This dataset includes all files used to model groundwater-surface water exchange at several oxbow ponds on the lower Quillayute River, WA in summer 2022. Sediment temperature data was collected continuously from July to September 2022 at multiple depths using temperature rods that were installed in the subsurface. Temperature data was collected at depths of 1, 4, 7, 11, and 50 cm using internally logging iButton temperature sensors (model DS1922L). Specific discharge across the sediment-water interface was estimated using the tempest1d model; a python-based model that solves a 1-dimensional heat flux equation (McAliley and others, 2022a, McAliley and others, 2022b). The tempest1d model was run at 13 different sites across three oxbow lakes within the study area. Estimates of hourly specific discharge values were determined throughout the deployment period. A negative specific discharge indicates upward flow (groundwater discharge) into the lake. This data release contains the formatted sediment temperature time series data for each site (Inputs.2022.zip), the files needed to run the model (Code.2022.zip), a summary of the specific discharge results at each site (Outputs.2022.zip), and a step-by-step guide on how to run the model at each location (html.output.2022.zip). Site locations are also provided as a .csv file (oxbow.sites.2020.csv). Additional details are provided in the main README file as well as specific readme files within each zip folder.. For further information about the tempest1d modeling approach, please refer to the following publications: McAliley, W.A., Rey, D.M., and Day-Lewis, F.D., 2022a, Data release for tempest1d--Recursive Estimation of Vertical Groundwater/Surface-Water Exchange using Heat Tracing: U.S. Geological Survey data release, available at https://doi.org/10.5066/P99DBTKT. McAliley, W. A., Day-Lewis, F. D., Rey, D., Briggs, M. A., Shapiro, A. M., and Werkema, D., 2022b, Application of recursive estimation to heat tracing for groundwater/surface-water exchange: Water Resources Research, v. 58, no. 6, e2021WR030443, available at https://doi.org/10.1029/2021WR030443.