[1]Liu Yidi,Ji Wangjia,Li Zhi.Soil Fractal Characteristics of Deep Profiles Under Different Vegetation in Loess Areas of Northern Shaanxi, China[J].Research of Soil and Water Conservation,2024,31(05):250-256,264.[doi:10.13869/j.cnki.rswc.2024.05.024]
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Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
31
Number of periods:
2024 05
Page number:
250-256,264
Column:
Public date:
2024-08-10
- Title:
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Soil Fractal Characteristics of Deep Profiles Under Different Vegetation in Loess Areas of Northern Shaanxi, China
- Author(s):
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Liu Yidi, Ji Wangjia, Li Zhi
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(College of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi 712100, China)
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- Keywords:
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loess area; fractal dimension; soil physicochemical properties; hydrodynamic parameter
- CLC:
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S152.3
- DOI:
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10.13869/j.cnki.rswc.2024.05.024
- Abstract:
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[Objective]The aims of this study are to explore the fractal characteristics of deep profile soil under different vegetation types and their relationship with soil physicochemical properties and hydraulic parameters, and to provide important reference basis for vegetation restoration and agricultural production. [Methods]Shenmu Liudaogou watershed in Shaanxi Province was taken as the research area. Soil samples with a depth of>13 meters were collected from four vegetation types(grassland, apricot, pine, and peashrub)in the area. Soil particle composition, moisture content, and organic carbon content were measured. Soil fractal dimension was calculate, The fractal characteristics of deep profile soil under different vegetation types analyzed. [Results](1)The soil clay, silt, and sand contents in this area are about 15%, 40%, and 45%, respectively, and the differences in soil particle composition under different vegetation were significant(p<0.05).(2)The fractal dimension of the four sample plots did not differ significantly(p>0.05)throughout the profile, and the effect of vegetation type on soil fractal dimension was significant(p<0.05)in the depth of 1~2 m.(3)The fractal dimension of the pine and grassland was greater than the other two sample plots. In addition, soil fractal dimension is significantly correlated with clay content and soil hydraulic parameters(θr, n and Ksat)(p<0.05), but not with soil organic carbon and soil moisture content(p>0.05). [Conclusion]Soil fractal dimension is mainly influenced by soil fine particles, and is indicative of soil hydraulic properties. Pine and grassland have the best effect on soil structure improvement. This study has important implications for the sustainable use and management of vegetation and water resources in dryland areas.