热带地理 ›› 2018, Vol. 38 ›› Issue (3): 347-355.doi: 10.13284/j.cnki.rddl.003046

• 论文 • 上一篇    下一篇

基于RUSLE的广东南岭土壤侵蚀敏感性研究

王 钧,周 平,宫清华,杨 龙,温美丽,付淑清   

  1. (广州地理研究所//广东省地理空间信息技术与应用公共实验室,广州 510070)
  • 出版日期:2018-05-05 发布日期:2018-05-05
  • 作者简介:王钧(1988―),男,甘肃人,博士,助理研究员,主要从事地质灾害风险评估研究工作,(E-mail)wangjun@gdas.ac.cn
  • 基金资助:
    广东省科学院创新人才引进资助专项(2017GDASCX-0701、2017GDASCX-0803);广东省水利厅科技创新项目(2016-15)

Study on the Soil Erosion Sensitivity in the Nanling Mountains, Guangdong, Using the RUSLE Model

WANG Jun,ZHOU Ping,GONG Qinghua,YANG Long,WEN Meili and FU Shuqing   

  1. (Guangdong Open Laboratory of Geospatial Information Technology and Application,Guangzhou Institute of Geography,Guangzhou 510070,China)
  • Online:2018-05-05 Published:2018-05-05

摘要: 基于修正的通用水土流失方程RUSLE和GIS技术,分析了影响土壤侵蚀敏感性的降雨侵蚀力因子、土壤可蚀性因子、坡度坡长因子以及植被覆盖与管理因子,并生成单要素敏感性评价图,在此基础上,评价研究区土壤侵蚀敏感性,探讨不同土壤侵蚀敏感性的分布规律及其主导因子的空间分异特征。结果表明:降雨侵蚀力因子的变化范围为8 181.52~14 621.56(MJ·mm)/(hm2·h·a),土壤可蚀性因子为0.146~0.238(t·hm2·h)/(hm2·MJ·mm),坡度坡长因子为0~612.615,植被覆盖与管理因子为0.101~1.183,土壤侵蚀的最大值和平均值分别为7 016.44和137.69 t/(km2·a),土壤侵蚀敏感性以低度敏感和较低敏感为主,不同影响因子在敏感性分区的变化范围不同,其中地形因子和植被覆盖与管理因子对土壤侵蚀最为敏感。

关键词: RUSLE模型, 土壤侵蚀, 敏感性分区, 南岭

Abstract: In recent years, due to the intense human activities, the ecological environment of the Nanling National Nature Reserve, Guangdong Province, China, has been severely damaged and the soil erosion has been exacerbated. The sensitivity and spatial differentiation characteristics of the soil erosion in this area are urgently needed to be studied so that providing a reasonable scientific basis for local formulation of water and soil conservation measures, eco-environment conservation, and economic and social sustainable development. In this paper, based on the modified universal soil erosion equation (RUSLE) and Geographic Information System (GIS), factors affecting the sensitivity of soil erosion, such as rainfall erosion factor, soil erosion factor, slope length and steepness factor, and vegetation and management factor, were analyzed, and a single factor sensitivity assessment map was generated. On this basis, the comprehensive evaluation of the soil erosion sensitivity in the study area was achieved. The distribution of different soil erosion sensitivity and the spatial differentiation characteristics of the dominant factor were discussed finally. The results showed that the range of variation of rainfall erosion was from 8 181.52 to 14 621.56 MJ·mm/(hm2·h·a), the range of soil erosion was from 0.146 to 0.238 t·h/(MJ·mm), the slope length and steepness factor was ranging from 0 to 612.615 and the vegetation and management factor C was ranging from 0.101 to 1.183. The maximum and average values of soil erosion were 7 016.44 and 137.69 t/(km2·a), respectively. The sensitivity of soil erosion in the study area was mainly low sensitivity and lower sensitivity, whose areas accounted for about 90.44% of the total of the study site. The area above moderate sensitivity was 55.81 km2, accounting for about 9.56% of the total. The area of high sensitivity and higher sensitivity was about 6.45 km2, which only accounted for 1.10% of the total area and mainly distributed on both sides of mountain ridges and human activities in steep terrain. The comparison results between analysis of the soil erosion sensitivity and interpretation of remote sensing images showed that the RUSLE model was in good agreement with natural erosion, and there was more difference between the model result and the accelerated erosion induced by the human activity. It is necessary to further study the type and main controlling factors of soil erosion in the study area, and then revise the RUSLE model to highlight the accelerating effect of human activities on soil erosion so that making the model more realistic and reasonable. Different impact factors have different ranges of sensitivity in different zoning areas. Topographic factors and vegetation cover and management factors are the most sensitive to soil erosion in the study area, which can be adapted to local conditions and targeted soil erosion control measures can be adopted to prevent soil erosion. In particular, attention should be paid to control of the intensity of human activities for maintaining the ecological landscape and preventing the occurrence of secondary disasters such as collapses, landslides, and mudslides. The study results could be applied to the planning of soil and water conservation, land resources management in the Nanling National Nature Reserve, Guangdong Province, China.

Key words: RUSLE model, soil erosion;, sensitivity zoning, the Nanling Mountains