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崇礼清水河流域土壤侵蚀空间格局及其影响因素研究
引用本文:丁杰,杨新兵,朱辰光,谢建治,文宏达.崇礼清水河流域土壤侵蚀空间格局及其影响因素研究[J].水土保持学报,2018,32(4):73-80.
作者姓名:丁杰  杨新兵  朱辰光  谢建治  文宏达
作者单位:河北农业大学林学院河北省林木种质资源与森林保护重点实验室;河北农业大学资源与环境科学学院
基金项目:国家水体污染控制与治理科技重大专项"海河北系永定河—洋河段水污染控制与水质改善技术集成与综合示范"(2015ZX07203-005)子课题"关键支流清水河水环境保护与防治技术集成与示范(2015ZX07203-005-02)
摘    要:基于DEM数字高程模型并结合RUSLE模型应用GIS、GeoDa、GS+等软件分析了河北省张家口市崇礼区25年间土壤侵蚀空间格局演变及影响因素。结果表明:(1)1990—2015年,研究区中部、西部和西南部土壤侵蚀较严重,土壤侵蚀强度以轻度、中度为主,土壤侵蚀量呈先减少后增加的趋势。(2)1990—2000年,土壤侵蚀强度转变以轻度侵蚀转入为主,土壤侵蚀状况减轻;2000—2010年,土壤侵蚀由微度侵蚀转为高级别侵蚀,侵蚀程度呈严重趋势;2010—2015年,总体表现为微度侵蚀、轻度侵蚀转向高级别侵蚀,但侵蚀增加面积有所减少,侵蚀状况稍有改善。(3)土壤侵蚀Moran’s I0,空间分布呈正相关性,表现为聚集状态,以高高型聚集为主,主要集中在崇礼区中西部和西南部。土壤侵蚀模数符合指数模型和球状模型,R2为0.943~0.979。变程A先由3 870m减小到860m再增加至1 470m,表明1990—2015年土壤侵蚀变化先快后慢,空间相关性分布范围由小变大,空间异质性呈先增强后减弱趋势。分形维数(FD)介于1.922~1.971,在区域较小空间尺度下,土壤侵蚀空间异质性主要是由植被覆盖、土地利用类型、水土保持措施等随机因子引起的。(4)土壤侵蚀影响因子中前3个主成分贡献率占到89.215 0%。在第1主成分载荷中,植被覆盖因子向量投影长度最大,为0.976 4。在第2,3主成分载荷中,水土保持措施因子、土壤可蚀性因子向量投影长度较大。因此,崇礼区土壤侵蚀影响因素大小依次为植被覆盖因子(C)、水土保持措施因子(P)、土壤可蚀性因子(K)、降雨侵蚀力因子(R)、坡长坡度因子(LS)。研究结果可为崇礼区清水河流域水土综合治理和可持续发展提供理论依据。

关 键 词:土壤侵蚀  RUSLE模型  Markov模型  空间分析  影响因素
收稿时间:2018/3/6 0:00:00

Spatial Pattern and Influence Factors of Soil Erosion of Qingshui River Basin in Chongli
DING Jie,YANG Xinbing,ZHU Chenguang,XIE Jianzhi,WEN Hongda.Spatial Pattern and Influence Factors of Soil Erosion of Qingshui River Basin in Chongli[J].Journal of Soil and Water Conservation,2018,32(4):73-80.
Authors:DING Jie  YANG Xinbing  ZHU Chenguang  XIE Jianzhi  WEN Hongda
Institution:1. College of Forestry, Hebei Agricultural University, Key Laboratory Genetic Resources of Forest and Forest Protection of Hebei, Baoding, Hebei 071000;2. College of Resources and Environment Science, Hebei Agricultural University, Baoding, Hebei 071000
Abstract:Based on DEM digital elevation model, RUSLE model combined with GIS, GeoDa, GS+ and other software, the evolution of spatial pattern of soil erosion and its influencing factors in 25 years in Chongli District, Zhangjiakou City, Hebei Province were analyzed. The results showed that:(1) From 1990 to 2015, the soil erosion was severe in the central, western, and southwestern regions of the study area. The intensity of soil erosion was mainly mild and moderate. The amount of soil erosion firstly decreased and then increased. (2) From 1990 to 2000, the change of soil erosion intensity was dominated by mild transformation. Soil erosion was alleviated. From 2000 to 2010, it was mainly slight erosion turning to high-level erosion, and showed aggravate trend. From 2010 to 2015, the overall transformation was in the form of slight erosion, mild erosion turned to high erosion levels, but the area of increased erosion decreased, and the erosion slightly improved. (3) Soil erosion''s Moran''s I>0, the spatial distribution was positive correlation, showing aggregation state, with high-level aggregation mainly in central and western and southwest. Soil erosion modulus met index model and spherical model, R2 was 0.943~0.979. The range of soil erosion reduced from 3 870 m to 860 m and then increased to 1 470 m, indicating that the change of soil erosion was firstly fast and then slow down from 1990 to 2015, the spatial distribution of spatial correlation expanded and the spatial heterogeneity increased firstly and then decreased. The fractal dimension of soil erosion ranged from 1.922 to 1.971. Spatial heterogeneity of soil erosion was mainly caused by stochastic factors such as vegetation cover, land use types, and water and soil conservation measures in a small spatial scale. (4) The contribution rate of the first, second, and third principal components to the soil erosion factors accounted for 89.215 0%. In the first principal component load, the projection length of vegetation cover factor was the largest, which was 0.976 4. In the second and third principal component loads, the projection length of soil and water conservation measures factor and soil erodibility factor were large. Therefore, the influencing factors of soil erosion in Chongli District were in order of vegetation cover factor, soil and water conservation measures factor, soil erodibility factor, rainfall erosivity factor, and slope length slope factor. The results can provide theoretical basis for soil and water management and sustainable development of Qingshui River Basin in Chongli District.
Keywords:soil erosion  RUSLE  Markov  space analysis  influence factors
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