Evaluation of Improved Model to Accurately Monitor Soil Water Content

Abstract

The accurate monitoring of soil water content during the growth of crops is of great importance to improve agricultural water use efficiency. The Campbell model is one of the most widely used models for monitoring soil moisture content from soil thermal conductivities in farmland, which always needs to be calibrated due to the lack of adequate original data and the limitation of measurement methods. To precisely predict the water content of complex soils using the Campbell model, this model was evaluated by investigating several factors, including soil texture, bulk density and organic matter. The comparison of the R2 and the reduced Chi-Sqr values, which were calculated by Origin, was conducted to calibrate the Campbell model calculated. In addition, combining factors of parameters, a new parameter named m related to soil texture and the organic matter was firstly introduced and the original fitting parameter, E, was improved to an expression related to clay fraction and the organic matter content in the improved model. The soil data collected from both the laboratory and the previous literature were used to assess the revised model. The results show that most of the R2 values of the improved model are >0.95, and the reduced Chi-Sqr values are <0.01, which presents a better matching performance compared to the original. It is concluded that the improved model provides more accurate monitoring of soil water content for water irrigation management.