Terrain complexity-based assessment of soil and water loss risk in mountainous regions
WEI Xiuyun1, GAN Shu1,2, YUAN Xiping1,3, LI Raobo1
1. School of Land Resources Engineering, Kunming University of Science and Technology, 650093, Kunming, China; 2. Application Engineering Research Center of Spatial Information Surveying and Mapping Technology in Plateau and Mountainous Areas Set by Universities in Yunnan Province, 650093, Kunming, China; 3. School of Earth Science and Engineering Technology, West Yunnan University of Applied Sciences, 671006, Dali, Yunnan, China
Abstract：[Background] In studies related to soil and water loss, the primary emphasis is frequently placed on large-scale regional data, presenting a challenge in effectively articulating the specific conditions found in small-scale mountainous areas. Investigating fine-scale conditions in small mountainous regions is of significant practical importance for assessing soil and water loss. [Methods] This study utilized unmanned aerial vehicle (UAV) data to generate high-precision digital elevation model (DEM) and 3D model. Based on DEM data, multiple terrain factors were calculated, and the classification of terrain factors was achieved through correlation analysis and cluster analysis. Subsequently, the selection and weighting of terrain factors were accomplished using the variation coefficient method and principal component analysis, leading to the establishment of a terrain complexity model. Later, a constant offset was introduced and normalized within the terrain complexity model to derive a soil and water loss risk assessment factor model. Finally, validation analysis was conducted by comparing it with 3D model and on-site reconnaissance data. [Results] 1) Coefficients for slope, surface incision depth, profile curvature, and plan curvature in the soil and water loss risk assessment factor model were 1.933, 0.338, 0.206, and 2.633, respectively. 2) In the entire study area, the medium risk area accounted for 28.50%, with a dispersed distribution. The very high risk area accounted for 4.42%, concentrated in the south and northwest. Overall, the area was predominantly at a medium to low risk. 3) The risk of soil and water loss was higher in regions F1 and F2 due to factors such as steep terrain, low vegetation coverage, and soil desertification. The F3 region exhibited relatively mild soil and water loss due to its flat terrain and extensive cultivation of crops. [Conclusions] The model is capable of accurately delineating areas prone to soil and water loss, providing valuable insights for geoscientific research on soil and water loss and sedimentation in small-scale mountainous regions.
魏休耘, 甘淑, 袁希平, 李绕波. 基于地形复杂度的山区水土流失风险评价[J]. 中国水土保持科学, 2024, 22(4): 25-33.
WEI Xiuyun, GAN Shu, YUAN Xiping, LI Raobo. Terrain complexity-based assessment of soil and water loss risk in mountainous regions. SSWC, 2024, 22(4): 25-33.
欧镇丽, 刘彦花, 廖丹婵, 等. 基于DEM地形因子的水土流失分析 [J]. 测绘与空间地理信息, 2021, 44(2): 58. OU Zhenli, LIU Yanhua, LIAO Danchan, et al. Analysis of soil and water loss based on DEM terrain factor [J]. Geomatics & Spatial Information Technology, 2021, 44(2): 58.
[2]
罗为东, 甘淑, 袁希平, 等. 基于UAV高分辨率DEM的复杂微地貌形态特征分析:以恐龙谷南缘山区为例 [J]. 中国水土保持科学, 2022, 20 (5): 109. LUO Weidong, GAN Shu, YUAN Xiping, et al. Morphological characterization of complex micro-landscapes based on UAV high-resolution DEM: Take the mountainous area on the southern rim of Dinosaur valley as an example[J]. Science of Soil and Water Conservation, 2022, 20(5): 109.
[3]
李鑫, 郭伟玲, 张莎莎. 黄土丘陵沟壑区坡长与地形复杂度关系研究 [J]. 人民长江, 2020, 51 (2): 43. LI Xin, GUO Weiling, ZHANG Shasha. Study on the relation between slope length and terrain complexity in loess hilly and gully region [J]. Yangtze River, 2020, 51(2): 43.
[4]
汤国安, 刘学军, 闾国年. 数字高程模型及地学分析的原理与方法 [M]. 北京:科学出版社, 2005:208. TANG Guoan, LIU Xuejun, LÜ Guonian. Principles and methods of digital elevation models and geospatial analysis [M]. Beijing: Science Press, 2005: 208.
[5]
卢华兴, 刘学军, 汤国安. 地形复杂度的多因子综合评价方法 [J]. 山地学报, 2012, 30(5): 616. LU Huaxing, LIU Xuejun, TANG Guoan. Terrain complexity assessment based on multivariate analysis [J]. Mountain Research, 2012, 30(5): 616.
[6]
何文秀, 石云. 黄土丘陵沟壑区地形复杂度分析 [J]. 测绘科学, 2015, 40(10): 146. HE Wenxiu, SHI Yun. Analysis of terrain complexity in the hilly and gully area of Loess Plateau [J]. Science of Surveying and Mapping, 2015, 40(10): 146.
[7]
张倩宁, 黄泽纯, 徐柱, 等. 一种自适应定权地形复杂度模型 [J]. 山地学报, 2017, 35(2): 230. ZHANG Qianning, HUANG Zechun, XU Zhu, et al. An adaptive weighting terrain complexity model [J]. Mountain Research, 2017, 35(2): 230.
[8]
张雪莹, 张正勇, 刘琳, 等. 新疆地形复杂度的空间格局及地理特征 [J]. 地理研究, 2022, 41(10): 2832. ZHANG Xueying, ZHANG Zhengyong, LIU Lin, et al. Spatial pattern and geographical characteristics of terrain complexity index in Xinjiang [J]. Geographical Research, 2022, 41(10): 2832.
王诗琪, 周振宏, 刘东义, 等. 基于地形梯度的黄山市景观格局演变分析 [J]. 湖南生态科学学报, 2023, 10 (3): 10. WANG Shiqi, ZHOU Zhenhong, LIU Dongyi, et al. Evolution analysis of landscape pattern of Huangshan city based on topographic gradient [J]. Journal of Hunan Ecological Science, 2023, 10(3): 10.
[11]
董晓宇, 秦富仓, 李龙, 等. 裸露砒砂岩区坡面侵蚀过程中地表粗糙度与水力侵蚀特征参数的关系 [J]. 水土保持学报, 2022, 36(2): 33. DONG Xiaoyu, QIN Fucang, LI Long, et al. Relationship between surface roughness and hydraulic erosion characteristic parameters during slope erosion in exposed pisha sandstone area [J]. Journal of Soil and Water Conservation, 2022, 36(2): 33.
[12]
池金洺, 刘殿君, 于洋, 等. 黄河流域十大孔兑土地利用变化的土壤侵蚀效应 [J]. 泥沙研究, 2023, 48(6): 16. CHI Jinming, LIU Dianjun, YU Yang, et al. Effects of land-use changes on soil erosion in Ten Tributaries of the Yellow River Basin [J]. Journal of Sediment Research, 2023, 48(6): 16.
2024, Vol. 22 
