Passive distributed temperature sensing (PDTS)-based moisture content estimation in agricultural soils under different vegetative canopies

Abstract

A semi-empirical Boltzmann model is proposed to describe the relationship between the rate of temperature increase and soil moisture content, which can replace the existing complicated numerical iterative algorithm. The proposed method greatly simplifies the calculation process and improves the applicability of the passive distributed temperature sensing (PDTS) technology. A field test was performed in the Loess Plateau of China to validate the capability of this method. The field site has four typical land cover conditions: bare soil (G1), plastic mulch (G2), plastic mulch cover with potatoes (G3), and plastic much cover with maize (G4). The monitoring results indicate that for G1 and G2, the relationship between soil moisture content and the rate of temperature increase can be quantitatively described by the Boltzmann model with a root-mean-square error of 0.024 m3/m3. For G3, a linear relationship is found. In contrast, the PDTS technology is not applicable for G4 because a constant ground surface heat power from solar radiation and small air temperature fluctuations are preconditions of PDTS. If the coefficient of determination (R2) for fitting rate of temperature increase is larger than 0.9, the ground surface heat power by solar radiation can be considered as a constant.