Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1007/s00382-019-04664-w |
Regionalization and parameterization of a hydrologic model significantly affect the cascade of uncertainty in climate-impact projections | |
Vaghefi, Saeid Ashraf1; Iravani, Majid2; Sauchyn, David3; Andreichuk, Yuliya3; Goss, Greg4; Faramarzi, Monireh1 | |
2019-09-01 | |
发表期刊 | CLIMATE DYNAMICS |
ISSN | 0930-7575 |
EISSN | 1432-0894 |
出版年 | 2019 |
卷号 | 53页码:2861-2886 |
文章类型 | Article |
语种 | 英语 |
国家 | Canada |
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. |
英文关键词 | Uncertainty analysis Uncertainty decomposition Climate change Natural climate variability SWAT ANOVA-SUFI-2 |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000483626900023 |
WOS关键词 | RIVER-BASINS ; DAILY PRECIPITATION ; SELECTING VALUES ; INPUT VARIABLES ; WATER-QUALITY ; FUTURE ; ENSEMBLE ; OUTPUT ; TEMPERATURE ; CALIBRATION |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/186351 |
专题 | 气候变化 |
作者单位 | 1.Univ Alberta, Dept Earth & Atmospher Sci, Watershed Sci & Modelling Lab, Edmonton, AB T6G 2E3, Canada; 2.Univ Alberta, Alberta Biodivers Monitoring Inst, Edmonton, AB, Canada; 3.Univ Regina, Prairie Adaptat Res Collaborat, Regina, SK, Canada; 4.Univ Alberta, Dept Biol Sci, Edmonton, AB, Canada |
推荐引用方式 GB/T 7714 | Vaghefi, Saeid Ashraf,Iravani, Majid,Sauchyn, David,et al. Regionalization and parameterization of a hydrologic model significantly affect the cascade of uncertainty in climate-impact projections[J]. CLIMATE DYNAMICS,2019,53:2861-2886. |
APA | Vaghefi, Saeid Ashraf,Iravani, Majid,Sauchyn, David,Andreichuk, Yuliya,Goss, Greg,&Faramarzi, Monireh.(2019).Regionalization and parameterization of a hydrologic model significantly affect the cascade of uncertainty in climate-impact projections.CLIMATE DYNAMICS,53,2861-2886. |
MLA | Vaghefi, Saeid Ashraf,et al."Regionalization and parameterization of a hydrologic model significantly affect the cascade of uncertainty in climate-impact projections".CLIMATE DYNAMICS 53(2019):2861-2886. |
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