DOI: 10.5194/hess-24-3251-2020
论文题名: Assessment of extreme flows and uncertainty under climate change: Disentangling the uncertainty contribution of representative concentration pathways; global climate models and internal climate variability
作者: Gao C. ; Booij M.J.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2020
卷: 24, 期: 6 起始页码: 3251
结束页码: 3269
语种: 英语
Scopus关键词: Climate models
; Decision making
; Drought
; Floods
; Markov chains
; Rain
; Rivers
; Stochastic models
; Stochastic systems
; Stream flow
; Uncertainty analysis
; Watersheds
; Adaptation strategies
; ANOVA (analysis of variance)
; Daily rainfall model
; Global climate model
; Internal climate variability
; Uncertainty contributions
; Uncertainty sources
; Water resources management
; Climate change
; assessment method
; climate change
; climate modeling
; concentration (composition)
; extreme event
; global climate
; uncertainty analysis
英文摘要: Projections of streamflow, particularly of extreme flows under climate change, are essential for future water resources management and the development of adaptation strategies to floods and droughts. However, these projections are subject to uncertainties originating from different sources. In this study, we explored the possible changes in future streamflow, particularly for high and low flows, under climate change in the Qu River basin, eastern China. ANOVA (analysis of variance) was employed to quantify the contribution of different uncertainty sources from RCPs (representative concentration pathways), GCMs (global climate models) and internal climate variability, using an ensemble of 4 RCP scenarios, 9 GCMs and 1000 simulated realizations of each model-scenario combination by SDRM-MCREM (a stochastic daily rainfall model coupling a Markov chain model with a rainfall event model). The results show that annual mean flow and high flows are projected to increase and that low flows will probably decrease in 2041-2070 (2050s) and 2071-2100 (2080s) relative to the historical period of 1971-2000, suggesting a higher risk of floods and droughts in the future in the Qu River basin, especially for the late 21st century. Uncertainty in mean flows is mostly attributed to GCM uncertainty. For high flows and low flows, internal climate variability and GCM uncertainty are two major uncertainty sources for the 2050s and 2080s, while for the 2080s, the effect of RCP uncertainty becomes more pronounced, particularly for low flows. The findings in this study can help water managers to become more knowledgeable about and get a better understanding of streamflow projections and support decision making regarding adaptations to a changing climate under uncertainty in the Qu River basin. © 2020 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/162657
Appears in Collections: 气候变化与战略
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作者单位: Gao, C., Department of Water Engineering and Management, Faculty of Engineering Technology, University of Twente, Enschede, 7500 AE, Netherlands; Booij, M.J., Department of Water Engineering and Management, Faculty of Engineering Technology, University of Twente, Enschede, 7500 AE, Netherlands
Recommended Citation:
Gao C.,Booij M.J.. Assessment of extreme flows and uncertainty under climate change: Disentangling the uncertainty contribution of representative concentration pathways; global climate models and internal climate variability[J]. Hydrology and Earth System Sciences,2020-01-01,24(6)