Spatial variability analysis of soil nutrients characteristics in the rape field based on GIS
Wang We
Abstract
Wang We
Abstract
In this paper, geo-statistics combined with GIS was applied to analyze the spatial variability of soil nutrients characteristics including pH value, organic matter, total nitrogen, available phosphorus, available potassium and available boron in the rape field, and scatter diagrams of the distribution of soil nutrients were constructed, to provid a theoretical basis for effective fertilization. The results showed that all of soil nutrients in the coefficient of variation ranged from 16.88% to 65.42%, which belonged to moderate degree of variation. Nitrogen and potassium's nugget coefficient was less than 0.25, with a strong spatial correlation; pH value and three other nutrients had moderate spatial correlation. After a semi-variance function analysis, the Gaussian model, exponential model, spherical and linear model were used to fitt model parameters. The results indicateal that there was significant spatial difference in soil physical and chemical characteristics of the study area. In the southwest region, nutrient content was high, in northeast regional nutrient content was generally low, and its main influencing factors were the structural and human randomness factors.
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In this paper, geo-statistics combined with GIS was applied to analyze the spatial variability of soil nutrients characteristics including pH value, organic matter, total nitrogen, available phosphorus, available potassium and available boron in the rape field, and scatter diagrams of the distribution of soil nutrients were constructed, to provid a theoretical basis for effective fertilization. The results showed that all of soil nutrients in the coefficient of variation ranged from 16.88% to 65.42%, which belonged to moderate degree of variation. Nitrogen and potassium's nugget coefficient was less than 0.25, with a strong spatial correlation; pH value and three other nutrients had moderate spatial correlation. After a semi-variance function analysis, the Gaussian model, exponential model, spherical and linear model were used to fitt model parameters. The results indicateal that there was significant spatial difference in soil physical and chemical characteristics of the study area. In the southwest region, nutrient content was high, in northeast regional nutrient content was generally low, and its main influencing factors were the structural and human randomness factors.
Key concepts: Nutrient, Soil science, Spatial variability, Environmental science, Soil nutrients, Phosphorus, Spatial distribution, Nitrogen