Abstract

AbstractIn recent decades, distributed temperature sensing (DTS) has emerged as a robust technology for environmental applications, enabling high‐resolution temperature measurements along fibre optic cables (FOCs). The actively heated fibre optic (AHFO) method is employed to monitor soil moisture (, m3 m−3), wherein the soil temperature subsequent to the application of a heat pulse is measured by a DTS (AHFO‐DTS approach). Despite significant improvements in the application of AHFO‐DTS under controlled and natural conditions, the thermal behaviour of soil during multiple saturation–natural drying cycles has been insufficiently evaluated. This study aimed to address this gap by constructing an experimental horizontal soil profile in the laboratory for the application of the AHFO‐DTS method during two successive saturation–drainage–evaporation (SDE) cycles. Three heating strategies were applied to a metallic alloy in contact with a FOC, and calibration models were used to correlate with the thermal conductivity (), cumulative temperature increase (), and maximum temperature increase (). The results indicated that during the second SDE cycle, the highest errors in estimates were observed with the low power‐short heat pulse, whereas the application of the low power‐long duration and high power‐short duration pulses improved the accuracy of calculations. Additionally, errors in estimates escalated under wetter conditions, attributed to a shift in soil heat transfer capacity from the first to the second SDE cycle for > 0.10 m3 m−3. This behaviour was ascribed to thermal hysteresis, arising from the contact resistance of the FOC and the alloy with the surrounding soil. Furthermore, the method exhibited the least sensitivity to this effect and yielded reliable estimates, thus its adoption is recommended. Moreover, the use of the low power‐long duration heating strategy is suggested as it promotes a trade‐off between energy saving and accurate estimates. We concluded that assessing soil thermal response under multiple SDE cycles enhances the comprehension of the AHFO‐DTS method. Overall, our findings provide insights into enhancing the applicability of this approach under field conditions, particularly following irrigation schedules and natural rainfall events.

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