Supporting Data for King and Neilson 2019: Quantifying Reach-Average Effects of Hyporheic Exchange on Arctic River Temperatures in an Area of Continuous Permafrost

• Main Authors: Bethany Neilson, Tyler King
• Format: Dataset
• Language: unknown
• Published: 2019
• Subjects: Heat Flux; Permafrost; River Temperature; Modeling; Hyporheic; Arctic; albedo; permafrost
• Online Access: https://search.dataone.org/view/sha256:2393e6f4939cdf371f14d158f8c30e6c6528ef9fc760db73b8a8c69fba685409

These date files provide observations, model calibration, and model testing results used in King and Neilson 2019, \"Quantifying Reach-Average Effects of Hyporheic Exchange on Arctic River Temperatures in an Area of Continuous Permafrost\" published in Water Resources Research. Note on Units: All temperature values are in degrees Celsius. All discharge values are in cubic meters per second All solute concentrations are in milligrams sodium-chloride per L Files Description: ParetoOptimal_Solute_Temperature.dat: Time series of simulated main channel solute breakthrough curve and temperature at 1500 m downstream of the injection location using the Pareto optimal model calibration. Solute_EndMember_Solute_Temperature.dat: Time series of simulated main channel solute breakthrough curve and temperature at 1500 m downstream of the injection location using the solute end member model calibration. Temperauture_EndMember_Solute_Temperature.dat: Time series of simulated main channel solute breakthrough curve and temperature at 1500 m downstream of the injection location using the temperature end member model calibration. ParetoOptimal_HTS_Solute.dat: Time series of simulated solute breakthrough curve in sediment at 1500 m downstream of the injection location using the Pareto optimal model calibration. ParetoOptimal_HTS_Temp.dat: Time series of simulated sediment temperature at 1500 m downstream of the injection location using the Pareto optimal model calibration. YYYY-Site9-Site8_HeatFluxes-withHTS.DAT: Time series of simulated heat fluxes for the test reach for the simulation period in year “YYYY” using the Pareto optimal model calibration. YYYY-Site9-Site8_ModelOutput-withHTS.DAT: Time series of simulated temperature at Site8 for the test reach for the simulation period in year “YYYY” using the Pareto optimal model calibration. YYYY-Site9-Site8_ModelOutput-noHTS.DAT: Time series of simulated temperature at Site8 for the test reach for the simulation period in year “YYYY” using the Pareto optimal model calibration, but setting QHTS to zero. 2015-Site8_HeatFlux_SedWarm+X.DAT: Time series of simulated heat fluxes for the test reach in the simulation period in 2015 using Pareto optimal model calibration and changing observed ground temperatures by X degrees C. 2015-Site8_ModelTemp_SedWarm.DAT: Time series of simulated main channel temperatures at Site8 for the test reach in the simulation period in 2015 using Pareto optimal model calibration and changing observed ground temperatures by plus or minus 1, 2 or 4 degrees C. Site8_MCTemp_2013-2017_DegC.csv: Time series of observed main channel temperature at Site 8. Site8Discharge_cms.csv: Time series of observed discharge at Site 8. Site9_MCTemp_2013-2017_DegC.csv: Time series of observed main channel temperature at Site 9. Site9_Discharge_cms.csv: Time series of observed discharge at Site 9. Site9_Sediment_Temperatures_DegC.csv: Time series of sediment/ground temperatures at Site 9 from 2017 at depths of 10, 20, 30, 40, 50, and 60 cm below the river bed. 201707DDTS.csv: Time series of main channel and piezometer solute concentrations and temperatures during tracer studies conducted on the “DD” day of July 2017. Model_Cell_Extracted_Wetted_Widths_m_And_Interpolated_Discharge_cms.csv: Wetted widths extracted from aerial imagery and associated spatially interpolated discharge for each 10 m model cell. These data were used to estimate reach average wetted widths for the calibration and test simulations. KupSolarRad_2014-2016.csv: Observed incoming and outgoing shortwave radiation at Site 9 in the summers (June – August) of 2014, 2015, and 2016. These observations were used to estimate time varying albedo.