paf_943 NicholasThirosnicholas.thiros@umontana.edu https://orcid.org/0000-0002-1704-1031 EricaSiirila-WoodburnERWoodburn@lbl.gov P. JamesDennedy-Frankpjdf@northeastern.edu KennethWilliamskhwilliams@lbl.gov W. PaytonGardnerUniversity of Montanapayton.gardner@mso.umt.edu Department of Energy (DOE) EPSCoR grant DE-FOA-0002215 fundingOrganization DOE ORISE Office of Science Graduate Student Research (SCGSR) Program fundingOrganization U.S. DOE > Office of Science > Biological and Environmental Research (BER) http://dx.doi.org/10.13039/100006206 fundingOrganization 2023-01-19 Groundwater residence times provide fundamental descriptions of hydrologic dynamics and mixing processes in mountainous watersheds. Yet, few observational datasets that can constrain groundwater residence times over broad timescales are available in high elevation mountain systems. Here we present field observations from May 2021 of dissolved noble gases (He, Ne, Ar, Kr, and Xe), Chloroflourcarbons (CFCs), Sulfurhexaflouride (SF6), and tritium (3H) sampled from the Pumphouse Lower Montane study site (wells PLM1, PLM6, and PLM7) within the East River Watershed, Colorado. The presented noble gas (PLM_noblegas_2021.csv) and environmental tracer (PLM_tracers_2021.csv) observation datasets, along with the associated modeling scripts, aide in quantifying groundwater residence times and recharge conditions in a high elevation mountain system. Furthermore, the modeling scripts quantify groundwater residence time and noble gas recharge condition uncertainties using a novel Markov-chain Monte Carlo approach. All data modeling scripts are written in the Python code.GroundwaterResidence TimesEnvironmental TracersESS-DIVE File Level Metadata Reporting FormatCATEGORICAL:NONEDissolved Noble GasesEnvironmental TracersNumerical ModelVARIABLE:NONE

Thiros, N. E., Siirila-Woodburn, E. R., Dennedy-Frank, P. J., Williams, K. H., & Gardner, W. P. (2023). Constraining bedrock groundwater residence times in a mountain system with environmental tracer observations and Bayesian uncertainty quantification. Water Resources Research, 59, e2022WR033282. https://doi.org/10.1029/2022WR033282Velliquette, T., Welch, J., Crow, M., Devarakonda, R., Heinz, S., Crystal-Ornelas, R. (2021). ESS-DIVE Reporting Format for File-level Metadata. Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE), ESS-DIVE Repository. https://doi.org/10.15485/1734840Additional metadata on specific locations within the watershed are provided in the following related data package:Varadharajan C ; Kakalia Z ; Burrus M ; O'Ryan D ; Alper E ; Banfield J ; Berkelhammer M ; Beutler C ; Brodie E ; Brown W ; Carbone M S ; Carroll R ; Christianson D ; Chou C ; Crystal-Ornelas R ; Chadwick K D ; Christensen J ; Dafflon B ; Elbashandy H ; Enquist B J ; Fox P ; Gochis D ; Henderson M ; Johnson D ; Kueppers L ; Matheus Carnevali P ; Newman A ; Powell T ; Singha K ; Sorensen P ; Sprenger M ; Tokunaga T ; Versteeg R ; Wilkins M ; Williams K ; Worsham M ; Wong C ; Wu Y ; Agarwal D (2022): Location Identifiers, Metadata, and Map for Field Measurements at the East River Watershed, Colorado, USA (Version 3.0). Watershed Function SFA, ESS-DIVE repository. Dataset. doi:10.15485/1660962

This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The East River (ER) is a snow‐dominated, headwater basin of the Upper Colorado River Basin (UCRB) located in the western United States. The ER is the designated testbed of Lawrence Berkeley National Laboratory's Watershed Function Scientific Focus Area (WFSFA). Through WFSFA, observational networks have been established to measure stream discharge and precipitation chemistry. The ER is considered representative of many snow‐dominated headwaters of the Rocky Mountains. The study domain encompasses nearly 85 square km, a 1.4‐km vertical drop in elevation (4,120 to 2,760 m) and pristine alpine, subalpine, montane, and riparian ecosystems. The ER contains high‐energy mountain streams to low‐energy meandering floodplains and is eroding primarily into the Cretaceous, carbon‐rich, marine shale of the Mancos Formation. Additional metadata on specific locations within the watershed are provided in the following related data package: Varadharajan C. et al. (2022) doi:10.15485/1660962 -107.05-106.8839.03438.88 2021-05-092021-05-12 NicholasThirosnicholas.thiros@umontana.edu https://orcid.org/0000-0002-1704-1031 NicholasThirosnthiros@lbl.gov Watershed Function SFA Detailed descriptions of the environmental tracer collection and interpretation techniques can be found in the associated manuscript:Thiros, N. E., Siirila-Woodburn, E. R., Dennedy-Frank, P. J., Williams, K. H., & Gardner, W. P. (2023). Constraining bedrock groundwater residence times in a mountain system with environmental tracer observations and Bayesian uncertainty quantification. Water Resources Research, 59, e2022WR033282. https://doi.org/10.1029/2022WR033282Environmental tracers (CFC, SF6, 3H, and dissolved noble gases) were collected in May, 2021 from groundwater wells PLM1, PLM6, and PLM7. Prior to sample collection, the wells were purged for approximately 3 well volumes and until water field parameters (temperature, pH, specific conductivity, and dissolved oxygen) stabilized. CFCs were collected in 250 mL glass bottles with foil-lined caps and no head-space. SF6 was collected in 1000 mL bottles with no head-space. 3H was collected in 500 mL plastic bottles with a head-space. Noble gases were collected in copper tubes following procedures outlined at https://noblegaslab.utah.edu. Environmental tracer analysis was performed at the University of Utah Noble Gas Lab (https://noblegaslab.utah.edu). CFC and SF6 were analyzed using gas-chromatography. Noble gases and tritium were analyzed with mass-spectrometry. In particular, tritium was analyzed using the helium in-growth method. All environmental tracers were reported as aqueous concentrations or mass-fractions relative to atmospheric mixing ratios.. Interpreting the aqueous tracer observations to estimates of mean groundwater residence times was performed using lumped parameter models. Input timeseries of the tracers were constructed using published datasets for the Northern Hemisphere. We extend the lumped parameter model inverse problem to consider parametric uncertainties using Bayesian Markov-chain Monte Carlo techniques. We estimate groundwater recharge elevations, temperatures, and excess-air conditions using measurements of the dissolved noble gases. Eoin Brodie Lawrence Berkeley National Lab elbrodie@lbl.gov Principal Investigator dd.csv text/csv flmd.csv text/csv NobleGas_RTD_MCMC.zip application/zip