TY - JOUR
T1 - Automated calculation of vertical pore-water flux from field temperature time series using the VFLUX method and computer program
AU - Gordon, Ryan P.
AU - Lautz, Laura K.
AU - Briggs, Martin A.
AU - McKenzie, Jeffrey M.
N1 - Funding Information:
Field data were collected in collaboration with Timothy Daniluk and Danielle Hare. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-0750965 , and is partially based upon work supported by the National Science Foundation under Grant Nos. EAR-0911612 and EAR-0901480 and the Canadian Foundation for Innovation.
Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012/2/14
Y1 - 2012/2/14
N2 - Heat is a useful tracer for quantifying groundwater-surface water interaction, but analyzing large amounts of raw thermal data has many challenges. We present a computer program named VFLUX, written in the MATLAB computing language, for processing raw temperature time series and calculating vertical water flux in shallow sub-surface-water systems. The step-by-step workflow synthesizes several recent advancements in signal processing, and adds new techniques for calculating flux rates with large numbers of temperature records from high-resolution sensor profiles. The program includes functions for quantitatively evaluating the ideal spacing between sensor pairs, and for performing error and sensitivity analyses for the heat transport model due to thermal parameter uncertainty. The program synchronizes and resamples temperature data from multiple sensors in a vertical profile, isolates the diurnal signal from each time series and extracts its amplitude and phase angle information using Dynamic Harmonic Regression (DHR), and calculates vertical water flux rates between multiple sensor pairs using heat transport models. Flux rates are calculated every 1-to-2. h using four similar analytical methods. One or more " sliding analysis windows" can be used to automatically identify any number of variably spaced sensor pairs for flux calculations, which is necessary when a single vertical profile contains many sensors, such as in a high-resolution fiber-optic distributed temperature sensing (DTS) profile. We demonstrate the new method by processing two field temperature time series datasets collected using discrete temperature sensors and a high-resolution DTS profile. The analyses of field data show vertical flux rates significantly decreasing with depth at high-spatial resolution as the sensor profiles penetrate shallow, curved hyporheic flow paths, patterns which may have been obscured without the unique analytical abilities of VFLUX.
AB - Heat is a useful tracer for quantifying groundwater-surface water interaction, but analyzing large amounts of raw thermal data has many challenges. We present a computer program named VFLUX, written in the MATLAB computing language, for processing raw temperature time series and calculating vertical water flux in shallow sub-surface-water systems. The step-by-step workflow synthesizes several recent advancements in signal processing, and adds new techniques for calculating flux rates with large numbers of temperature records from high-resolution sensor profiles. The program includes functions for quantitatively evaluating the ideal spacing between sensor pairs, and for performing error and sensitivity analyses for the heat transport model due to thermal parameter uncertainty. The program synchronizes and resamples temperature data from multiple sensors in a vertical profile, isolates the diurnal signal from each time series and extracts its amplitude and phase angle information using Dynamic Harmonic Regression (DHR), and calculates vertical water flux rates between multiple sensor pairs using heat transport models. Flux rates are calculated every 1-to-2. h using four similar analytical methods. One or more " sliding analysis windows" can be used to automatically identify any number of variably spaced sensor pairs for flux calculations, which is necessary when a single vertical profile contains many sensors, such as in a high-resolution fiber-optic distributed temperature sensing (DTS) profile. We demonstrate the new method by processing two field temperature time series datasets collected using discrete temperature sensors and a high-resolution DTS profile. The analyses of field data show vertical flux rates significantly decreasing with depth at high-spatial resolution as the sensor profiles penetrate shallow, curved hyporheic flow paths, patterns which may have been obscured without the unique analytical abilities of VFLUX.
KW - Distributed temperature sensing
KW - Dynamic Harmonic Regression
KW - Groundwater-surface water interaction
KW - Heat tracing
KW - Hyporheic
KW - MATLAB
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U2 - 10.1016/j.jhydrol.2011.11.053
DO - 10.1016/j.jhydrol.2011.11.053
M3 - Article
AN - SCOPUS:84856214379
SN - 0022-1694
VL - 420-421
SP - 142
EP - 158
JO - Journal of Hydrology
JF - Journal of Hydrology
ER -