Multi-scale estimation method for soil moisture content based on distributed temperature information

The soil water migration is one of the key types of researches in geotechnical engineering and geological engineering, and it is an important prerequisite to accurately monitor the spatial-temporal evolution of soil moisture content. Based on the fiber optic distributed temperature sensing (FO-DTS) technology, a high spatial and temporal resolution in-situ monitoring test is conducted to illustrate the proposed method and its feasibility. The continuous natural temperature information of the soil at different depths on the shallow surface (0~0.5 m) is recorded. The amplitude and phase are extracted from the natural temperature data based on the half-pass filtering algorithm, and the soil moisture content is then estimated based on the analytical solution of the one-dimensional transient heat transfer equation. The results show that: (1) The natural temperature information obtained by the FO-DTS technology can be effectively used to estimate the moisture content of shallow soil at different depths. (2) The proposed method can accurately reflect response of the soil moisture under influences of complex weather changes (cloudy, sunny, rain, cold wave, etc.) in the shallow environment (0~0.5 m). (3) The rainfall effects on the change of shallow soil moisture decays with depth and lags in time. The new method, which owns the advantages of high-resolution monitoring, easy expansion and low energy consumption, can realize the rapid content estimation of soil moisture in multi-scale shallow subsurface environment within the range of 0~10 km. This study should be meaningful for the researches on shallow surface-atmosphere interaction, natural hazards and disaster prevention and mitigation in geotechnical engineering.