Climate Dynamics

, Volume 47, Issue 1–2, pp 191–209 | Cite as

Assessment of climate change impacts on watershed in cold-arid region: an integrated multi-GCM-based stochastic weather generator and stepwise cluster analysis method

  • X. W. Zhuang
  • Y. P. LiEmail author
  • G. H. Huang
  • J. Liu


An integrated multi-GCM-based stochastic weather generator and stepwise cluster analysis (MGCM-SWG–SCA) method is developed, through incorporating multiple global climate models (MGCM), stochastic weather generator (SWG), and stepwise-clustered hydrological model (SCHM) within a general framework. MGCM-SWG–SCA can investigate uncertainties of projected climate changes as well as create watershed-scale climate projections from large-scale variables. It can also assess climate change impacts on hydrological processes and capture nonlinear relationship between input variables and outputs in watershed systems. MGCM-SWG–SCA is then applied to the Kaidu watershed with cold-arid characteristics in the Xinjiang Uyghur Autonomous Region of northwest China, for demonstrating its efficiency. Results reveal that the variability of streamflow is mainly affected by (1) temperature change during spring, (2) precipitation change during winter, and (3) both temperature and precipitation changes in summer and autumn. Results also disclose that: (1) the projected minimum and maximum temperatures and precipitation from MGCM change with seasons in different ways; (2) various climate change projections can reproduce the seasonal variability of watershed-scale climate series; (3) SCHM can simulate daily streamflow with a satisfactory degree, and a significant increasing trend of streamflow is indicated from future (2015–2035) to validation (2006–2011) periods; (4) the streamflow can vary under different climate change projections. The findings can be explained that, for the Kaidu watershed located in the cold-arid region, glacier melt is mainly related to temperature changes and precipitation changes can directly cause the variability of streamflow.


Climate change Cold-arid Multi-GCM Stochastic weather generator Stepwise cluster analysis Watershed 



This research was supported by the Natural Sciences Foundation of China (51379075 and 51190095), the National Natural Science Foundation for Distinguished Young Scholar (51225904), the State Key Laboratory of Desert and Oasis Ecology at Xinjiang Institute of Ecology and Geography, and the Fundamental Research Funds for the Central Universities (2015XS96). The authors are grateful to the editors and the anonymous reviewers for their insightful comments and helpful suggestions. The authors would also like to thank Dr. X.Q. Wang at the University of Regina providing the packagee of rSCA.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • X. W. Zhuang
    • 1
  • Y. P. Li
    • 1
    • 2
    Email author
  • G. H. Huang
    • 1
    • 2
  • J. Liu
    • 1
  1. 1.MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, Sino-Canada Resources and Environmental Research AcademyNorth China Electric Power UniversityBeijingChina
  2. 2.Environmental Systems Engineering Program, Faculty of Engineering and Applied ScienceUniversity of ReginaReginaCanada

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