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Spatial and temporal variations in hydro-climatic variables and runoff in response to climate change in the Luanhe River basin, China

  • Weiguang WangEmail author
  • Jiande Wei
  • Quanxi Shao
  • Wanqiu Xing
  • Bin Yong
  • Zhongbo Yu
  • Xiyun Jiao
Original Paper

Abstract

Climate change in North China would result in significant changes in temperature, precipitation and their spatial/temporal distributions. Consequently, these induced changes will have profound effects on the hydrological cycle and water resources in both agricultural and natural ecosystems. Panjiakou reservoir in the middle Luanhe River basin—a tributary of the Haihe River basin—is one of the important sources of water for industrial and agricultural development in Beijing, Tianjin and Hebei province, China. Any significant change in the magnitude and/or timing of runoff from the reservoir induced by changes in climatic variables would have significant implication for the economic prosperity in North China. This paper investigates the impacts of climate change on hydrological processes in the Luanhe River basin as follows. Firstly, spatial and temporal patterns of precipitation, temperature and runoff at both annual and seasonal scales from 1957 to 2000 in the Luanhe River basin are analyzed using Mann–Kendall trend analysis, linear regression methods and inverse distance weighted interpolation. For the impact study, four Global Climate Models (GCMs) (named CSIRO, HadCM3, CNRM and GFDL) were used to produce precipitation and temperature data under A2 scenario by mean of a widely used quantile–quantile transformation. Projected meteorological variables were used to force a two-parameter hydrologic model to simulate the hydrological response to climate change in the future (2021–2050). Moreover, a sensitivity analysis is conducted to assess how precipitation and temperature affect the runoff. Results suggested that most part of the Luanhe River basin was dominated by significant increasing trends of temperature and no significant trends of precipitation in annual and seasonal scale during the past decades. Annual, spring and autumn runoffs present significant decreasing trends in the Panjiakou reservoir basin. Meanwhile, runoff is more strongly related to precipitation than to temperature. All GCMs projected precipitation and temperature series after bias correction indicated increasing temperature and increasing precipitation trends for the period 2021–2050 except that CNRM showed a slight decreasing trend in precipitation. Great enhancements can be found in projected runoff except CNRM by driving the two-parameter water balance model. The study provides valuable information on the assessment of the impact of the climate change on water resources in the Luanhe River basin as well for allocating and designing water resources projects.

Keywords

Climate change Luanhe River basin Bias correction Sensitivity analysis Panjiakou reservoir 

Notes

Acknowledgments

This work was financed by the National Key Technologies Research and Development Program of China during the 12th Five-year Plan Period (2013BAC10B01), the National Natural Science Foundation of China (51379057), Commonweal Program of Chinese Ministry of Water Resources (201301014), the Program for Graduate Education Innovation Project in Jiangsu Province (CXLX13_241), QingLan Project, the Fund of Advanced Science and Technology Innovation in Colleges and Universities in Jiangsu Province, the Program for Distinguished Talents in Hohai University, a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). Moreover, cordial thanks should be extended to the associated editor and two anonymous referees for their valuable comments which greatly improved the quality of this paper.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Weiguang Wang
    • 1
    • 2
    Email author
  • Jiande Wei
    • 1
    • 2
  • Quanxi Shao
    • 3
  • Wanqiu Xing
    • 1
    • 2
  • Bin Yong
    • 1
  • Zhongbo Yu
    • 4
  • Xiyun Jiao
    • 1
  1. 1.State Key Laboratory of Hydrology-Water Resources and Hydraulic EngineeringHohai UniversityNanjingChina
  2. 2.College of Hydrology and Water ResourcesHohai UniversityNanjingChina
  3. 3.CSIRO Computational InformaticsWembleyAustralia
  4. 4.Department of GeoscienceUniversity of Nevada Las VegasLas VegasUSA

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