Frontiers of Earth Science

, Volume 12, Issue 2, pp 431–443 | Cite as

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

  • Hongchun Zhu
  • Yipeng Zhao
  • Haiying Liu
Research Article


Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China’s Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.


watershed scale features gully structure bifurcation ratio fractal dimension scale sequence 


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This work was supported by the auspices of the National Natural Science Foundation of China (Nos. 41471331, 41601408, and 41506111).


  1. Altaf F, Meraj G, Romshoo S A (2014). Morphometric analysis to infer hydrological behaviour of Lidder watershed, Western Himalaya, India. Geography Journal, 2013(2013): 1–12Google Scholar
  2. Babu K J, Sreekumar S, Aslam A (2016). Implication of drainage basin parameters of a tropical river basin of South India. Appl Water Sci, 6 (1): 67–75CrossRefGoogle Scholar
  3. Band L E (1989). A terrain-based watershed information system. Hydrol Processes, 3(2): 151–162CrossRefGoogle Scholar
  4. Bultreys T, De Boever W, Cnudde V (2016). Imaging and image-based fluid transport modeling at the pore scale in geological materials: a practical introduction to the current state-of-the-art. Earth Sci Rev, 155: 93–128CrossRefGoogle Scholar
  5. Chen Y Z (1984). The classification of gully in hilly loess region in the middle reaches of the yellow river. Scientla Geographica Sinica, (04): 321–327 (in Chinese)Google Scholar
  6. Cheng J C, Jiang M Q (1986). Watershed Topography System. Beijing: Science Press (in Chinese)Google Scholar
  7. Dungan J L, Perry J N, Dale M R T, Legendre P, Citron-Pousty S, Fortin M J, Jakomulska A, Miriti M, Rosenberg M S (2002). A balanced view of scale in spatial statistical analysis. Ecography, 25(5): 626–640CrossRefGoogle Scholar
  8. Frankl A, Poesen J, Deckers J, Haile M, Nyssen J (2012). Gully head retreat rates in the semi-arid highlands of northern Ethiopia. Geomorphology, 173–174: 185–195CrossRefGoogle Scholar
  9. Gao J (1997). Resolution and accuracy of terrain representation by grid DEMs at a micro-scale. Int J Geogr Inf Sci, 11(2): 199–212CrossRefGoogle Scholar
  10. Hong S Z, Hong S M (1988). A study of fractals in geoscience: drainages, earthquakes and others. Exploration of Nature, (02): 33–40 (in Chinese)Google Scholar
  11. Horton R E (1945). Erosional development of streams and their drainage basins; Hydrophysical approach to quantitative morphology. Bull Geol Soc Am, 56(3): 275–370CrossRefGoogle Scholar
  12. Huang C C, Pang J, Zha X, Su H, Zhou Y (2012). Development of gully systems under the combined impact of monsoonal climatic shift and neo-tectonic uplift over the Chinese Loess Plateau. Quat Int, 263(12): 46–54CrossRefGoogle Scholar
  13. La Barbera P, Rosso R (1989). On the fractal dimension of stream networks. Water Resour Res, 25(4): 735–741CrossRefGoogle Scholar
  14. Li L, Ying S (2005). Fundamental problem on spatial scale. Geomatics and Information Science of Wuhan University, 30(03): 199–203 (in Chinese)Google Scholar
  15. Li Z J, Liu J, Yang Z (2014). Estimating the fractal dimension value of valley based on DEM data. Geomatics and Information Science of Wuhan University, 39(11): 1277–1281 (in Chinese)Google Scholar
  16. Lin S, Jing C, Coles N A, Chaplot V, Moore N J, Wu J (2013). Evaluating DEM source and resolution uncertainties in the Soil and Water Assessment Tool. Stochastic Environ Res Risk Assess, 27(1): 209–221CrossRefGoogle Scholar
  17. Lu X J, Li H G, Chen S P, (2000). The initial research on the geographical spatial-temporal system spatial-temporal hierarchy. Geo-Information Science, 2(1): 60–66 (in Chinese)Google Scholar
  18. Lu Z C, Jia S F, Huang K X (1991). The Drainage Geomorphic System. Dalian: Dalian Publishing House (in Chinese)Google Scholar
  19. Mandelbrot B B (1967). How long is the coast of Britain? Statistical selfsimilarity and fractional dimension. Science, 156 (3775): 636–638CrossRefGoogle Scholar
  20. Mandelbrot B B, Wheeler J A (1982). The fractal geometry of nature. J R Stat Soc [Ser A], 147(4): 468–469Google Scholar
  21. Oguchi T (2015). Drainage density and relative relief in humid steep mountains with frequent slope failure. Earth Surf Process Landf, 2 (22): 107–120Google Scholar
  22. Pan B, Hu Z, Wang J, Vandenberghe J, Hu X, Wen Y, Li Q, Cao B (2012). The approximate age of the planation surface and the incision of the Yellow River. Palaeogeogr Palaeoclimatol Palaeoecol, 356–357(9): 54–61CrossRefGoogle Scholar
  23. Schuller D J, Rao A R, Jeong G D (2001). Fractal characteristics of dense stream networks. J Hydrol (Amst), 243(1–2): 1–16CrossRefGoogle Scholar
  24. Sen Roy S, Rouault M (2013). Spatial patterns of seasonal scale trends in extreme hourly precipitation in South Africa. Appl Geogr, 39: 151–157CrossRefGoogle Scholar
  25. Sharma A, Tiwari K N, Bhadoria P B S (2011). Determining the optimum cell size of digital elevation model for hydrologic application. J Earth Syst Sci, 120(4): 573–582CrossRefGoogle Scholar
  26. Shen X H, Zou L J, Zhang G F, Su N,WuWY, Yang S F (2011). Fractal characteristics of the main channel of Yellow River and its relation to regional tectonic evolution. Geomorphology, 127(1–2): 64–70CrossRefGoogle Scholar
  27. Stevens T, Carter A,Watson T P, Vermeesch P, Andò S, Bird A F, Lu H, Garzanti E, Cottam M A, Sevastjanova I (2013). Genetic linkage between the Yellow River, the Mu Us desert and the Chinese Loess Plateau. Quat Sci Rev, 78(19): 355–368CrossRefGoogle Scholar
  28. Strahler A N (1957). Quantitative analysis of watershed geomorphology. Eos (Wash DC), 6(38): 913–920Google Scholar
  29. Strahler A N (1958). Dimensional Analysis Applied to Fluvially Eroded Landforms. Geol Soc Am Bull, 69(3): 279–300CrossRefGoogle Scholar
  30. Tang G, Liu X, Fang L, Luo M (2006). A review on the scale issue in DEMs and digital terrain analysis. Geomatics and Information Science of Wuhan University, 31(12): 1059–1066Google Scholar
  31. Tian S M, Su X H, Wang W H, Lai R X (2012). Application of fractal theory in the river regime in the Lower Yellow River. Appl Mech Mater, 190–191: 1238–1243CrossRefGoogle Scholar
  32. Wang L, Fan W, Xu X, Liu Y (2014). The spatial scaling effect of canopy FAPAR retrieved by remote sensing. In: Geoscience and Remote Sensing Symposium. IEEE: 804–807Google Scholar
  33. William D C (2011). Scaling relations between riparian vegetation and stream order in the Whitewater River network. Wildl Soc Bull, 2(32): 594–597Google Scholar
  34. Xiong L Y, Tang G A, Zhu A X, Li J L, Duan J Z, Qian Y Q (2016). Landform-derived placement of electrical resistivity prospecting for paleotopography reconstruction in the loess landforms of China. J Appl Geophys, 131: 1–13CrossRefGoogle Scholar
  35. Xiong L Y, Tang G A, Zhu A X, Yuan B Y Lu B Y, Dang T M (2017). Paleotopographic controls on modern gully evolution in the loess landforms of China. Sci China Earth Sci, 60(3): 438–451CrossRefGoogle Scholar
  36. Zhou Q M, Lees B, Tang G A (2008). Advances in digital terrain analysis. Lecture Notes in Geoinformation & Cartography, 2008: 3–10Google Scholar
  37. Zhu H C, Huang W, Liu H Y (2018). Loess terrain segmentation from digital elevation models based on the region growth method. Phys Geogr, 39(1): 51–66CrossRefGoogle Scholar
  38. Zhu H C, Tang G A, Qian K J, Liu H Y (2014). Extraction and analysis of gully head of Loess Plateau in China based on digital elevation model. Chin Geogr Sci, 24(3): 328–338CrossRefGoogle Scholar

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© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of GeometricsShandong University of Science and TechnologyQingdaoChina
  2. 2.College of Computer Science and EngineeringShandong University of Science and TechnologyQingdaoChina

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