Sediment temperatures and estimates of vertical groundwater-surface water exchange using the tempest1d model: Data from the mainstem Quillayute River, WA, summer 2024

This dataset includes sediment temperature data collected from seven sites on the mainstem of the Quillayute River in the summer of 2024. Sediment temperatures were collected at up to four depths (1, 4, 7, and 11 centimeters) at each location using a temperature rod that was installed into the streambed. See "quillayute.sites.2024.csv" for field IDs, sediment thermal properties, and locations of these seven sites. All temperature data was collected using internally logging iButton temperature sensors (model DS1922L).
These temperature data were used to estimate groundwater-surface water exchange, calculated as specific discharge, across the sediment-water interface. Specific discharge was estimated using the tempest1d model; a Python-based model that uses a recursive-estimation framework (McAliley and others, 2022a; McAliley and others, 2022b). In this framework one-dimensional convection/conduction partial differential equation is formulated as a state-space model using a finite difference approximation consistent with that of VS2DH (Healy and Ronan, 1996). An Extended Kalman Filter (EKF) is used to estimate specific discharge in discrete time coincident with vertical temperature profile observations. The EKF predicts system states using the process model and prior state covariance values and subsequently corrects these predicted states by assimilating new temperature observations. Tempest1d supports fixed-interval smoothing via the Extended Rauch-Tung-Striebel Smoother (ERTSS), an algorithm based on the EKF. ERTSS uses state and covariance estimates from the EKF filter in a backwards pass, smoothing the EKF predicted states.
Estimates of hourly specific discharge values were determined throughout the deployment period. A negative specific discharge indicates upward flow (groundwater discharge) into the river. Data from at least three depths are needed to run this model. Data loss at 4 of the 7 locations meant the tempest1d model could only be used at three of the sites.
For locations that did not have enough data to run the tempest1d model, raw sediment temperature data are provided in the zip folder "Sed.temps.zip". For locations where the tempest1d model was run, sediment temperature data are included in the zip folder "Inputs.zip"
All the files needed to run the tempest1d model are provided in this data release: the formatted model input of sediment temperature time series data for each site (Inputs.2024.zip), the source code needed to run the model (Code.2024.zip), a summary of the specific discharge results at each site (Outputs.2024.zip), and a step-by-step guide on how to run the model at each location (html.output.2024.zip). 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:
Healy, R.W., and Ronan, A.D., 1996, Documentation of computer program VS2Dh for simulation of energy transport in variably saturated porous media: Modification of the US Geological Survey's computer program VS2DT, U.S. Geological Survey, Water Resources Investigation Report 96-4230, https://doi.org/10.3133/wri964230.
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, 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 Resour. Res. 58, e2021WR030443. doi:10.1029/2021WR030443.
 
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