Sensitivity of WOFOST-based modelling solutions to crop parameters under climate change
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DOI: 10.1016/j.ecolmodel.2017.11.003
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Cited by:
- Bregaglio, Simone & Ginaldi, Fabrizio & Raparelli, Elisabetta & Fila, Gianni & Bajocco, Sofia, 2023. "Improving crop yield prediction accuracy by embedding phenological heterogeneity into model parameter sets," Agricultural Systems, Elsevier, vol. 209(C).
- Haowei Sun & Jinghan Ma & Li Wang, 2023. "Changes in per capita wheat production in China in the context of climate change and population growth," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 15(3), pages 597-612, June.
- Jiandong Liu & Jun Du & De-Li Liu & Hans W. Linderholm & Guangsheng Zhou & Yanling Song & Yanbo Shen & Qiang Yu, 2022. "Spatial and Temporal Variations in the Potential Yields of Highland Barley in Relation to Climate Change in Three Rivers Region of the Tibetan Plateau from 1961 to 2020," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
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Keywords
Climate scenarios; Crop parameters; Crop yield; e-FAST method; Extreme weather events; Morris’ method; Sensitivity analysis; WOFOST;All these keywords.
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