Research on Spatial Variability of Soil Water and Salt in Weigan River Irrigation Area
Shunjun Hu, Kang Shaozhong
Abstract
Shunjun Hu, Kang Shaozhong
Abstract
According to the data from 150 sampling points designed by using the methods of straight line sampling and rectangle net sampling. The spatial variability of soil electrical conductivity and mass soil water content at the newly-reclaimed land were discussed and the rational sampling number for soil electrical conductivity and mass soil water content was given under different believable level and exactitude through the classic statistics analysis. By the analysis of self-correlation and semi-variance, the spatial variability structure and semi-variance function model of soil electrical conductivity and mass soil water content were also discussed. The results showed that the spatial variability of soil electrical conductivity and mass soil water content are all with structure, the maximal correlated ranges of soil electrical conductivity and mass soil water content are 9 m and 6.4 m, respectively. Both of the semi-variance functions can be fitted with linear with sill models.
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According to the data from 150 sampling points designed by using the methods of straight line sampling and rectangle net sampling. The spatial variability of soil electrical conductivity and mass soil water content at the newly-reclaimed land were discussed and the rational sampling number for soil electrical conductivity and mass soil water content was given under different believable level and exactitude through the classic statistics analysis. By the analysis of self-correlation and semi-variance, the spatial variability structure and semi-variance function model of soil electrical conductivity and mass soil water content were also discussed. The results showed that the spatial variability of soil electrical conductivity and mass soil water content are all with structure, the maximal correlated ranges of soil electrical conductivity and mass soil water content are 9 m and 6.4 m, respectively. Both of the semi-variance functions can be fitted with linear with sill models.
Key concepts: Environmental science, Soil science, Sampling (signal processing), Water content, Soil salinity, Spatial variability, Hydrology (agriculture), Leaching model