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Uncertainty in climate change impact studies for irrigated maize cropping systems in southern Spain

  • This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability. Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, three sowing dates, and three maize cultivars to the uncertainty in simulated yields. The water allocation strategies were derived from historical records of farmer's allocation patterns in drip-irrigation scheme of the Genil-Cabra region, Spain (2014-2017). By considering combinations of allocation strategies, the adjusted R-2 values (showing the degree of agreement between simulated and observed yields) increased by 29% compared to unrealistic assumptions of considering only near optimal or deficit irrigation scheduling. The factor decomposition analysis based on historic climate showed that irrigation strategies was the main driver of uncertainty in simulated yields (66%).This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability. Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, three sowing dates, and three maize cultivars to the uncertainty in simulated yields. The water allocation strategies were derived from historical records of farmer's allocation patterns in drip-irrigation scheme of the Genil-Cabra region, Spain (2014-2017). By considering combinations of allocation strategies, the adjusted R-2 values (showing the degree of agreement between simulated and observed yields) increased by 29% compared to unrealistic assumptions of considering only near optimal or deficit irrigation scheduling. The factor decomposition analysis based on historic climate showed that irrigation strategies was the main driver of uncertainty in simulated yields (66%). However, under temperature increase scenarios, the contribution of crop model and cultivar choice to uncertainty in simulated yields were as important as irrigation strategy. This was partially due to different model structure in processes related to the temperature responses. Our study calls for including information on irrigation strategies conducted by farmers to reduce the uncertainty in simulated yields at field scale.show moreshow less

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Author details:Bahareh Kamali, Ignacio J. Lorite, Heidi A. Webber, Ehsan Eyshi Rezaei, Clara Gabaldon-Leal, Claas NendelORCiDGND, Stefan Siebert, Juan Miguel Ramirez-Cuesta, Frank Ewert, Jonathan J. Ojeda
DOI:https://doi.org/10.1038/s41598-022-08056-9
ISSN:2045-2322
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/35260727
Title of parent work (English):Scientific reports
Publisher:Macmillan Publishers Limited,
Place of publishing:London
Publication type:Article
Language:English
Date of first publication:2022/03/08
Publication year:2022
Release date:2024/06/14
Volume:12
Issue:1
Article number:4049
Number of pages:13
Funding institution:Projekt DEAL
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie
DDC classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer review:Referiert
Publishing method:Open Access / Gold Open-Access
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License (German):License LogoCC-BY - Namensnennung 4.0 International
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