Quantifying surface water–groundwater interactions using time series analysis of streambed thermal records: Method development

Abstract

[1] We present a method for determining streambed seepage rates using time series thermal data. The new method is based on quantifying changes in phase and amplitude of temperature variations between pairs of subsurface sensors. For a reasonable range of streambed thermal properties and sensor spacings the time series method should allow reliable estimation of seepage rates for a range of at least ±10 m d À1 (±1.2 Â 10 À2 m s À1 ), with amplitude variations being most sensitive at low flow rates and phase variations retaining sensitivity out to much higher rates. Compared to forward modeling, the new method requires less observational data and less setup and data handling and is faster, particularly when interpreting many long data sets. The time series method is insensitive to streambed scour and sedimentation, which allows for application under a wide range of flow conditions and allows time series estimation of variable streambed hydraulic conductivity. This new approach should facilitate wider use of thermal methods and improve understanding of the complex spatial and temporal dynamics of surface water-groundwater interactions.Citation: Hatch, C. E., A. T. Fisher, J. S. Revenaugh, J. Constantz, and C. Ruehl (2006), Quantifying surface water -groundwater interactions using time series analysis of streambed thermal records: Method development, Water Resour.

Changes in stream temperatures in response to restoration of groundwater discharge and solar heating in a culverted, urban stream

“…These velocities can be converted to fluid velocity by multiplying by the ratio of the saturated streambed material's heat capacity to that of the fluid (Hatch et al, 2006). The interrelation between (1) and (2), in which velocity is found on both sides of (1), requires that fluid velocities be calculated with an iterative process.…”

“…We lost two of these piezometer nests (PN3-L and PN5-M) due to large storm flows, which ripped them out of the streambed, and the data from another piezometer nest (PN3-M) due to a faulty temperature datalogger, leaving 15 piezometer nests for the entire summer monitoring season. We combined our temperature time-series data with an analytical solution to quantify baseflow velocities at each of the measurement sites (Hatch et al, 2006). Streambed temperatures and their lagged thermal response to surface conditions can be used to calculate groundwater velocities in both gaining and losing streams as long as the vertical separation is known (Hatch et al, 2006; see also Keery et al, 2007, for further discussion of a similar method).…”

“…We combined our temperature time-series data with an analytical solution to quantify baseflow velocities at each of the measurement sites (Hatch et al, 2006). Streambed temperatures and their lagged thermal response to surface conditions can be used to calculate groundwater velocities in both gaining and losing streams as long as the vertical separation is known (Hatch et al, 2006; see also Keery et al, 2007, for further discussion of a similar method). Daily velocities may be calculated for a given time series of streambed temperatures using either (1) the ratio of decreasing amplitude in the daily streambed temperature sig-nal with depth or (2) the phase shift in the timing of the peak measured temperature with depth.…”

“…After filtering our streambed temperature data by subtracting a 24-h running average from the measured data, we use the amplitude ratio (Hatch et al, 2006) to calculate velocity with peak manual discharge measurements are lower. We fit power-law curves to stage versus discharge plots, thereby enabling direct computation of discharge from the stage data.…”

“…Streambed temperature time series are an effective natural tracer for detecting the rate and direction of groundwater movement and, thus, are a primary method for measuring surface watergroundwater interactions (Hatch et al, 2006). Streambed temperature measurements have been used to determine areas of maximum and minimum discharge within a stream reach (Conant, 2004), to develop a field-scale analytical solution for determining groundwater discharge rates (Schmidt et al, 2007), and to quantify groundwater flow in the vicinity of stream barriers, such as natural and constructed dams (Fanelli and Lautz, 2008).…”