Characterizing soil water content variability across spatial scales from optimized high-resolution distributed temperature sensing technique

Fiber-optic Distributed Temperature Sensing, when combined with the Single-probe Heat-pulse technique can measure soil moisture (theta) across spatial scales. The key limitation of this system is in obtaining the relationship between soil thermal conductivity (lambda) and theta for a specific field. Using the Department of Energy Atmospheric Radiation Measurement (ARM) site, this study tested a new methodology to account for the spatial variability in the lambda-theta relationship using a Gaussian processes model. The resulting accurate theta measurements (RMSE = 0.03 m(3)m(-3)) were used to characterize the spatial variability of theta across scales and to develop an empirical equation that can correct for the changes in the theta spatial variability observed at different spatial resolutions. In addition, the number of required samples to accurately characterize theta and its variability over scales ranging from 5 m and 350 m were estimated. These findings provide key information to scale soil moisture from centimeters to hun-dreds of meters for process understanding.

Automated summary

Fiber-optic Distributed Temperature Sensing combined with the Single-probe Heat-pulse technique can measure soil moisture across spatial scales. This study tested a new methodology using Gaussian processes model to account for the spatial variability in the relationship between soil thermal conductivity and soil moisture. The findings provide key information for scaling soil moisture across different spatial resolutions.