Advertisement

Theoretical and Applied Climatology

, Volume 136, Issue 1–2, pp 489–497 | Cite as

Applications of multiple change point detections to monthly streamflow and rainfall in Xijiang River in southern China, part II: trend and mean

  • Yongqin David Chen
  • Jianmin JiangEmail author
  • Yuxiang Zhu
  • Changxing Huang
  • Qiang Zhang
Original Paper
  • 88 Downloads

Abstract

This article, as part II, illustrates applications of other two algorithms, i.e., the scanning F test of change points in trend and the scanning t test of change points in mean, to both series of the normalized streamflow index (NSI) at Makou section in the Xijiang River and the normalized precipitation index (NPI) over the watershed of Xijiang River. The results from these two tests show mainly positive coherency of changes between the NSI and NPI. However, some minor negative coherency patches may expose somewhat impacts of human activities, but they were often associated with nearly normal climate periods. These suggest that the runoff still depends upon well the precipitation in the Xijiang catchment. The anthropogenic disturbances have not yet reached up to violating natural relationship on the whole in this river.

Keywords

Change point Scanning detection Streamflow Rainfall Southern China 

Notes

Acknowledgements

This work is jointly supported by the Direct Grant from The Chinese University of Hong Kong, China (project no. 4052134), by the National Key Research and Development Program of China (2017YFC1502005), the China Meteorological Administration Special Found for Climate Change (CCSF201806), the China Meteorological Administration Special Found for Development of Weather Forecasting Key Technologies (YBGJXM(2018) 03-15), the National Natural Science Foundation of China (41505079 and 40705026), the National Department of Science and Technology - 863 projects (2008AA09A404-2).

References

  1. Bayley GV, Hammersley JM (1946) The effective number of independent observations in an auto-correlated time series. J Roy Statist Soc 8(1B):184–197Google Scholar
  2. China Meteorological Administration National Climate Center (1998) 98 large scale floods in China and climatic abnormalies. Meteorological Press, Beijing, p 139 (in Chinese)Google Scholar
  3. Chen Y (2002) Normative and effective engineering management for Pingban hydropower station project. Hongshui River 21(4):1–3 (in Chinese)Google Scholar
  4. Chen J, Gupta AK (2012) Parametric statistical change point analysis: with applications to genetics. Medicine and Finance, Birkhauser, BostonCrossRefGoogle Scholar
  5. Foufoula-Georgiou E, Kumar P (eds) (1994) Wavelets in geophysics. Academic Press, SanDiegoGoogle Scholar
  6. Jiang J (2009) Scanning detection of multi-scale significant change points in subseries means, variances, trends and correlation, in: Proceedings of 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009, pp. 609-613Google Scholar
  7. Jiang, J., Gu, X., Timonen, M., Helama, S., Mielikainen, K., 2015: Chapter 5: significant change points of subperiod levels in tree-ring chronologies as indications of climate changes, in: Justin A. Daniels Edit: <Advances in Environmental Research>, 37, NOVA Publisher, New York, 2015, p. 109–146Google Scholar
  8. Li S, Zhong H (2008) Introduction to the auto-observation system for water regimen at hydropower station Longtan. HongShui River 27(1):82–85 (in Chinese)Google Scholar
  9. Lund R, Reeves J (2002) Detection of undocumented change points: a revision of the two-phase regression model. J Clim 15:2547–2554CrossRefGoogle Scholar
  10. Luo Y (2005) A study of restoring annual sreamflow at Lehuang hydro-station under influence of a hydropower-station construction in Guyihe river. Pearl River 2005(2):48–50 (in Chinese)Google Scholar
  11. Luo X, Zeng E, Ji R, Wang C (2007) Effects of in-channel sand excavation on the hydrology of the Pearl River Delta. China J Hydrol 343:230–239CrossRefGoogle Scholar
  12. Ni Y, Zhang S (2012) A post-evaluation of the Baise hydro-junction. Pearl River 33(06):65–67.  https://doi.org/10.3969/j.issn.1001-9235.2012.06.020 (in Chinese)Google Scholar
  13. Von Storch H, Zwiers F (1999) Statistical analysis in climate research. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  14. Walling DE (1995) Suspended sediment yields in a changing environment. In: Gurnell A, Petts G (eds) Changing river channels. John Wiley and Sons, Chichester, pp 149–176Google Scholar
  15. Walling, D.E., 1997: The response of sediment yields to environmental change, in: Human Impact on Erosion and Sedimentation (proc. Rabat symposium), IAHS Publication, IAHS Press, Wallingford, 245, pp. 77–89Google Scholar
  16. Yao Z (1984) Basic statistics in climatology (in Chinese). Sciences Press, BeijingGoogle Scholar
  17. Yue X, Mu X, Zhao G, Shao H, Gao P (2014) Dynamic changes of sediment load in the middle reaches of the Yellow River basin, China and implications for eco-restoration. Ecol Eng 73:64–72CrossRefGoogle Scholar
  18. Zhang SK (2001) A brief introduction to Longtan Hydropower Station in Hongshuihe river. Gungxi DIanli Jianshe Keji Xinxi 2001(3):8–9Google Scholar
  19. Zhang Q, Liu C, Xu C, Xu Y, Jiang T (2006) Observed trends of annual maximum water level and streamflow during past 130 years in the Yangtze River basin, China. J Hydrol 324:255–265CrossRefGoogle Scholar
  20. Zhang Q, Xu C, Chen Y, Jiang J (2009) Abrupt behaviors of the streamflow of the Pearl River basin and implications for hydrological alterations across the Pearl River Delta, China. J Hydrol 377:274–283CrossRefGoogle Scholar
  21. Zhu, Y., Jiang, J., Huang, C., Chen, Y., Zhang, Q., 2018: Applications of multiple change point detections to monthly streamflow and rainfall in Xijiang, southern of China, part I: correlation and variance, submitted together with this manuscriptGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Geography and Resource Management, Institute of Environment, Energy and SustainabilityThe Chinese University of Hong KongShatinHong Kong
  2. 2.China Meteorological Administration Training CenterBeijingChina
  3. 3.Information Center (Hydrology Monitor and Forecast Center), Ministry of Water ResourcesBeijingChina
  4. 4.State Key Laboratory of Earth Surface Processes and Resource EcologyBeijing Normal UniversityBeijingChina

Personalised recommendations