4.7 Article

Effects of measurement resolution on the analysis of temperature time series for stream-aquifer flux estimation

期刊

WATER RESOURCES RESEARCH
卷 47, 期 -, 页码 -

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AMER GEOPHYSICAL UNION
DOI: 10.1029/2011WR010834

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资金

  1. National Science Foundation
  2. Sustainability of Semi-Arid Hydrology and Riparian Areas (SAHRA) of the National Science Foundation [EAR-9876800, EAR 07-53521]
  3. Environmental Protection Agency Science to Achieve Results (EPASTAR) [R833025]
  4. Directorate For Geosciences
  5. Division Of Earth Sciences [1038938] Funding Source: National Science Foundation
  6. EPA [909260, R833025] Funding Source: Federal RePORTER

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[1] From its inception in the mid-1960s, the use of temperature time series (thermographs) to estimate vertical fluxes has found increasing use in the hydrologic community. Beginning in 2000, researchers have examined the impacts of measurement and parameter uncertainty on the estimates of vertical fluxes. To date, the effects of temperature measurement discretization (resolution), a characteristic of all digital temperature loggers, on the determination of vertical fluxes has not been considered. In this technical note we expand the analysis of recently published work to include the effects of temperature measurement resolution on estimates of vertical fluxes using temperature amplitude and phase shift information. We show that errors in thermal front velocity estimation introduced by discretizing thermographs differ when amplitude or phase shift data are used to estimate vertical fluxes. We also show that under similar circumstances sensor resolution limits the range over which vertical velocities are accurately reproduced more than uncertainty in temperature measurements, uncertainty in sensor separation distance, and uncertainty in the thermal diffusivity combined. These effects represent the baseline error present and thus the best-case scenario when discrete temperature measurements are used to infer vertical fluxes. The errors associated with measurement resolution can be minimized by using the highest-resolution sensors available. But thoughtful experimental design could allow users to select the most cost-effective temperature sensors to fit their measurement needs.

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