气候变化领域集成服务门户(CCPortal): Regionalization and parameterization of a hydrologic model significantly affect the cascade of uncertainty in climate-impact projections

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DOI	10.1007/s00382-019-04664-w
	Regionalization and parameterization of a hydrologic model significantly affect the cascade of uncertainty in climate-impact projections
	Ashraf Vaghefi S.; Iravani M.; Sauchyn D.; Andreichuk Y.; Goss G.; Faramarzi M.
发表日期	2019
ISSN	0930-7575
起始页码	2861
结束页码	2886
卷号	53 期号:2020-05-06
英文摘要	Climate-impact projections are subject to uncertainty arising from climate models, greenhouse gases emission scenarios, bias correction and downscaling methods (BCDS), and the impact models. We studied the effects of hydrological model parameterization and regionalization (HM-P and HM-R) on the cascade of uncertainty. We developed a new, widely-applicable approach that improves our understanding of how HM-P and HM-R along with other uncertainty drivers contribute to the overall uncertainty in climate-impact projections. We analyzed uncertainties arising from general circulation models (GCMs), representative concertation pathways, BCDS, evapotranspiration calculation methods, and specifically HM-P and HM-R. We used the Soil and Water Assessment Tool, a semi-physical process-based hydrologic model with a high capability of parameterization, to project blue and green water resources for historical (1983–2007), near future (2010–2035) and far future (2040–2065) periods in Alberta, a western province of Canada. We developed an Analysis of Variance (ANOVA)-Sequential Uncertainty Fitting Program approach, to decompose the overall uncertainty into contributions of single drivers using the projected blue and green water resources. The monthly analyses of projected water resources showed that HM-P and HM-R contribute 21–51% and 15–55% to the blue water, and 20–48% and 15–50% to the green water overall uncertainty in near future and far future, respectively. Overall, we found that in spring and summer seasons uncertainty arising from HM-P and HM-R dominates other uncertainty sources, e.g. GCMs. We also found that global climate models are another dominant source of uncertainty in future impact projections. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
英文关键词	ANOVA-SUFI-2; Climate change; Natural climate variability; SWAT; Uncertainty analysis; Uncertainty decomposition
语种	英语
scopus关键词	atmospheric general circulation model; climate change; climate variation; decomposition analysis; hydrological modeling; parameterization; regionalization; soil and water assessment tool; uncertainty analysis; variance analysis
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/146064
作者单位	Watershed Science and Modelling Laboratory, Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB T6G 2E3, Canada; Alberta Biodiversity Monitoring Institute, University of Alberta, Edmonton, AB, Canada; Prairie Adaptation Research Collaborative, University of Regina, Regina, SK, Canada; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
推荐引用方式 GB/T 7714	Ashraf Vaghefi S.,Iravani M.,Sauchyn D.,et al. Regionalization and parameterization of a hydrologic model significantly affect the cascade of uncertainty in climate-impact projections[J],2019,53(2020-05-06).
APA	Ashraf Vaghefi S.,Iravani M.,Sauchyn D.,Andreichuk Y.,Goss G.,&Faramarzi M..(2019).Regionalization and parameterization of a hydrologic model significantly affect the cascade of uncertainty in climate-impact projections.Climate Dynamics,53(2020-05-06).
MLA	Ashraf Vaghefi S.,et al."Regionalization and parameterization of a hydrologic model significantly affect the cascade of uncertainty in climate-impact projections".Climate Dynamics 53.2020-05-06(2019).