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

TLDR

The study introduces a time‑series thermal method to estimate streambed seepage rates from subsurface temperature data. The method quantifies phase and amplitude changes between paired subsurface sensors, is insensitive to scour and sedimentation, and enables variable hydraulic conductivity estimation. It reliably estimates seepage rates up to ±10 m d⁻¹, with amplitude variations most sensitive at low flows and phase variations at higher flows, while requiring less data and processing than forward modeling and broadening the applicability of thermal techniques for surface‑water–groundwater interaction studies.

Abstract

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 −1 (±1.2 × 10 −2 m s −1 ), 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.