干旱区生态环境知识资源中心(Arid): 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, Limin; Yuan, Fei; Wang, Bing; Ren, Liliang; Zhao, Chongxu; Shi, Jiayong; Liu, Yi; Jiang, Shanhu; Yang, Xiaoli; Chen, Tao; Liu, Shuya
通讯作者	Yuan, F (corresponding author), Hohai Univ, Coll Hydrol & Water Resources, 1 Xikang Rd, Nanjing 210098, Peoples R China.
来源期刊	ATMOSPHERIC RESEARCH
ISSN	0169-8095
EISSN	1873-2895
出版年	2021
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
英文关键词	Climate change Extreme flow projection Uncertainty Climate model Hydrological model Statistical downscaling method
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000596911500003
WOS关键词	CHANGE IMPACTS ; RIVER-BASIN ; HYDROLOGICAL PROJECTIONS ; RCP SCENARIOS ; MODEL ; SURFACE ; RUNOFF ; PARAMETERIZATION ; FREQUENCY ; REGIMES
WOS类目	Meteorology & Atmospheric Sciences
WOS研究方向	Meteorology & Atmospheric Sciences
来源机构	河海大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/347752
作者单位	[Zhang, Limin; Yuan, Fei; Ren, Liliang; Zhao, Chongxu; Shi, Jiayong; Liu, Yi; Jiang, Shanhu; Yang, Xiaoli; Liu, Shuya] Hohai Univ, Coll Hydrol & Water Resources, 1 Xikang Rd, Nanjing 210098, Peoples R China; [Wang, Bing] Yellow River Conservancy Commiss, Hydrol Bur, 12 East Chengbei Rd, Zhengzhou 540004, Peoples R China; [Ren, Liliang] Hohai Univ, State Key Lab HydrologyWater Resources & Hydraul, 1 Xikang Rd, Nanjing 210098, Peoples R China; [Chen, Tao] Nanjing Hydraul Res Inst, Hydrol & Water Resources Dept, 225 Guangzhou Rd, Nanjing 210029, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Limin,Yuan, Fei,Wang, Bing,et al. Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China[J]. 河海大学,2021,249.
APA	Zhang, Limin.,Yuan, Fei.,Wang, Bing.,Ren, Liliang.,Zhao, Chongxu.,...&Liu, Shuya.(2021).Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China.ATMOSPHERIC RESEARCH,249.
MLA	Zhang, Limin,et al."Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China".ATMOSPHERIC RESEARCH 249(2021).