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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

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Front. Earth Sci.    2018, Vol. 12 Issue (2) : 431-443    https://doi.org/10.1007/s11707-018-0696-x
RESEARCH ARTICLE
Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models
Hongchun ZHU1(), Yipeng ZHAO1, Haiying LIU2()
1. College of Geometrics, Shandong University of Science and Technology, Qingdao 266590, China
2. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China
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Abstract

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.
Keywords watershed      scale features      gully structure      bifurcation ratio      fractal dimension      scale sequence     
Corresponding Author(s): Hongchun ZHU,Haiying LIU   
Just Accepted Date: 02 March 2018   Online First Date: 09 April 2018    Issue Date: 09 May 2018
 Cite this article:   
Hongchun ZHU,Yipeng ZHAO,Haiying LIU. Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models[J]. Front. Earth Sci., 2018, 12(2): 431-443.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-018-0696-x
https://academic.hep.com.cn/fesci/EN/Y2018/V12/I2/431
Fig.1  (a) Distribution of five study areas. (b)–(f) DEM image of watershed in TA-b-TA-f, respectively.
Test area Landform type Feature parameter
Catchment area/km2 Mean slope/(°) Relief/m
TA-b Loess flat-topped ridge and gully 15.84 15.74 232.30
TA-c Loess ridge and gully 19.32 26.57 282.56
TA-d Loess hill ridge and gully 18.14 24.00 319.10
TA-e Loess hill and gully 19.07 28.01 194.46
TA-f Loess hill and gully 20.65 28.20 183.49
Tab.1  Major geomorphologic features of five watersheds extracted from five test areas in Shaanxi Province, China
Fig.2  Diagram of the research method.
Test area Scale
(resolution/m)		 Feature parameter
Gully level Mean length ratio Bifurcation ratio Fractal dimension
Yijun 1:10,000 (5 m) 3 2.96 5.43 1.56
1:10,000 (10 m) 3 2.92 5.34 1.56
1:50,000 (25 m) 3 2.68 5.45 1.72
1:50,000 (50 m) 3 2.64 5.28 1.71
Ganquan 1:10,000 (5 m) 4 1.55 4.43 3.41
1:10,000 (10 m) 4 1.55 4.43 3.41
1:50,000 (25 m) 4 1.52 4.43 3.54
1:50,000 (50 m) 4 1.51 4.38 3.59
Yanchuan 1:10,000 (5 m) 4 2.02 5.51 2.43
1:10,000 (10 m) 4 2.02 5.51 2.42
1:50,000 (25 m) 4 1.82 5.47 2.85
1:50,000 (50 m) 4 1.79 5.45 2.92
Suide 1:10,000 (5 m) 3 3.12 7.50 1.77
1:10,000 (10 m) 3 3.15 7.30 1.73
1:50,000 (25 m) 3 3.24 7.64 1.72
1:50,000 (50 m) 3 3.20 7.30 1.71
Jiaxian 1:10,000 (5 m) 3 1.97 4.34 2.17
1:10,000 (10 m) 3 1.88 4.07 2.22
1:50000 (25 m) 3 1.81 4.33 2.48
1:50000 (50 m) 3 1.74 4.42 2.70
Tab.2  Watershed information list based on different data scales
Fig.3  The bifurcation ratio of different data scales.
Fig.4  The fractal dimension of different data scales.
Fig.5  The gully network of Ganquan area by different scales of analysis. The maximum flow accumulation of (a) 5.0%, (b) 1.0%, and (c) 0.1%.
Fig.6  The extraction result of watershed structure, with the analysis scale less than 0.1%.
Test area The analysis scale range
Gully level 5 to 4 Gully level 4 to 3 Gully level 3 to 2
Yijun (0.30%, 0.50%) (0.70%, 0.90%) (2.00%, 2.20%)
Ganquan (0.10%, 0.30%) (1.10%, 1.30%) (3.40%, 3.60%)
Yanchuan (0.10%, 0.30%) (0.70%, 0.90%) (2.00%, 2.20%)
Suide (0.10%, 0.30%) (0.70%, 0.90%) (4.60%, 4.80%)
Jiaxian (0.10%, 0.30%) (0.70%, 0.90%) (2.00%, 2.20%)
Tab.3  The analysis scale range in the change of gully level
Analysis scale Fractal dimension of test area
Yijun Ganquan Yanchuan Suide Jiaxian
2.00% 1.28 1.70 0.96 1.45 1.44
1.70% 1.46 1.64 1.15 1.6 1.45
1.50% 1.53 1.67 1.18 1.43 1.53
1.30% 1.66 1.39 1.19 1.51 1.59
1.10% 1.78 1.68 1.18 1.5 1.59
0.90% 1.55 1.83 1.28 1.52 1.64
0.70% 1.82 1.69 1.77 1.56 1.66
0.50% 1.93 1.71 1.27 1.59 1.69
0.30% 2.11 1.49 1.35 1.76 1.64
0.10% 1.85 1.77 1.34 2.26 1.79
Tab.4  The fractal dimension of the watersheds at different analysis scales
Fig.7  The fractal dimension of different analysis scales. (a) Yijun; (b) Ganquan; (c) Yanchuan; (d) Suide; (e) Jiaxian.
Analysis scale Bifurcation ratio of test area
Yijun Ganquan Yanchuan Suide Jiaxian
2.00% 4.17 4.00 3.88 4.38 3.88
1.70% 4.50 4.25 4.50 4.63 4.40
1.50% 4.50 4.50 4.50 4.88 4.50
1.30% 4.84 4.84 4.80 5.38 5.10
1.10% 5.67 3.07 5.25 5.75 5.72
0.90% 6.00 3.17 5.84 5.9 6.22
0.70% 3.92 3.33 3.76 3.63 3.80
0.50% 4.24 4.26 3.93 3.68 3.83
0.30% 3.29 4.64 4.53 4.20 4.60
0.10% 4.03 4.00 4.03 4.67 3.89
Tab.5  The bifurcation ratio of watershed in different scales of analysis
Fig.8  The bifurcation ratio of different analysis scales.
Test area Fractal dimension Bifurcation ratio
Correlation coefficient Coefficient of?variation Mean value Correlation coefficient Coefficient of?variation Mean value
Yijun ?0.89 0.15 1.70 0.29 0.18 4.52
Ganquan ?0.01 0.08 1.66 0.08 0.16 4.01
Yanchuan ?0.63 0.17 1.27 0.09 0.15 4.50
Suide ?0.70 0.15 1.62 0.25 0.17 4.71
Jiaxian ?0.95 0.07 1.60 0.10 0.18 4.59
Tab.6  Results of the correlation analysis
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