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.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-21-5531-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China
College of Natural Resources and Environment, Northwest A&F
University, Yangling, Shaanxi, 712100, China
Jiming Jin
CORRESPONDING AUTHOR
College of Water Resources and Architectural Engineering, Northwest
A&F University, Yangling, Shaanxi, 712100, China
Departments of Watershed Sciences, Utah State University, Logan, UT
84322, USA
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Latest update: 21 Nov 2024
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.
We developed an efficient multisite and multivariate GCM downscaling method and generated...