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为揭示粒径分级对土壤体积分形维数测定的影响,采用激光衍射技术测定毛乌素沙地风沙土粒径组成,基于中国制、前苏联制、美国制和国际制4种不同粒径分级方法计算土壤体积分形维数.研究结果显示,(1)研究区土壤质地较粗,土壤颗粒组成以砂粒为主,占总体积的90%以上,而黏粒、粉粒含量相对较少;土壤体积分形维数大小排序为前苏联制(DSU)>中国制(DCHN)>国际制(DINT)>美国制(DUS);(2)DCHN、DUS和DINT与土壤粘粒、粉粒和砂粒含量线性回归拟合效果良好,且相关性极显著(P<0.01);DSU与土壤粉粒和砂粒含量相关性显著(P<0.05),但线性回归拟合效果较差;(3)DCHN、DUS和DINT之间呈极显著正相关关系(P<0.01),DSU与DCHN、DUS和DINT相关性较差,线性回归方程可实现DCHN、DUS和DINT之间的转化.综合考虑土壤颗粒组成信息、数值差异和相关性,美国制土壤粒径分级方法是计算土壤体积分形维数的较优选择.
In order to reveal the effect of particle size classification on the determination of soil volume fractal dimension, the particle size distribution of aeolian sandy soil in Mu Us sandy land was determined by laser diffraction technique. Based on the four different grading methods of China, the former Soviet Union, the United States and the international ones The results showed that: (1) The soil texture was coarse in the study area, with the main component of the soil being sand, accounting for more than 90% of the total volume, while the content of clay and silt was relatively small. The soil volume fractal DCH, DUS, DUS, DCHN, DUS, DINT and linear regression of soil clay, silt and sand content (P <0.01). The correlation between DSU and soil silt and sand content was significant (P <0.05), but the fitting effect of linear regression was poor. (3) DCHN, DUS and DINT (P <0.01), the correlation between DSU and DCHN, DUS and DINT is poor, and the linear regression equation can achieve the transformation between DCHN, DUS and DINT.Considering the information of soil particle composition, the numerical difference And correlation, the US soil grading method is to calculate the soil volume fractal dimension Excellent choice.