Benchmarking of drought and climate indices for agricultural drought monitoring in Argentina
| Autor: | María Bermúdez, Ronnie J. Araneda-Cabrera, Jerónimo Puertas |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Environmental Engineering
010504 meteorology & atmospheric sciences Climate Climate Change Argentina Agricultural drought 010501 environmental sciences 01 natural sciences Crop Environmental Chemistry Soybean yield Temporal scales Waste Management and Disposal 0105 earth and related environmental sciences business.industry Phenology Crop yield fungi food and beverages Agriculture Regression analysis Drought indices Benchmarking Pollution Statistical models Droughts Teleconnections Environmental science Seasons Physical geography Statistical model business Teleconnection |
| Zdroj: | Digibug. Repositorio Institucional de la Universidad de Granada instname RUC. Repositorio da Universidade da Coruña |
| Popis: | Ronnie Araneda gratefully acknowledges financial support from the Spanish Regional Government of Galicia (Xunta de Galicia) and the European Union through the predoctoral grant reference ED481A- 2018/162. María Bermúdez was supported by the European Union H2020 Research and Innovation Program under the Marie Skłodowska-Curie Grant Agreement No. 754446 and the Research and Transfer Fund of the University of Granada - Athenea3i. Site-specific studies are required to identify suitable drought indices (DIs) for assessing and predicting droughtrelated impacts. This study presents a benchmark of eight DIs and 19 large-scale climate indices (CIs) to monitor agricultural drought in Argentina. First, the link between the CIs and DIs was investigated at the departmentaladministrative level and at different temporal scales. Then, the effectiveness of the DIs in explaining the variability of crop yields, understood as impacts of agricultural droughts, was evaluated using statistical regression models. Soybeans were used as the reference crop. Additionally, the performances of DIs and CIs in explaining the variability of crop yields were compared. The CIs located in the Pacific Ocean (El Niño 3.4 and El Niño 4) were found to have the best correlations with the DIs (R values up to 0.49). These relationships were stronger with longer temporal aggregations and during the wet and hot seasons (summer), showing a significant role in the triggering of droughts in Argentina. The DIs that best corelatedwith CIswere those that included temperature in their calculations (STCI, SVHI, and SPEI). The impacts of droughts on soybean productionwere better explained using DIs than with CIs (up to 89% vs 8% of variability explained) as predictors of the statistical models. SVHI-6 and SPEI-6, depending on the area of interest, were, during the phenological period of crop growth (summer), the most effective DIs in explaining annual variations in soybean yields. The results may be of interest in water resource management, drought risk management, and the Argentinean soybean production sector. Furthermore, they provide a foundation for future studies aimed at forecasting agricultural droughts and their impacts. Spanish Regional Government of Galicia (Xunta de Galicia) European Commission ED481A-2018/162 European Union H2020 Research and Innovation Program under the Marie SkodowskaCurie Grant Agreement No. 754446 Research and Transfer Fund of the University of Granada - Athenea3i |
| Databáze: | OpenAIRE |
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