Multi–scale estimation method of soil moisture content based on distributed temperature information

The soil water migration is one of the key researches in geotechnical engineering and geological engineering, and it is an important prerequisite to accurately monitor the spatio–temporal evolution of soil moisture. In this paper, based on Fiber optic distributed temperature sensing (FO–DTS) technology, an in–situ monitoring test was conducted. By recording the natural temperature information of soil at different depths and using McCallum amplitude and phase analysis algorithm, a novel method for the estimation of soil moisture was proposed. The results show that: (1) the temperature information with high spatial and temporal resolution based on FO–DTS can effectively estimate the shallow soil moisture (0–0.5 m) at different depths; (2) This method can accurately reflect the influence of complex weather changes (cloudy, sunny, rain, cold wave, etc.) on the shallow soil moisture. (3) The influence degree of rainfall on shallow soil moisture decays with depth, and the change of soil moisture has obvious lag. The proposed method has the characteristics of high-resolution monitoring, easy expansion and low energy consumption, and can realize the rapid estimation of multi–scale shallow within the range of 0–10 km. The study of soil moisture migration process and its law based on in–situ monitoring is of great practical significance for disaster warning and prevention of rock and soil mass.