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https://doi.org/10.5194/hess-2020-25
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2020-25
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 14 Feb 2020

Submitted as: research article | 14 Feb 2020

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This preprint is currently under review for the journal HESS.

Assessment of extreme flows and uncertainty under climate change: disentangling the contribution of RCPs, GCMs and internal climate variability

Chao Gao1,2, Martijn J. Booij2, and Yue-Ping Xu1 Chao Gao et al.
  • 1Institute of Hydrology and Water Resources, Zhejiang University, Hangzhou 310058, China
  • 2Water Engineering and Management Group, Faculty of Engineering Technology, University of Twente, Enschede 7500 AE, the Netherlands

Abstract. Projections of streamflow, particularly of extreme flows under climate change are essential for future water resources management and development of adaptation strategies to floods and droughts. However, these projections are subject to uncertainties originating from different sources. In this study, we explore the possible changes in future streamflow, particularly for high and low flows, under climate change in the Qu River basin, East China. ANOVA (Analysis of Variance) is 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 four RCP scenarios, nine GCMs and 1,000 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 low flows will probably decrease in 2041–2070 (2050s) and 2071–2100 (2080s) relative to the historical period 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 is becoming more pronounced, particularly for low flows. The findings in this study can help water managers to get a better knowledge and understanding of streamflow projections and support decision making on adaptions to changing climate under uncertainty in the Qu River basin.

Chao Gao et al.

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Short summary
This paper aims to study the impacts of climate change on high and low flows and quantify the contribution of three uncertainty sources from RCPs, GCMs, and internal climate variability in extreme flows. Internal climate variability was reflected through using our newly-developed stochastic rainfall model. The results show that internal climate variability and GCM uncertainty are dominant in high flows, while GCM and RCP uncertainty are more important in low flows, especially for far future.
This paper aims to study the impacts of climate change on high and low flows and quantify the...
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