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Article

Evaluation of Drought Stress in Cereal through Probabilistic Modelling of Soil Moisture Dynamics

1
Department of Agronomy, University of Córdoba, 14071 Córdoba, Spain
2
Institute for Sustainable Agriculture, CSIC, 14071 Córdoba, Spain
*
Author to whom correspondence should be addressed.
Water 2020, 12(9), 2592; https://doi.org/10.3390/w12092592
Received: 24 August 2020 / Revised: 10 September 2020 / Accepted: 11 September 2020 / Published: 16 September 2020
The 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). View Full-Text
Keywords: drought indicators; drought monitoring; plant water stress; crop yield; Spain drought indicators; drought monitoring; plant water stress; crop yield; Spain
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MDPI and ACS Style

Jiménez-Donaire, M.d.P.; Giráldez, J.V.; Vanwalleghem, T. Evaluation of Drought Stress in Cereal through Probabilistic Modelling of Soil Moisture Dynamics. Water 2020, 12, 2592. https://doi.org/10.3390/w12092592

AMA Style

Jiménez-Donaire MdP, Giráldez JV, Vanwalleghem T. Evaluation of Drought Stress in Cereal through Probabilistic Modelling of Soil Moisture Dynamics. Water. 2020; 12(9):2592. https://doi.org/10.3390/w12092592

Chicago/Turabian Style

Jiménez-Donaire, María d.P.; Giráldez, Juan V.; Vanwalleghem, Tom. 2020. "Evaluation of Drought Stress in Cereal through Probabilistic Modelling of Soil Moisture Dynamics" Water 12, no. 9: 2592. https://doi.org/10.3390/w12092592

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