4.7 Article

Automated calculation of vertical pore-water flux from field temperature time series using the VFLUX method and computer program

期刊

JOURNAL OF HYDROLOGY
卷 420, 期 -, 页码 142-158

出版社

ELSEVIER
DOI: 10.1016/j.jhydrol.2011.11.053

关键词

Heat tracing; Groundwater-surface water interaction; Hyporheic; MATLAB; Dynamic Harmonic Regression; Distributed temperature sensing

资金

  1. National Science Foundation [DGE-0750965, EAR-0911612, EAR-0901480]
  2. Canadian Foundation for Innovation
  3. Directorate For Geosciences
  4. Division Of Earth Sciences [0911612] Funding Source: National Science Foundation
  5. Division Of Earth Sciences
  6. Directorate For Geosciences [0901480] Funding Source: National Science Foundation

向作者/读者索取更多资源

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. (C) 2011 Elsevier B.V. All rights reserved.

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