An <scp>ADTS</scp> Toolbox for Automatically Interpreting Active Distributed Temperature Sensing Measurements

Simon, Nataline; Bour, Olivier

doi:10.1111/gwat.13172

Cited by 13 publications

(11 citation statements)

References 41 publications

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“…(2021), represents the moment when the effect of the jacket can be ignored, this can be compared to the beginning of the S g ‐phase in case of no groundwater flow ( t c = 5.6 hr). Following the steps recommended by Simon and Bour (2022), the suggested feature points were extracted, as shown in Figures 5d and 5e ( t d = 4.4 × 10 4 s for 25.5 m, 1.1 × 10 5 s for 74.5 m). This means, as discussed in Section 3.1, that a smaller flow rate thus requires a longer TRT.…”

Section: Resultsmentioning

confidence: 99%

Estimation of Groundwater Flow Rate by an Actively Heated Fiber Optics Based Thermal Response Test in a Grouted Borehole

Zhang

Bayer

et al. 2023

Water Resources Research

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Section: Resultsmentioning

confidence: 99%

Estimation of Groundwater Flow Rate by an Actively Heated Fiber Optics Based Thermal Response Test in a Grouted Borehole

Zhang

Bayer

et al. 2023

Water Resources Research

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“…Note that the raw data of active DTS measurements, the data processing (sorting and quality check), and the definition of significant points are presented in detail in the Supplement. The data were further interpreted using the ADTS toolbox, proposed by Simon and Bour (2022), for automatically interpreting active DTS measurements. The ADTS toolbox contains several MATLAB codes that allow the estimation of the thermal conductivities and the groundwater fluxes (specific discharge) and their respective spatial distribution all along the heated section.…”

Section: Active Dts Measurementsmentioning

confidence: 99%

“…The method is based on an analytical approach proposed and validated by Simon et al (2021a), which consists of defining, for each measurement point along the heated section, the optimized values of thermal conductivity and flux that allow the reproduction of, at best, the associated temperature increase measured over the heating period. The use of the ADTS toolbox also provides an estimate of the associated uncertainties (Simon and Bour, 2022).…”

Section: Active Dts Measurementsmentioning

confidence: 99%

“…It clearly appears that the main advantages of the approach are (i) the low uncertainty on fluxes estimates and (ii) the associated estimates of thermal conductivities. The use of the ADTS toolbox that automatically interprets active DTS measurements (Simon and Bour, 2022) highly facilitates the data interpretation, which is finally much easier than the interpretation of passive DTS measurements. Contrary to passive DTS measurements, the interpretation of active DTS measurements provides estimates of thermal conductivities with a very good accuracy.…”

Section: Accuracy Of Fluxes Estimated With Active Dts Measurementsmentioning

confidence: 99%

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Combining passive and active distributed temperature sensing measurements to locate and quantify groundwater discharge variability into a headwater stream

Simon

Bour

Faucheux

et al. 2022

Hydrol. Earth Syst. Sci.

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Abstract. Exchanges between groundwater and surface water play a key role for ecosystem preservation, especially in headwater catchments where groundwater discharge into streams highly contributes to streamflow generation and maintenance. Despite several decades of research, investigating the spatial variability in groundwater discharge into streams still remains challenging mainly because groundwater/surface water interactions are controlled by multi-scale processes. In this context, we evaluated the potential of using FO-DTS (fibre optic distributed temperature sensing) technology to locate and quantify groundwater discharge at a high resolution. To do so, we propose to combine, for the first time, long-term passive DTS measurements and active DTS measurements by deploying FO cables in the streambed sediments of a first- and second-order stream in gaining conditions. The passive DTS experiment provided 8 months of monitoring of streambed temperature fluctuations along more than 530 m of cable, while the active DTS experiment, performed during a few days, allowed a detailed and accurate investigation of groundwater discharge variability over a 60 m length heated section. Long-term passive DTS measurements turn out to be an efficient method to detect and locate groundwater discharge along several hundreds of metres. The continuous 8 months of monitoring allowed the highlighting of changes in the groundwater discharge dynamic in response to the hydrological dynamic of the headwater catchment. However, the quantification of fluxes with this approach remains limited given the high uncertainties on estimates, due to uncertainties on thermal properties and boundary conditions. On the contrary, active DTS measurements, which have seldom been performed in streambed sediments and never applied to quantify water fluxes, allow for the estimation of the spatial distribution of both thermal conductivities and the groundwater fluxes at high resolution all along the 60 m heated section of the FO cable. The method allows for the description of the variability in streambed properties at an unprecedented scale and reveals the variability in groundwater inflows at small scales. In the end, this study shows the potential and the interest of the complementary use of passive and active DTS experiments to quantify groundwater discharge at different spatial and temporal scales. Thus, results show that groundwater discharges are mainly concentrated in the upstream part of the watershed, where steepest slopes are observed, confirming the importance of the topography in the stream generation in headwater catchments. However, through the high spatial resolution of measurements, it was also possible to highlight the presence of local and highly contributive groundwater inflows, probably driven by local heterogeneities. The possibility to quantify groundwater discharge at a high spatial resolution through active DTS offers promising perspectives for the characterization of distributed responses times but also for studying biogeochemical hotspots and hot moments.

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“…Estimation of the on‐site groundwater flux is an inverse problem in field studies (Anderson 2005). These studies have performed field experiments to measure the TD profiles and used the heat transfer models to estimate the groundwater flux (Hatch et al 2006; Briggs et al 2014; Caissie et al 2014; Zhu et al 2015; Abesser et al 2021; Simon and Bour 2022 ) . The flux is estimated by fitting a developed analytical or numerical model to the TD data and surface temperature changes measured in a study area.…”

Section: Introductionmentioning

confidence: 99%

Effects of Soil Type and Thermal Boundary on Predicting Temperature Profiles and Groundwater Fluxes

et al. 2023

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In the last few years, several articles have studied heat as a groundwater tracer and developed analytical geothermal solutions to predict the subsurface temperature and groundwater fluxes. These solutions can be sorted into steady‐state and transient solutions. The steady‐state solutions cannot describe the time‐varying subsurface temperature, while the transient solutions ignore subsurface thermal boundary effects. Moreover, soil type may be another crucial factor significantly affecting the prediction results. This study compares six existing classical analytical solutions to examine the effects of soil types and subsurface thermal boundaries on simulating temperature‐depth profiles and estimating groundwater fluxes. Several synthetic cases are built by considering the common soil types, sand and clay, to demonstrate their effects on predicting the profiles. A field case is used to show the effect of subsurface thermal boundaries on the groundwater flux estimated by an inverse approach. The study results indicate that the soil types have significant influences on simulating the profiles, and the influences grow with time. Some existing solutions may give inaccurate estimations of the field groundwater flux since they merely consider the heat source from the temperature variations on the ground surface but ignore possible thermal boundary effects in the subsurface. These findings will be valuable to those applying heat as a tracer to investigate infiltration.

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An ADTS Toolbox for Automatically Interpreting Active Distributed Temperature Sensing Measurements

Cited by 13 publications

References 41 publications

Estimation of Groundwater Flow Rate by an Actively Heated Fiber Optics Based Thermal Response Test in a Grouted Borehole

Estimation of Groundwater Flow Rate by an Actively Heated Fiber Optics Based Thermal Response Test in a Grouted Borehole

Combining passive and active distributed temperature sensing measurements to locate and quantify groundwater discharge variability into a headwater stream

Effects of Soil Type and Thermal Boundary on Predicting Temperature Profiles and Groundwater Fluxes

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