outperform traditional indicators such as the Standardized Precipitation Index (SPI)-3 as predictors of crop yield, and the R2 values are around 0.70, compared to 0.40 for the latter. The results from this study highlight the potential of these new indicators for agricultural drought monitoring and management (e.g., as early warning systems, insurance schemes or water management tools).es_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightshttps://creativecommons.org/licenses/by/4.0/es_ES
dc.sourceWater 12(9), 2592 (2020)es_ES
dc.subjectDrought indicatorses_ES
dc.subjectDrought monitoringes_ES
dc.subjectPlant water stresses_ES
dc.subjectCrop yieldes_ES
dc.subjectSpaines_ES
dc.titleEvaluation of Drought Stress in Cereal through Probabilistic Modelling of Soil Moisture Dynamicses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.3390/w12092592es_ES
dc.relation.projectIDGobierno de España. PID2019-109924RB-I00es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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