Spatial distribution and influencing factors of Surface Nibble Degree index in the severe gully erosion region of China's Loess Plateau

doi:10.1007/s11442-021-1912-2

摘要/Abstract

Abstract:

In China's Loess Plateau severe gully erosion (LPGE) region, the shoulder-line is the most intuitive and unique manifestation of the loess landform, which divides a landform into positive and negative terrains (PNTs*The spatial combination model of PNTs is of great significance for revealing the evolution of the loess landform. This study modeled and proposed the Surface Nibble Degree (SND), which is a new index that reflects the comparison of the areas of PNTs. Based on 5 m DEMs and matched high-resolution remote sensing images, the PNTs of 172 complete watersheds in the LPGE were extracted accurately, and the SND index was calculated. The spatial distribution trend of SND was discussed, and the relationship between SND and the factors that affect the evolution mechanism of regional landform was explored further. Results show that: (1) The SND can be calculated formally. It can quantify the development of the loess landform well*2) The SND of the LPGE has evident spatial differentiation that increases from southwest to northeast. High values appear in Shenmu of Shaanxi, Shilou of Shanxi, and northern Yanhe River, whereas the low values are mainly distributed in the southern loess tableland and the inclined elongated ridge area of Pingliang in Gansu and Guyuan in Ningxia*3) In the Wuding River and Yanhe River, the SND decreases with the increase in flow length (FL*In the North-Luohe River and Jinghe River, the SND increases with FL*4) SND is significantly correlated with gully density and sediment modulus and moderately correlated with hypsometric integral. As for the mechanism factors analysis, the relationship between loess thickness and SND is not obvious, but SND increased first and then decreased with the increase of precipitation and vegetation in each geographical division, and we found that the land use type of low coverage grassland has greater erosion potential.

Key words: digital elevation model, shoulder-line, Surface Nibble Degree, spatial distribution, terrain factor, digital terrain analysis, Loess Plateau gully erosion region

. [J]. 地理学报(英文版), 2021, 31(11): 1575-1597.

ZHOU Yi, YANG Caiqin, LI Fan, CHEN Rong. Spatial distribution and influencing factors of Surface Nibble Degree index in the severe gully erosion region of China's Loess Plateau[J]. Journal of Geographical Sciences, 2021, 31(11): 1575-1597.

图/表 14

Number	Lat	Lon	Number	Lat	Lon
1	110.033	37.0707	12	110.198	38.1848
2	107.951	35.3999	13	109.222	37.0174
3	106.835	35.7482	14	109.474	37.3572
4	107.231	35.4794	15	110.83	36.8835
5	110.279	36.2634	16	110.495	37.3494
6	110.248	36.1131	17	110.915	37.4759
7	110.802	38.772	18	111.382	39.1953
8	110.953	38.3863	19	110.758	36.5699
9	109.305	37.0718	20	109.894	36.4359
10	110.472	37.1896	21	107.331	35.1658
11	109.81	37.2797	22	111.117	39.1658
Number	Lat	Lon	Number	Lat	Lon
23	109.984	38.0775	68	108.402	35.3774
24	111.052	37.8289	69	111.9215	39.2664
25	110.956	37.094	70	108.608	34.8039
26	109.837	37.4431	71	108.087	35.2474
27	110.713	38.9347	72	110.318	37.4710
28	110.65	37.9804	73	110.700	37.3854
29	110.771	37.8817	74	109.429	37.7926
30	110.758	37.0093	75	110.834	38.9883
31	110.746	38.1056	76	110.918	36.4765
32	106.763	36.0591	77	106.964	35.3487
33	106.554	35.6681	78	110.379	38.0940
34	106.931	36.6177	79	108.403	36.4414
35	107.137	36.5798	80	107.818	35.5294
36	106.513	35.9951	81	107.225	36.8137
37	107.0	35.7445	82	110.584	36.0768
38	110.384	36.4940	83	111.294	38.8903
39	107.070	35.9556	84	109.696	35.6187
40	107.309	36.1977	85	110.174	36.2950
41	107.278	36.7339	86	109.767	36.4583
42	107.320	35.5627	87	110.722	36.6932
43	107.502	35.3238	88	109.793	37.2528
44	107.688	35.8767	89	111.491	38.8743
45	107.807	35.6414	90	108.942	37.0613
46	107.780	35.2545	91	109.081	37.2824
47	109.478	35.8585	92	109.287	37.5356
48	108.143	35.0713	93	109.502	37.7438
49	107.817	36.1229	94	111.186	38.9767
50	107.695	36.3004	95	111.017	37.178
51	107.906	36.5821	96	110.241	36.8861
52	108.025	36.9507	97	109.559	37.8908
53	108.005	35.8717	98	108.712	37.2122
54	107.179	37.0657	99	108.594	37.2009
55	107.623	37.1344	100	108.407	37.2424
56	107.778	37.2294	101	108.712	36.7946
57	109.625	37.5820	102	108.171	37.0806
58	107.553	35.2536	103	107.394	36.9248
59	109.049	35.6990	104	109.59	37.0042
60	109.731	35.2954	105	109.3	36.8327
61	109.626	35.3987	106	108.733	36.976
62	107.540	36.0237	107	110.518	36.7005
63	111.236	37.6664	108	111.093	38.5642
64	110.591	36.4738	109	110.52	37.6902
65	109.551	36.8988	110	110.812	36.7609
66	108.329	35.1554	111	110.746	36.3063
67	108.254	35.2298	112	110.128	36.5689
Number	Lat	Lon	Number	Lat	Lon
113	109.664	36.3772	139	110.218	37.7938
114	109.697	36.606	140	110.093	37.6126
115	109.322	36.5958	141	109.943	37.8034
116	109.104	36.7068	142	110.936	37.9112
117	108.275	36.7145	143	110.332	37.0434
118	108.693	36.4447	144	110.055	37.2545
119	108.899	36.293	145	109.138	35.9500
120	110.478	38.5782	146	109.397	35.2169
121	108.031	36.2957	147	109.647	37.7163
122	107.493	36.3935	148	110.572	36.4798
123	106.711	36.7131	149	110.693	38.1253
124	106.828	36.2325	150	111.352	39.0003
125	109.811	36.0532	151	111.451	39.2793
126	109.424	35.8032	152	109.841	38.2649
127	109.213	35.7367	153	110.302	37.9837
128	109.111	35.9684	154	110.687	37.5559
129	107.887	35.7404	155	109.563	35.4001
130	107.799	35.9819	156	111.153	37.4615
131	107.291	35.7277	157	110.331	36.9478
132	109.42	35.6105	158	108.461	35.7526
133	109.6	35.4757	159	110.415	35.5783
134	109.358	35.4727	160	108.688	36.4855
135	108.848	35.0658	161	111.830	39.4029
136	107.848	35.1926	162	111.752	39.5629
137	106.735	35.4812	163	110.829	38.6034
138	110.58	38.4604	164	110.332	38.0383

参考文献 55

[1]	Arabameri A, Pradhan B, Rezaei K, 2019. Spatial prediction of gully erosion using ALOS PALSAR data and ensemble bivariate and data mining models. Geosciences Journal, 23(4): 669-686. doi: 10.1007/s12303-018-0067-3
[2]	Cao J J, Tang G A, Fang X et al., 2019. Terrain relief periods of loess landforms based on terrain profiles of the Loess Plateau in northern Shaanxi Province, China. Frontiers of Earth Science, 13(2): 410-421. doi: 10.1007/s11707-018-0732-x
[3]	Carroll C, Merton L, Burger P, 2000. Impact of vegetative cover and slope on runoff, erosion, and water quality for field plots on a range of soil and spoil materials on central Queensland coal mines. Soil Research, 38(2): 313-328. doi: 10.1071/SR99052
[4]	Chen H, Lu Z C, Zhou J X et al., 2004. Interactions of environmental factors on sediment yield in the region of the middle Yellow River basin. Journal of Sediment Research, 2004(2): 40-46. (in Chinese)
[5]	Chen H, Wang K Z, 1999. A study on the slope gully erosion relationship on small basins in the loess areas at the middle reaches of the Yellow River. Geographical Research, 18(4): 363-372. (in Chinese)
[6]	Chen Q B, Fei X L, 1996. New progress in the research of soil erosion forecast. Soil and Water Conservation in China, (2): 20-23. (in Chinese)
[7]	Clark C, 2000. Storms, floods and soil erosion: The consequences of the storm of 13 May 1998 at Hadspen, Somerset. Weather, 55(1): 17-25. doi: 10.1002/wea.2000.55.issue-1
[8]	Fu B J, 2014. The integrated studies of geography: Coupling of patterns and processes. Acta Geographica Sinica, 69(8): 1052-1059. (in Chinese)
[9]	Feng X M, Wang Y F, Chen L D et al., 2010. Modeling soil erosion and its response to land-use change in hilly catchments of the Chinese Loess Plateau. Geomorphology, 118(34): 239-248. doi: 10.1016/j.geomorph.2010.01.004
[10]	Gao H D, Li Z B, Jia L L,et al., 2016. Capacity of soil loss control in the Loess Plateau based on soil erosion control degree. Journal of Geographical Sciences, 26(4): 457-472. doi: 10.1007/s11442-016-1279-y
[11]	Jing K, 1986. A study on gully erosion on the Loess Plateau. Scientia Geographica Sinica, 6(4): 340-347. (in Chinese)
[12]	Jing K, Zheng F L, 2004. An introduction to the typical models for soil and water conservation in China. Research of Soil and Water Conservation, 11(4): 34-39. (in Chinese)
[13]	Jiang L, Tang G A, Zhao M W et al., 2013. Extraction and analysis of loess gully heads considering geomorphological structures. Geographical Research, 32(11): 2153-2162. (in Chinese)
[14]	Lei X, 2020. Research on the spatial differentiation characteristics of the proximity index of the Loess Plateau in northern Shaanxi based on DEM[D]. Xi'an: Shaanxi Normal University. (in Chinese)
[15]	Li C R, Li F Y, Ma J et al., 2017. The study of watershed topography characteristic in the middle reaches of the Yellow River. Geography and Geo-Information Science, 33(4): 107-112. (in Chinese)
[16]	Li C R, Li F Y, Dai Z Y et al., 2020. Spatial variation of gully development in the Loess Plateau of China based on the morphological perspective. Earth Science Informatics, 13(4): 1103-1117. doi: 10.1007/s12145-020-00491-4
[17]	Li Z, Zhang Y, Zhu Q K et al., 2015. Assessment of bank gully development and vegetation coverage on the Chinese Loess Plateau. Geomorphology, 228(1): 462-469. doi: 10.1016/j.geomorph.2014.10.005
[18]	Li Z, Zhang Y, Zhu Q K et al., 2017. A gully erosion assessment model for the Chinese Loess Plateau based on changes in gully length and area. Catena, 148(2): 195-203. doi: 10.1016/j.catena.2016.04.018
[19]	Li Z B, Zhu B B, Li P, 2008. Advancement in study on soil erosion and soil and water conservation. Acta Pedologica Sinica, 45(5): 802-809. (in Chinese)
[20]	Li Z S, Yang L, Wang G L et al., 2019. The management of soil and water conservation on the Loess Plateau of China: Present situations, problems, and counter-solutions. Acta Ecologica Sinica, 39(20): 7398-7409. (in Chinese)
[21]	Liu G B, Shangguan Z P, Yao W Y et al., 2017. Ecological effects of soil conservation in Loess Plateau. Bulletin of Chinese Academy of Sciences, 32(1): 11-19. (in Chinese)
[22]	Liu K, 2017. Gully features extraction and the regional difference analysis in the severe soil erosion region of Loess Plateau of China based on multisource data. Nanjing: Nanjing Normal University. (in Chinese)
[23]	Liu L M, Liu P, 1993. Study on methodology and models of quantifying soil erosion in the hilly-gully loess regions. Journal of Soil and Water Conservation, 7(3): 73-79. (in Chinese)
[24]	Liu T S, Sun J M, Wu W X, 2001. Past, present and future of the Chinese loess research: A discussion on the reality facts and math. Quaternary Sciences, 21(3): 185-207. (in Chinese)
[25]	Liu X D, Wu Q X, Zhao H Y, 1994. The vertical interception function of forest vegetation and soil and water conservation. Research of Soil and Water Conservation, 1(3): 8-13. (in Chinese)
[26]	Luo L X, 1956. A tentative classification of landforms in the Loess Plateau. Acta Geographica Sinica, 22(3): 201-222. (in Chinese)
[27]	Lv G N, Xiong L Y, Chen M et al., 2017. Chinese progress in geomorphometry. Journal of Geographical Sciences, 27(11): 1389-1412. doi: 10.1007/s11442-017-1442-0
[28]	Magdoff F, 2011. Ecological civilization. Monthly Review, 62(8): 1-25.
[29]	Ochoa P A, Fries A, Mejía D et al., 2016. Effects of climate, land cover and topography on soil erosion risk in a semiarid basin of the Andes. Catena, 140: 31-42. doi: 10.1016/j.catena.2016.01.011
[30]	Rajbanshi J, Bhattacharyaa S, 2020. Assessment of soil erosion, sediment yield and basin specific controlling factors using RUSLE-SDR and PLSR approach in Konar River Basin, India. Journal of Hydrology, 587(C): 1-55.
[31]	Song G Q, Li L T, Li R, 1990. Approach on proportions between gullied-land and ridge-land in the rolling loess area, northern Shaanxi. Bulletin of Soil and Water Conservation, 10(3): 37-44.. (in Chinese)
[32]	Tian J, Tang G A, Zhou Y et al., 2013. Spatial variation of gully density in the Loess Plateau. Scientia Geographica Sinica, 33(5): 622-628.. (in Chinese)
[33]	Tucker C, 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2): 127-150. doi: 10.1016/0034-4257(79)90013-0
[34]	Vanmaercke M, Poesen J, Van M B et al., 2016. How fast do gully headcuts retreat? Earth Science Reviews, 154: 336-355. doi: 10.1016/j.earscirev.2016.01.009
[35]	Wang B, Zheng F L, Mathias J M et al., 2013. Soil erodibility for water erosion: A perspective and Chinese experiences. Geomorphology, 187: 1-10. doi: 10.1016/j.geomorph.2013.01.018
[36]	Wang N, Jiao J Y, Bai L C et al., 2020. Magnitude of soil erosion in small catchments with different land use patterns under an extreme rainstorm event over the northern Loess Plateau, China. Catena, 195: 104780. doi: 10.1016/j.catena.2020.104780
[37]	Wang Z J, Jiao J Y, Rayburg S et al., 2016. Soil erosion resistance of “Grain for Green” vegetation types under extreme rainfall conditions on the Loess Plateau, China. Catena, 141: 109-116. doi: 10.1016/j.catena.2016.02.025
[38]	Wu X L, Xiong L Y, Hu E L, 2017. An adaptive approach to selecting accumulation threshold for gully networks extraction from DEMs. Geography and Geo-Information Science, 33(4): 93-98. (in Chinese)
[39]	Xiao C C, Tang G A, 2007. Classification of valley shoulder line in loess relief. Arid Land Geography, 30(5): 646-653. (in Chinese)
[40]	Xiong L Y, Tang G A, Strobl J et al., 2016. Paleotopographic controls on loess deposition in the Loess Plateau of China. Earth Surface Processes Landforms, 41(9): 1155-1168. doi: 10.1002/esp.v41.9
[41]	Xiong L Y, Tang G A, Yang Xin et al., 2021. Geomorphology-oriented digital terrain analysis: Progress and perspectives. Journal of Geographical Sciences, 31(3): 456-476. doi: 10.1007/s11442-021-1853-9
[42]	Yan J S, Tang G A, Li F Y et al., 2011. An edge detection based method for extraction of loess shoulder-line from grid DEM. Geomatics and Information Science of Wuhan University, 36(3): 363-367. (in Chinese)
[43]	Yang L, Wei W, Chen L D et al., 2014. Response of temporal variation of soil moisture to vegetation restoration in semi-arid Loess Plateau, China. Catena, 115: 123-133. doi: 10.1016/j.catena.2013.12.005
[44]	Yang X, Dai W, Tang G A et al., 2017. Deriving ephemeral gullies from VHR image in loess hilly areas through directional edge detection. ISPRS International Journal of Geo-Information, 6(11): 371-389. doi: 10.3390/ijgi6110371
[45]	Yang X Na, J M, Tang G A et al., 2019. Bank gully extraction from DEMs utilizing the geomorphologic features of a loess hilly area in China. Frontiers of Earth Science, 13(1): 151-168. doi: 10.1007/s11707-018-0700-5
[46]	Yuan X F, Han J C, Shao Y J et al., 2019. Geodetection analysis of the driving forces and mechanisms of erosion in the hilly-gully region of northern Shaanxi Province. Journal of Geographical Sciences, 29(5): 779-790. doi: 10.1007/s11442-019-1627-9
[47]	Zhang J C, 2012. Policy research on ecological environment management in western China[D]. Yangling: Institute of Soil and Water Conservation, Northwest A&F University. (in Chinese)
[48]	Zhang L, 2013. Spatial pattern of the loess landforms based on core topographic factor analysis[D]. Nanjing: Nanjing Normal University. (in Chinese)
[49]	Zheng F L, Kang S Z, 1998. Erosion and sediment yield in different zones of loess slopes. Acta Geographica Sinica, 53(5): 428-435. (in Chinese)
[50]	Zheng F L, Xu X M, Qin C, 2016. A review of gully erosion process research. Transactions of the Chinese Society for Agricultural Machinery, 47(8): 48-59, 116. (in Chinese)
[51]	Zhou C H, Cheng W M, Qian J K et al., 2009. Research on the classification system of digital land geomorphology of 1: 1000000 in China. Journal of Geo-Information Science, 11(6): 707-724. (in Chinese) doi: 10.3724/SP.J.1047.2009.00707
[52]	Zhou Y, 2011. DEM based research on positive-negative terrains and their spatial variation on Loess Plateau[D]. Nanjing: Nanjing Normal University. (in Chinese)
[53]	Zhou Y, Lei X, Yang F et al., 2019. Characteristics and influencing factors of proximity distance index on the northern Shaanxi Loess Plateau in China. Journal of Mountain Science, 16(12): 2844-2855. doi: 10.1007/s11629-019-5610-9
[54]	Zhou Y, Tang G A, Xi Y et al., 2013. A shoulder-lines connection algorithm using improved Snake Model. Geomatics and Information Science of Wuhan University, 38(1): 82-85. (in Chinese)
[55]	Zhou Y, Yang X, Xiao C C et al., 2010. Positive and negative terrains on northern Shaanxi Loess Plateau. Journal of Geographical Sciences, 20(1): 64-76. doi: 10.1007/s11442-010-0064-6

Name	P terrain (km²)	N terrain (km²)	Watershed (km²)	SND	Lon	Lat	Landform type
Chunhua	30.8425	8.8657	39.7082	0.29	108.376	34.9018	Loess tableland
Yijun	19.1229	7.6041	26.7170	0.40	109.408	35.4398	Loess residual tableland
Ganquan	11.8106	7.5338	19.3444	0.64	109.546	36.2017	Loess ridge
Yan'an	9.3437	9.0372	18.3809	0.97	109.430	36.5230	Loess hilly-ridge
Yanchuan	9.4479	9.3030	18.7509	0.98	109.910	36.7351	Loess hilly-ridge
Suide	6.6881	5.8591	12.5472	0.87	110.332	37.5688	Loess hill
Jiaxian	6.6615	6.7144	13.3759	1.01	110.534	37.9655	Loess hill
Shenmu	5.5759	6.1503	11.7262	1.10	110.778	38.5685	Loess hilly-ridge

	SST	LWG	SCLH	LIMB	LH	LR	LRH	LT	BRM	RAP
Dry land (%)	40.20	40.18	48.88	54.75	43.42	41.03	17.06	43.67	33.77	67.83
Woodland (%)							10.34
Shrubland (%)				10.52			27.06		13.55
HCGL (%)							13.01
MCGL (%)	10.81	42.11	17.30		20.56	35.87	21.66	30.53	24.95	18.47
LCGL (%)	31.21	11.95	24.47	16.18	20.50	14.70			13.62