Uncertainties in Measuring Soil Moisture Content with Actively Heated Fiber-Optic Distributed Temperature Sensing

Abstract

Actively heated fiber-optic distributed temperature sensing (aFO-DTS) measures soil moisture content at sub-meter intervals across kilometres of fiber-optic cable. The technology has great potential for environmental monitoring but calibration at field scales with variable soil conditions is challenging. To better understand and quantify the errors associated with aFO-DTS soil moisture measurements, we use a parametric numerical modeling approach to evaluate different error factors for uniform soil. A thermo-hydrogeologic, unsaturated numerical model is used to simulate a 0.01 m by 0.01 m two-dimensional domain, including soil and a fiber-optic cable. Results from the model are compared to soil moisture values calculated using the commonly used Tcum calibration method for aFO-DTS. The model is found to have high accuracy between measured and observed saturations for static hydrologic conditions but shows discrepancies for more realistic settings with active recharge. We evaluate the performance of aFO-DTS soil moisture calculations for various scenarios, including varying recharge duration and heterogeneous soils. The aFO-DTS accuracy decreases as the variability in soil properties and intensity of recharge events increases. Further, we show that the burial of the fiber-optic cable within soil may adversely affect calculated results. The results demonstrate the need for careful selection of calibration data for this emerging method of measuring soil moisture content.

Fiber Optic Network Technology of Communication of Specialists via Mental Neurointerfaces

“…A survey on integrated access and backhaul networks (Zhang, Kishk, & Alouini, 2021). Uncertainties in measuring soil moisture content with actively heated fiber-optic distributed temperature sensing (Wu, Lamontagne-Hallé, & McKenzie, 2021). A High-dynamic-range digital RF-Over-Fiber Link for MRI receive coils using delta-sigma modulation (Fan et al, 2021).…”

Variability in Soil Moisture by Natural and Artificial Snow: A Case Study in Mt. Balwang Area, Gangwon-do, South Korea

“…Soil moisture varies seasonally and exhibits lower values in the winter (frozen soil) and higher values in the warm period, and it affects the precipitation and vegetation cover (Choi et al, 2010;Wei et al, 2021). Moreover, the uncertainties in the in-situ sensors increases with variability in soil properties and intensity of recharge events (Wu et al, 2021). Soil temperature sensors placed 2-10 cm below the soil surface have also been used to detect the presence or absence of snow cover (Lundquist and Lott, 2008;Schmid et al, 2012).…”