Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the  Jing River of China

Li, Zhi; Jin, Jiming

doi:https://doi.org/10.5194/hess-21-5531-2017

Articles | Volume 21, issue 11

https://doi.org/10.5194/hess-21-5531-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Coupled terrestrial-aquatic approaches to watershed-scale...

https://doi.org/10.5194/hess-21-5531-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 21, issue 11

Research article

|

13 Nov 2017

Research article |

| 13 Nov 2017

Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China

Zhi Li and Jiming Jin

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Final revised paper (published on 13 Nov 2017)
Preprint (discussion started on 24 May 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

SC1: 'Referee comment on “Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method”', Zilefac Elvis ASONG, 23 Jun 2017
- AC3: 'Response to Dr Asong', Zhi Li, 02 Oct 2017
RC1: 'Referee Report', Anonymous Referee #1, 28 Jun 2017
- AC1: 'Response to Dr Asong', Zhi Li, 02 Oct 2017
RC2: 'Comments on "Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method"', Anonymous Referee #2, 14 Sep 2017
- AC2: 'Response to anonymous referee #2', Zhi Li, 02 Oct 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish as is (02 Oct 2017) by xuesong zhang

Short summary

We developed an efficient multisite and multivariate GCM downscaling method and generated climate change scenarios for SWAT to evaluate the streamflow variability within a watershed in China. The application of the ensemble techniques enables us to better quantify the model uncertainties. The peak values of precipitation and streamflow have a tendency to shift from the summer to spring season over the next 30 years. The number of extreme flooding and drought events will increase.