Climatic Change

, Volume 141, Issue 3, pp 483–498 | Cite as

Analysis of multi-dimensional hydrological alterations under climate change for four major river basins in different climate zones

  • Xiaoyan Wang
  • Tao Yang
  • Michel Wortmann
  • Pengfei Shi
  • Fred Hattermann
  • Anastasia Lobanova
  • Valentin Aich


Changes in river discharge regimes are regarded as the primary drivers of change of many in-stream ecological processes. While a lot of assessments addressing the hydrological alteration caused by human activities have been conducted for many river basins worldwide, a comprehensive analysis of hydrological alteration over major river basins worldwide under climate change is still limited to date. This study aims to address multi-dimensional hydrological alterations (alterations of multiple river flow characteristics) under climate change for four major rivers on three continents, by means of a consolidated framework consisting of two hydrological models, bias-corrected scenarios from five general circulation models (GCMs), and three Representative Concentration Pathways (RCPs) scenarios. The multi-dimensional hydrological alterations are quantified via the general Indicators of Hydrological Alteration approach (IHA) and two modified IHA methods based on dimensionality reduction. The reliability and advantages for the modified IHA methods are also analyzed. The results show that: (1) A modified IHA method (“NR-IHA method”) where the selected non-redundant IHA indices are basin specific is a valid alternative to the conventional IHA method for evaluating flow regime alteration, in consideration that high agreements in the simulated overall flow regimes alteration degree between it and the conventional IHA method are found during historical and future scenario periods, over four basins (the Upper Yellow River, the Lena River, the Tagus River and the Upper Amazon River). (2) Climate change is expected to remarkably alter overall flow regimes in the Tagus River and Upper Yellow River, especially at the end of the 21st century and under high RCP scenarios, whereas the dominant alteration extent tends to be low in the Lena River and Upper Amazon River in the two future periods. (3) The modified IHA method, preventing double-counting some aspects of the flow regime when assessing alteration degree of overall flow regimes, can save 65 % computation time and is more efficient than the conventional IHA method. It could be beneficial to figure out adaptive countermeasures for water resource management and restoration of eco-environmental systems under climate change.


Hydrological Model Hydrological Alteration Daily Streamflow Major River Basin Alteration Degree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The work was supported by the National Nature Science Foundation of China (41371051, 41501015), a key grant of the Chinese Academy of Sciences (KZZD-EW-12), and the Fundamental Research Funds for the Central Universities (2014B02614).

Supplementary material

10584_2016_1843_MOESM1_ESM.docx (95 kb)
ESM 1 (DOCX 94 kb)


  1. Acreman MC, Dunbar MJ, Hannaford J et al (2008) Developing environmental standards for abstractions from UK rivers to implement the Water Framework Directive. Hydrol Sci J 53:1105–1120CrossRefGoogle Scholar
  2. Chen X, Yang T, Wang XY (2013) Uncertainty intercomparison of different hydrological models in simulating extreme flows. Water Resour Manag 27:1393CrossRefGoogle Scholar
  3. Diakoulaki D, Mavrotas G, Papayannakis L (1995) Determining objective weights in multiple criteria problems: the critic method. Comput Oper 22:763–770CrossRefGoogle Scholar
  4. Gain AK, Apel H, Renaud FG, Giupponi C (2013) Thresholds of hydrologic flow regime of a river and investigation of climate change impact-the case of the Lower Brahmaputra river Basin. Clim Chang 120:463–475CrossRefGoogle Scholar
  5. Galat DL, Lipkin R (2000) Restoring ecological integrity of great rivers: historical hydrographs aid in determining reference conditions for the Missouri River. Hydrobiologia 422(423):29–48CrossRefGoogle Scholar
  6. Laize CLR, Acreman MC, Schneider C (2014) Projected flow alteration and ecological risk for pan-European rivers. River Res Appl 30:299–314CrossRefGoogle Scholar
  7. Lee A, Cho S, Kang DK, Kim S (2014) Analysis of the effect of climate change on the Nakdong river stream flow using indicators of hydrological alteration. J Hydro Environ Res 8:234–247CrossRefGoogle Scholar
  8. Olden JD, Poff NL (2003) Redundancy and the choice of hydrologic indices for characterizing streamflow regimes. River Res Appl 19:101–121CrossRefGoogle Scholar
  9. Poff NL, Zimmerman JKH (2010) Ecological responses to altered flow regimes: a literature review to inform the science and management of environmental flows. Freshw Biol 55:194–205CrossRefGoogle Scholar
  10. Poff NL, Allan JD, Bain MB et al (1997) The natural flow regime. Bioscience 47:769–784CrossRefGoogle Scholar
  11. Richter BD (2007) Testimony statement for SECURE Water Act,
  12. Richter BD (2009) Re-thinking environmental flows: from allocations and reserves to sustainability boundaries. River Res Appl 26:1052–1063Google Scholar
  13. Richter BD, Baumgartner JV, Powell J et al (1996) A method for assessing hydrologic alteration within ecosystems. Conserv Biol 10:1163–1174CrossRefGoogle Scholar
  14. Richter BD, Davis MM, Apse C et al (2012) A presumptive standard for environmental flow protection. River Res Appl 28:1312–1321CrossRefGoogle Scholar
  15. Schneider C, Laize CLR, Acreman MC et al (2013) How will climate change modify river flow regimes in Europe? Hydrol Earth Syst Sci 17:325–339CrossRefGoogle Scholar
  16. Shi X, Mao J, Thornton PE, Hoffman FM, Post WM (2011) The impact of climate, CO2, nitrogen deposition and land use change on simulated contemporary global river flow. Geophys Res Lett 38:L08704CrossRefGoogle Scholar
  17. Vorosmarty CJ, McIntyre PB, Gessner MO et al (2010) Global threats to human water security and river biodiversity. Nature 467:555–561CrossRefGoogle Scholar
  18. Wang WG, Xing WQ, Shao QX et al (2013) Changes in reference evapotranspiration across the Tibetan Plateau: Observations and future projections based on statistical downscaling. J Geophys Res: Atmos 118(10):4049–4068Google Scholar
  19. Wang XY, Yang T, Shao QX et al (2012) Statistical downscaling of extremes of precipitation and temperature and construction of their future scenarios in an elevated and cold zone. Stoch Env Res Risk A 26(3):405–418Google Scholar
  20. Warszawski L, Frieler K, Huber V et al (2014) The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework. PNAS 111:3228–3232. doi: 10.1073/pnas.1312330110 CrossRefGoogle Scholar
  21. Wood PJ, Agnew MD, Petts GE (2000) Flow variations and macroinvertebrate community responses in a small groundwater-dominated stream in south-east England. Hydrol Process 14:3133–3147CrossRefGoogle Scholar
  22. Yang T, Zhang Q, David Chen YQ (2008) A spatial assessment of hydrologic alteration caused by dam construction in the middle and lower Yellow River, China. Hydrol Process 22:3829–3843CrossRefGoogle Scholar
  23. Yang T, Xu CY, Shao Q et al (2010) Temporal and spatial patterns of low-flow changes in the Yellow River in the last half century. Stoch Environ Res Risk Assess 24:297CrossRefGoogle Scholar
  24. Zang CF, Liu J, van der Velde M et al (2012) Assessment of spatial and temporal patterns of green and blue water flows under natural conditions in inland river basins in Northwest China. Hydrol Earth Syst Sci 16:2859–2870CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Xiaoyan Wang
    • 1
  • Tao Yang
    • 1
    • 2
  • Michel Wortmann
    • 3
  • Pengfei Shi
    • 1
  • Fred Hattermann
    • 3
  • Anastasia Lobanova
    • 3
  • Valentin Aich
    • 3
  1. 1.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Center for Global Change and Water CycleHohai UniversityNanjingChina
  2. 2.State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqiChina
  3. 3.Research Domain II: Climate Impacts and VulnerabilitiesPotsdam Institute for Climate Impact ResearchPotsdamGermany

Personalised recommendations