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Science China Technological Sciences

, Volume 62, Issue 11, pp 1885–1895 | Cite as

Structural characteristics of river networks and their relations to basin factors in the Yangtze and Yellow River basins

  • XiaBin Chen
  • YiChu WangEmail author
  • JinRen Ni
Article
  • 30 Downloads

Abstract

The integration of rivers and basins highly implies the possible existence of certain relationships between hierarchical characteristics of river networks and primary basin factors. Here we investigated river networks in two large basins, the Yangtze River and the Yellow River, characterized with basic factors such as annual precipitation, slope, soil erodibility and vegetation. Hierarchical analysis demonstrated a fair self-similarity of river networks at the stream-order 1–5 in both rivers, described by the structural parameters including bifurcation ratio, side-branching ratio, drainage density, and length of headwater-river. Besides precipitation, basin slope was essential in shaping river networks in both basins, showing a significant positive correlation (R2=0.39–0.85) to bifurcation ratio, side-branching ratio, and drainage density. Given the same basin slope (5°–15°), the higher soil erodibility and sparse vegetation would promote greater side-branching ratio and drainage density in the Yellow River, which were estimated 11.97 % and 63.70 % larger, respectively than those in the Yangtze River. This study highlights the importance to formulate basin-specific strategies for water and soil conservation in terms of different structures of river networks.

Keywords

river network structural characteristics basin factor Yangtze River Yellow River 

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References

  1. 1.
    Ni J R, Ma N A. Fluvial Dynamic Geomorphology (in Chinese). Beijing: Peking University Press, 1998Google Scholar
  2. 2.
    Horton R E. Erosional development of streams and their drainage basins; hydrophysical approach to quantitative morphology. Geol Soc Am Bull, 1945, 56: 275–370CrossRefGoogle Scholar
  3. 3.
    Strahler A N. Hypsometric (area-altitude) analysis of erosional topography. Geol Soc Am Bull, 1952, 63: 1117–1142CrossRefGoogle Scholar
  4. 4.
    Strahler A N. Quantitative analysis of watershed geomorphology. EOS Trans Am Geophys Union, 1957, 38: 913–920CrossRefGoogle Scholar
  5. 5.
    Shreve R L. Statistical law of stream numbers. J Geol, 1966, 74: 17–37CrossRefGoogle Scholar
  6. 6.
    Tokunaga E. Ordering of divide segments and law of divide segment numbers. Trans Jpn Geomorphol Union, 1984, 5: 71–77Google Scholar
  7. 7.
    Benstead J P, Leigh D S. An expanded role for river networks. Nat Geosci, 2012, 5: 678–679CrossRefGoogle Scholar
  8. 8.
    Vörösmarty C J, Fekete B M, Meybeck M, et al. Global system of rivers: Its role in organizing continental land mass and defining land-to-ocean linkages. Glob Biogeochem Cycle, 2000, 14: 599–621CrossRefGoogle Scholar
  9. 9.
    Shen X, Anagnostou E N, Mei Y, et al. A global distributed basin morphometric dataset. Sci Data, 2017, 4: 160124CrossRefGoogle Scholar
  10. 10.
    Cohen S, Wan T, Islam M T, et al. Global river slope: A new geospatial dataset and global-scale analysis. J Hydrol, 2018, 563: 1057–1067CrossRefGoogle Scholar
  11. 11.
    Allen G H, Pavelsky T M. Global extent of rivers and streams. Science, 2018, 361: 585–588MathSciNetCrossRefGoogle Scholar
  12. 12.
    Allen G H, Pavelsky T M, Barefoot E A, et al. Similarity of stream width distributions across headwater systems. Nat Commun, 2018, 9: 610CrossRefGoogle Scholar
  13. 13.
    Perron J T, Richardson P W, Ferrier K L, et al. The root of branching river networks. Nature, 2012, 492: 100–103CrossRefGoogle Scholar
  14. 14.
    Zanardo S, Zaliapin I, Foufoula-Georgiou E. Are American rivers Tokunaga self-similar? New results on fluvial network topology and its climatic dependence. J Geophys Res Earth Surf, 2013, 118: 166–183CrossRefGoogle Scholar
  15. 15.
    Sangireddy H, Carothers R A, Stark C P, et al. Controls of climate, topography, vegetation, and lithology on drainage density extracted from high resolution topography data. J Hydrol, 2016, 537: 271–282CrossRefGoogle Scholar
  16. 16.
    Ranjbar S, Hooshyar M, Singh A, et al. Quantifying climatic controls on river network branching structure across scales. Water Resour Res, 2018, 54: 7347–7360CrossRefGoogle Scholar
  17. 17.
    Editorial Committee of Encyclopedia of Rivers and Lakes in China. Encyclopedia of Rivers and Lakes in China (in Chinese). Beijing: China Water Power Press, 2014Google Scholar
  18. 18.
    Ni J R, Wu A, Li T H, et al. Efficient soil loss assessment for large basins using smart coded polygons. J Env Inform, 2014, 23: 47–57CrossRefGoogle Scholar
  19. 19.
    Hartmann J, Moosdorf N. The new global lithological map database GLiM: A representation of rock properties at the Earth surface. Geochem Geophys Geosyst, 2012, 13: Q12004CrossRefGoogle Scholar
  20. 20.
    Bai R, Li T, Huang Y, et al. An efficient and comprehensive method for drainage network extraction from DEM with billions of pixels using a size-balanced binary search tree. Geomorphology, 2015, 238: 56–67CrossRefGoogle Scholar
  21. 21.
    Rui X F. Principles of Hydrology (in Chinese). Beijing: Higher Education Press, 2013Google Scholar
  22. 22.
    Willett S D, McCoy S W, Perron J T, et al. Dynamic reorganization of river basins. Science, 2014, 343: 1248765CrossRefGoogle Scholar
  23. 23.
    Panagos P, Meusburger K, Ballabio C, et al. Soil erodibility in Europe: A high-resolution dataset based on LUCAS. Sci Total Environ, 2014, 479–480: 189–200CrossRefGoogle Scholar
  24. 24.
    Samal D R, Gedam S S, Nagarajan R. GIS based drainage morphometry and its influence on hydrology in parts of Western Ghats region, Maharashtra, India. Geocarto Int, 2015, 30: 755–778CrossRefGoogle Scholar
  25. 25.
    Gupta V K, Ayalew T B, Mantilla R, et al. Classical and generalized Horton laws for peak flows in rainfall-runoff events. Chaos, 2015, 25: 075408CrossRefGoogle Scholar
  26. 26.
    Gregory K. Drainage Networks and Climate, in Geomorphology and Climate. New York: John Wiley, 1976Google Scholar
  27. 27.
    Collins D B G, Bras R L. Climatic and ecological controls of equilibrium drainage density, relief, and channel concavity in dry lands. Water Resour Res, 2010, 46: W04508CrossRefGoogle Scholar
  28. 28.
    Abrahams A D. Drainage densities and sediment yields in eastern Australia. Aust Geog Studies, 1972, 10: 19–41CrossRefGoogle Scholar
  29. 29.
    Abrahams A D, Ponczynski J J. Drainage density in relation to precipitation intensity in the U.S.A.. J Hydrol, 1984, 75: 383–388CrossRefGoogle Scholar
  30. 30.
    Han P, Ni J R, Hou K B, et al. Numerical modeling of gravitational erosion in rill systems. Int J Sediment Res, 2011, 26: 403–415CrossRefGoogle Scholar
  31. 31.
    Wang Y C, Gao X W, Li T J, et al. Geocode-based aquatic habitats in hierarchical system of the Yellow River basin. J Environ Inform, 2018, 32: 69–81Google Scholar
  32. 32.
    Tang K L. Soil and Water Conservation in China (in Chinese). Beijing: Science Press, 2004Google Scholar
  33. 33.
    Liu N. Analysis of design flood in middle and lower reach of the Yangtze river (in Chinese). Yangtze River, 2006, 37: 1–4Google Scholar
  34. 34.
    Chen L, Ma J T, Jiao Y, et al. General Survey Report on Water and Soil Conservation (in Chinese). Beijing: China Water Power Press, 2011Google Scholar
  35. 35.
    Pallard B, Castellarin A, Montanari A. A look at the links between drainage density and flood statistics. Hydrol Earth Syst Sci, 2008, 13: 1019–1029CrossRefGoogle Scholar
  36. 36.
    Wu L, Liu X, Ma X. Research progress on the watershed sediment delivery ratio. Int J Environ Studies, 2018, 75: 565–579CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.The Key Laboratory of Water and Sediment Sciences, Ministry of Education, College of Environmental Sciences and EngineeringPeking UniversityBeijingChina
  2. 2.Beijing Innovation Center for Engineering Science and Advanced Technology (BIC-ESAT)Peking UniversityBeijingChina

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