Document Type : Research Paper
Authors
1
Soil and Water Research Department, Isfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan, Iran
2
Soil and Water Research Department, Isfahan Agricultural and Natural Resources Research and Education Center. Agricultural Research, Education and Extension organization (AREEO), Isfahan, Iran.
Abstract
Evaluating the spatial variability of soil properties is an important prerequisite for precision agriculture. This research was conducted on 84 soil samples from different areas of Chadegan city (Isfahan province). With the aim of evaluating the spatial variability of some soil nutrient elements, including organic carbon, soil-available phosphorus, potassium, zinc, copper, manganese, and iron. The spatial correlation of each variable with a specific semi-variable and the best fitting model for each variable were selected. Interpolation was done using normal Kriging and Inverse Distance Weighting with powers of 1 to 3 methods. The accuracy of the distribution maps of these variables was evaluated by the Mean bias error (MBE) the standard root mean square error (NRMSE), and the coefficient of determination (R2). The results showed that all studied properties had moderate spatial dependence, which shows the effect of management factors such as fertilization, plowing, irrigation, etc. on these variables. The exponential model was the most accurate to predict organic carbon, phosphorus, potassium and zink variables while iron, copper, and manganese were best fitted with an spherical model. For phosphorus, iron, and copper variables, the Inverse Distance Weighting with the power of 1 (IDW-1) and for organic carbon, potassium, zinc, and manganese normal kriging methods were recognized as the best interpolation methods. According to the spatial distribution maps, the studied area is sufficient in terms of potassium, copper and manganese nutrients, and in other cases, the use of fertilizers and organic materials is necessary to increase soil fertility.
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