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为了揭示高原区域地区尺度上土壤全钾的空间异质性及其影响因素,该文采用状态空间方程和传统线性回归模型对该区土壤全钾含量的空间分布进行了模拟,并分析了其与土壤体积质量、黏粒含量、粉粒含量、土壤酸度、降水、气温和海拔高度等因素之间的关系。结果表明,以上变量在30～50km的采样间距下均表现出较好的空间自相关性,其中土壤体积质量、黏粒含量、粉粒含量、降水和气温与土壤全钾之间存在显著的交互相关关系,可用于土壤全钾的状态空间模拟。不同因素组合下的状态空间方程均比使用相同变量的线性回归方程能更好的模拟土壤全钾含量的空间分布。使用土壤体积质量和黏粒含量的双因素状态空间方程模拟效果最好,决定系数R2为0.978,均方根误差(RMSE)为0.049。状态空间模拟在大尺度区域的应用表现出较好的效果,为研究该区其他土壤属性的空间异质性提供了参考。
In order to reveal the spatial heterogeneity of soil total potassium and its influencing factors on the regional scale of the plateau, the spatial distribution of total potassium in the soil was simulated by the state space equation and the traditional linear regression model. Soil volume and quality, clay content, silt content, soil acidity, precipitation, air temperature and altitude and other factors. The results showed that all of the above variables showed good spatial autocorrelation at sampling intervals of 30-50 km. There was significant interaction between soil bulk mass, clay content, silt content, precipitation and air temperature and soil total potassium The correlation can be used to simulate the state of soil total potassium. The state space equation under different combinations of factors can better simulate the spatial distribution of total potassium in soil than the linear regression equation using the same variables. The two-factor state-space equation using soil volume and clay content had the best simulation results, with a determination coefficient R2 of 0.978 and a root mean square error (RMSE) of 0.049. The application of state space simulation in large-scale area shows good effect and provides a reference for studying the spatial heterogeneity of other soil properties in this area.