A climate impact attribution of historical rice yields in Sri Lanka using three crop models

Sri Lanka’s rice systems are subject to low yield events that threaten national food security. Extreme climate events during the cropping season are the main cause, but whether human-induced climate change has contributed to low yield events is an open question. Here, we present an impact attributio...

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Published inScientific reports Vol. 15; no. 1; pp. 15360 - 10
Main Authors Karunaratne, A. S., Chaogejilatu, Iizumi, Toshichika
Format Journal Article
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Published London Nature Publishing Group UK 02.05.2025
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Abstract Sri Lanka’s rice systems are subject to low yield events that threaten national food security. Extreme climate events during the cropping season are the main cause, but whether human-induced climate change has contributed to low yield events is an open question. Here, we present an impact attribution analysis that quantifies the effect of climate change to the average yield in 1981–2019 and the low yield event that occurred in 2017 using factual and counterfactual climate model simulations as inputs to three process-based crop models, DSSAT, APSIM and CYGMA. All of the crop models consistently show that climate change has decreased average yield by − 4.99% to − 0.20%, compared to that without climate change. However, the effect of climate change to the 2017 event is mixed in the sign across the crop models. When using a multi-model ensemble average (MME) of the three crop models, a significant negative impact on the Yala season is detected. The large uncertainties associated with the use of different crop models also make it inconclusive whether the 2017-level low yield events would become more frequent and severer by mid-century (2031–2069) under projected climates than under the present-day climate. The same result was derived even when MME is used. These results underscore the need for improved impact attribution to inform climate negotiations on the development of climate-resilient agri-food systems in low-income countries through the Loss and Damage mechanism.
AbstractList Sri Lanka’s rice systems are subject to low yield events that threaten national food security. Extreme climate events during the cropping season are the main cause, but whether human-induced climate change has contributed to low yield events is an open question. Here, we present an impact attribution analysis that quantifies the effect of climate change to the average yield in 1981–2019 and the low yield event that occurred in 2017 using factual and counterfactual climate model simulations as inputs to three process-based crop models, DSSAT, APSIM and CYGMA. All of the crop models consistently show that climate change has decreased average yield by − 4.99% to − 0.20%, compared to that without climate change. However, the effect of climate change to the 2017 event is mixed in the sign across the crop models. When using a multi-model ensemble average (MME) of the three crop models, a significant negative impact on the Yala season is detected. The large uncertainties associated with the use of different crop models also make it inconclusive whether the 2017-level low yield events would become more frequent and severer by mid-century (2031–2069) under projected climates than under the present-day climate. The same result was derived even when MME is used. These results underscore the need for improved impact attribution to inform climate negotiations on the development of climate-resilient agri-food systems in low-income countries through the Loss and Damage mechanism.
Abstract Sri Lanka’s rice systems are subject to low yield events that threaten national food security. Extreme climate events during the cropping season are the main cause, but whether human-induced climate change has contributed to low yield events is an open question. Here, we present an impact attribution analysis that quantifies the effect of climate change to the average yield in 1981–2019 and the low yield event that occurred in 2017 using factual and counterfactual climate model simulations as inputs to three process-based crop models, DSSAT, APSIM and CYGMA. All of the crop models consistently show that climate change has decreased average yield by − 4.99% to − 0.20%, compared to that without climate change. However, the effect of climate change to the 2017 event is mixed in the sign across the crop models. When using a multi-model ensemble average (MME) of the three crop models, a significant negative impact on the Yala season is detected. The large uncertainties associated with the use of different crop models also make it inconclusive whether the 2017-level low yield events would become more frequent and severer by mid-century (2031–2069) under projected climates than under the present-day climate. The same result was derived even when MME is used. These results underscore the need for improved impact attribution to inform climate negotiations on the development of climate-resilient agri-food systems in low-income countries through the Loss and Damage mechanism.
Sri Lanka's rice systems are subject to low yield events that threaten national food security. Extreme climate events during the cropping season are the main cause, but whether human-induced climate change has contributed to low yield events is an open question. Here, we present an impact attribution analysis that quantifies the effect of climate change to the average yield in 1981-2019 and the low yield event that occurred in 2017 using factual and counterfactual climate model simulations as inputs to three process-based crop models, DSSAT, APSIM and CYGMA. All of the crop models consistently show that climate change has decreased average yield by - 4.99% to - 0.20%, compared to that without climate change. However, the effect of climate change to the 2017 event is mixed in the sign across the crop models. When using a multi-model ensemble average (MME) of the three crop models, a significant negative impact on the Yala season is detected. The large uncertainties associated with the use of different crop models also make it inconclusive whether the 2017-level low yield events would become more frequent and severer by mid-century (2031-2069) under projected climates than under the present-day climate. The same result was derived even when MME is used. These results underscore the need for improved impact attribution to inform climate negotiations on the development of climate-resilient agri-food systems in low-income countries through the Loss and Damage mechanism.Sri Lanka's rice systems are subject to low yield events that threaten national food security. Extreme climate events during the cropping season are the main cause, but whether human-induced climate change has contributed to low yield events is an open question. Here, we present an impact attribution analysis that quantifies the effect of climate change to the average yield in 1981-2019 and the low yield event that occurred in 2017 using factual and counterfactual climate model simulations as inputs to three process-based crop models, DSSAT, APSIM and CYGMA. All of the crop models consistently show that climate change has decreased average yield by - 4.99% to - 0.20%, compared to that without climate change. However, the effect of climate change to the 2017 event is mixed in the sign across the crop models. When using a multi-model ensemble average (MME) of the three crop models, a significant negative impact on the Yala season is detected. The large uncertainties associated with the use of different crop models also make it inconclusive whether the 2017-level low yield events would become more frequent and severer by mid-century (2031-2069) under projected climates than under the present-day climate. The same result was derived even when MME is used. These results underscore the need for improved impact attribution to inform climate negotiations on the development of climate-resilient agri-food systems in low-income countries through the Loss and Damage mechanism.
Sri Lanka's rice systems are subject to low yield events that threaten national food security. Extreme climate events during the cropping season are the main cause, but whether human-induced climate change has contributed to low yield events is an open question. Here, we present an impact attribution analysis that quantifies the effect of climate change to the average yield in 1981-2019 and the low yield event that occurred in 2017 using factual and counterfactual climate model simulations as inputs to three process-based crop models, DSSAT, APSIM and CYGMA. All of the crop models consistently show that climate change has decreased average yield by - 4.99% to - 0.20%, compared to that without climate change. However, the effect of climate change to the 2017 event is mixed in the sign across the crop models. When using a multi-model ensemble average (MME) of the three crop models, a significant negative impact on the Yala season is detected. The large uncertainties associated with the use of different crop models also make it inconclusive whether the 2017-level low yield events would become more frequent and severer by mid-century (2031-2069) under projected climates than under the present-day climate. The same result was derived even when MME is used. These results underscore the need for improved impact attribution to inform climate negotiations on the development of climate-resilient agri-food systems in low-income countries through the Loss and Damage mechanism.
ArticleNumber 15360
Author Iizumi, Toshichika
Karunaratne, A. S.
Chaogejilatu
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Issue 1
Keywords Climate change
Crop model
Extreme event
Impact attribution
Food security
Language English
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Snippet Sri Lanka’s rice systems are subject to low yield events that threaten national food security. Extreme climate events during the cropping season are the main...
Sri Lanka's rice systems are subject to low yield events that threaten national food security. Extreme climate events during the cropping season are the main...
Abstract Sri Lanka’s rice systems are subject to low yield events that threaten national food security. Extreme climate events during the cropping season are...
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StartPage 15360
SubjectTerms 704/106/694
704/106/694/2739
704/106/694/674
Agribusiness
Agricultural production
Agriculture
Climate Change
Climate effects
Climate Models
Crop model
Crop yield
Crops
Crops, Agricultural - growth & development
Extreme event
Food security
Food systems
Humanities and Social Sciences
Humans
Impact attribution
Low income areas
Models, Theoretical
multidisciplinary
Oryza - growth & development
Rice
Science
Science (multidisciplinary)
Seasons
Sri Lanka
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Title A climate impact attribution of historical rice yields in Sri Lanka using three crop models
URI https://link.springer.com/article/10.1038/s41598-025-00262-5
https://www.ncbi.nlm.nih.gov/pubmed/40316584
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https://pubmed.ncbi.nlm.nih.gov/PMC12048595
https://doaj.org/article/01f54249d0c44d02a5608d08943ffa32
Volume 15
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