Assessing soil water content variability through active heat distributed fiber optic temperature sensing

Abstract

Soil spatial variability is a key point for the sustainable water management in agriculture. Fractal techniques provide proper tools to analyze soil spatial variability searching for statistical self-similarity patterns among different scales. Although they have been extensively applied to study the soil properties variability, its applicability for the soil water content (SWC) distribution is complicated because requires many data difficult to obtain with the typical point soil water sensors. Recently, a fiber optic distributed temperature sensor has been used to measure soil thermal properties which relate to SWC. These sensors provide large amount of data with high spatial and temporal resolution, thus filling the gap of point soil water sensors. In the present work, soil temperature was measured with a Distributed Temperature Sensing (DTS) and SWC was estimated by different fitting functions which have been studied with focus on spatial variability. Temperature was measured in a 133 m fiber optic cable laid in a sandy soil field plot. A The Active Heat Fiber Optic (AHFO) method was used, with 12 cm sampling resolution, and heat pulses (19,4 W/m during 2 min) were applied. The temperature data were correlated to SWC, considering the integration of temperature during the heat pulse T cum , and then the datasets Tcum-SWC were fitted to the best fit statistical function (exponential, potential and polynomial). The results showed that the T cum distribution presented a non-Gaussian pattern. Additionally, highly anti-persistent patterns have been detected for the larger spatial scaling lags. The function`s performance was different thus, the exponential function reproduced better the absolute moments of the temperature profile but it failed reproducing the non-Gaussian behavior.

Review of Novel and Emerging Proximal Soil Moisture Sensors for Use in Agriculture

“…Much of the current research on AHFO is focused on use of Fibre Bragg Gratings (FBG) in which variations in the refractive index are inscribed into the core of an optical fiber at prescribed locations to enable precise location and measurement of distortions. AHFO approaches have been used to study dripper wetting patterns in repacked soils [96], along transects at discreate depths [102,106], and as a multidepth soil moisture sensor [104]. Ref.…”

“…They reported that the correlation with a commercial soil moisture sensor (Decagon Devices 5TE sensors) ranged from 0.46 to 0.87. Similarly [106] measured changes in temperature every 12 cm along a 300 m fiber optic cable, buried at 0.2 m and 0.4 m depth along a 133 m long transect at a research farm in Spain. Ref.…”

“…They reported that the correlation with a commercial soil moisture sensor (Decagon Devices 5TE sensors) ranged from 0.46 to 0.87. Similarly [106] measured changes in temperature every 12 cm along a 300 m fiber optic cable, buried at 0.2 m and 0.4 m depth along a 133 m long transect at a research farm in Spain. [103] developed a down hole FBG soil moisture sensor with 1.25 cm depth resolution to a depth of 1 m for laboratory studies, and to a depth of 18 m for a field study, by wrapping a carbon-fiber-heated FBG optic fiber around a 5 cm diameter PVC tube ( Figure 5).…”

“…The use of AHFO approaches in agriculture may however be limited by their susceptibility to damage and deformation of the optic fiber by plant roots, agricultural machinery, and seasonal soil shrink-swelling which may limit the use of AHFO to forms of agriculture with shallow or no tillage, or installation of AHFO beneath the depth of tillage and root growth which isn't particularly useful for sensing crop moisture stress. Application of AHFO approaches in agriculture are also potentially limited by the need for good sensor-soil contact, need for considerable soil disturbance during installation, slow response time, and complex analysis of large amounts of data [107], and potential need for soil-specific calibrations as indicated by [102,106].…”