Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia

Wang, B; Liu, DL; Waters, C; Yu, Q

Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia

Wang, B

Liu, DL Waters, C Yu, Q

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Publication Type:: Journal Article
Citation:: Climatic Change, 2018, 151 (2), pp. 259 - 273
Issue Date:: 2018-11-01

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Field	Value	Language
dc.contributor.author	Wang, B https://orcid.org/0000-0002-6422-5802	en_US
dc.contributor.author	Liu, DL	en_US
dc.contributor.author	Waters, C	en_US
dc.contributor.author	Yu, Q https://orcid.org/0000-0001-6950-1821	en_US
dc.date.issued	2018-11-01	en_US
dc.identifier.citation	Climatic Change, 2018, 151 (2), pp. 259 - 273	en_US
dc.identifier.issn	0165-0009	en_US
dc.identifier.uri	http://hdl.handle.net/10453/130948
dc.description.abstract	© 2018, Springer Nature B.V. Future climate projections and impact analyses are pivotal to evaluate the potential change in crop yield under climate change. Impact assessment of climate change is also essential to prepare and implement adaptation measures for farmers and policymakers. However, there are uncertainties associated with climate change impact assessment when combining crop models and climate models under different emission scenarios. This study quantifies the various sources of uncertainty associated with future climate change effects on wheat productivity at six representative sites covering dry and wet environments in Australia based on 12 soil types and 12 nitrogen application rates using one crop model driven by 28 global climate models (GCMs) under two representative concentration pathways (RCPs) at near future period 2021–2060 and far future period 2061–2100. We used the analysis of variance (ANOVA) to quantify the sources of uncertainty in wheat yield change. Our results indicated that GCM uncertainty largely dominated over RCPs, nitrogen rates, and soils for the projections of wheat yield at drier locations. However, at wetter sites, the largest share of uncertainty was nitrogen, followed by GCMs, soils, and RCPs. In addition, the soil types at two northern sites in the study area had greater effects on yield change uncertainty probably due to the interaction effect of seasonal rainfall and soil water storage capacity. We concluded that the relative contributions of different uncertainty sources are dependent on climatic location. Understanding the share of uncertainty in climate impact assessment is important for model choice and will provide a basis for producing more reliable impact assessment.	en_US
dc.relation.ispartof	Climatic Change	en_US
dc.relation.isbasedon	10.1007/s10584-018-2306-z	en_US
dc.subject.classification	Meteorology & Atmospheric Sciences	en_US
dc.title	Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	151	en_US
utslib.for	0703 Crop and Pasture Production	en_US
utslib.for	0502 Environmental Science and Management	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	151	en_US

Abstract:

© 2018, Springer Nature B.V. Future climate projections and impact analyses are pivotal to evaluate the potential change in crop yield under climate change. Impact assessment of climate change is also essential to prepare and implement adaptation measures for farmers and policymakers. However, there are uncertainties associated with climate change impact assessment when combining crop models and climate models under different emission scenarios. This study quantifies the various sources of uncertainty associated with future climate change effects on wheat productivity at six representative sites covering dry and wet environments in Australia based on 12 soil types and 12 nitrogen application rates using one crop model driven by 28 global climate models (GCMs) under two representative concentration pathways (RCPs) at near future period 2021–2060 and far future period 2061–2100. We used the analysis of variance (ANOVA) to quantify the sources of uncertainty in wheat yield change. Our results indicated that GCM uncertainty largely dominated over RCPs, nitrogen rates, and soils for the projections of wheat yield at drier locations. However, at wetter sites, the largest share of uncertainty was nitrogen, followed by GCMs, soils, and RCPs. In addition, the soil types at two northern sites in the study area had greater effects on yield change uncertainty probably due to the interaction effect of seasonal rainfall and soil water storage capacity. We concluded that the relative contributions of different uncertainty sources are dependent on climatic location. Understanding the share of uncertainty in climate impact assessment is important for model choice and will provide a basis for producing more reliable impact assessment.

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http://hdl.handle.net/10453/130948