气候变化领域集成服务门户(CCPortal): Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China

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DOI	10.1016/j.atmosres.2020.105331
	Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China
	Zhang L.; Yuan F.; Wang B.; Ren L.; Zhao C.; Shi J.; Liu Y.; Jiang S.; Yang X.; Chen T.; Liu S.
发表日期	2021
ISSN	0169-8095
卷号	249
英文摘要	Extreme flow projections are of considerable necessity for flood and drought disaster prevention and sustainable water resources management to adapt to future climate change. However, these projections are usually associated with large uncertainties arising from different sources. A numerical modeling system including three emission scenarios (ESs), four climate models (CMs), four statistical downscaling (SD) methods, four hydrological modeling (HM) schemes, and four probability distribution (PD) functions was established in this study to project future extreme flow changes at basin scales. This modeling system was employed in the following three watersheds with different climatic and topographical characteristics in China: The Upper Ganjiang River basin (UGRB) in the humid region, the Laoha River basin (LRB) in the semi-arid region, and the Yellow River source region (YRSR) in the semi-humid region. Subsequently, the analysis of variance approach (ANOVA) was used to quantify the contribution of different uncertainty sources in extreme flow projections. Results show that extreme high flow was projected to increase in all basins. By contrast, extreme low flow would decrease in UGRB, and inconsistent change signals were found in LRB and YRSR. The ANOVA-based assessment reveals that CM is generally the dominant uncertainty source for mean monthly streamflow and extreme low flow projections. ES explains a large proportion of total uncertainty for extreme low flow projection in the 2060s in UGRB because of the large difference in non-precipitation frequency projected under different ESs. SD is the main uncertainty source in extreme high flow projection in UGRB where extreme precipitation events frequently occur. Compared with other basins, HM produces relatively high uncertainty in LRB due to its inferior performance in historical streamflow simulations. PD contributes a low percentage of uncertainty in extreme flow projections. Interactions among uncertainty sources even produce larger uncertainties than most individual sources. Although future extreme flow projections are associated with non-negligible uncertainties, the projected remarkable changes in extreme high and low flows indicate that stakeholders should take certain measures to mitigate flood risks in the three basins and alleviate drought risks in UGRB © 2020 Elsevier B.V.
英文关键词	Climate change; Climate model; Extreme flow projection; Hydrological model; Statistical downscaling method; Uncertainty
语种	英语
scopus关键词	Analysis of variance (ANOVA); Climate change; Climate models; Disaster prevention; Drought; Floods; Numerical methods; Probability distributions; Risk assessment; Rivers; Stream flow; Water conservation; Watersheds; Extreme precipitation events; Flood and drought disaster; Ganjiang river basin; Hydrological modeling; Precipitation frequency; Statistical downscaling; Streamflow simulations; Sustainable water resources; Uncertainty analysis; climate change; climate modeling; downscaling; extreme event; hydrological modeling; quantitative analysis; river basin; uncertainty analysis; watershed; China; Gan River; Jiangxi; Laoha River; Nei Monggol; Yellow River
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/145218
作者单位	College of Hydrology and Water Resources, Hohai University, 1 Xikang Road, Nanjing, 210098, China; Hydrology Bureau, Yellow River Conservancy Commission, 12 East Chengbei Road, Zhengzhou, 540004, China; State Key Laboratory of Hydrology–Water Resources and Hydraulic Engineering, Hohai University, 1 Xikang Road, Nanjing, 210098, China; Hydrology and Water Resources Department, Nanjing Hydraulic Research Institute, 225 Guangzhou Road, Nanjing, 210029, China
推荐引用方式 GB/T 7714	Zhang L.,Yuan F.,Wang B.,et al. Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China[J],2021,249.
APA	Zhang L..,Yuan F..,Wang B..,Ren L..,Zhao C..,...&Liu S..(2021).Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China.Atmospheric Research,249.
MLA	Zhang L.,et al."Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China".Atmospheric Research 249(2021).