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Using distributed temperature sensing to monitor field scale dynamics of ground surface temperature and related substrate heat flux
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| Created: | Mar 31, 2018 at 8:23 p.m. | |
| Last updated: | Apr 09, 2018 at 8:35 p.m. | |
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Abstract
We present one of the first studies of the use of distributed temperature sensing (DTS) along fibre-optic cables to purposely monitor spatial and temporal variations in ground surface temperature (GST) and soil temperature, and provide an estimate of the heat flux at the base of the canopy layer and in the soil. Our field site was at a groundwater-fed wet meadow in the Netherlands covered by a canopy layer (between 0 and 0.5 m thickness) consisting of grass and sedges. At this site, we ran a single cable across the surface in parallel 40 m sections spaced by 2 m, to create a 40 m × 40 m monitoring field for GST. We also buried a short length (≈10 m) of cable to depth of 0.1 ± 0.02 m to measure soil temperature. We monitored the temperature along the entire cable continuously over a two-day period and captured the diurnal course of GST, and how it was affected by rainfall and canopy structure. The diurnal GST range, as observed by the DTS system, varied between 20.94 and 35.08 °C; precipitation events acted to suppress the range of GST. The spatial distribution of GST correlated with canopy vegetation height during both day and night. Using estimates of thermal inertia, combined with a harmonic analysis of GST and soil temperature, substrate- and soil-heat fluxes were determined. Our observations demonstrate how the use of DTS shows great promise in better characterizing area-average substrate/soil heat flux, their spatiotemporal variability, and how this variability is affected by canopy structure. The DTS system is able to provide a much richer data set than could be obtained from point temperature sensors. Furthermore, substrate heat fluxes derived from GST measurements may be able to provide improved closure of the land surface energy balance in micrometeorological field studies. This will enhance our understanding of how hydrometeorological processes interact with near-surface heat fluxes.
Raw project data is available by contacting ctemps@unr.edu
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