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Dryad

Isogeochemical characterization of mountain system recharge processes in the Sierra Nevada, California

Cite this dataset

Armengol, Sandra et al. (2024). Isogeochemical characterization of mountain system recharge processes in the Sierra Nevada, California [Dataset]. Dryad. https://doi.org/10.5061/dryad.0cfxpnw9t

Abstract

Mountain System Recharge processes are significant natural recharge pathways in many arid and semi-arid mountainous regions. However, Mountain System Recharge processes are often poorly understood and characterized in hydrologic models. Mountains are the primary water supply source to valley aquifers via lateral groundwater flow from the mountain block (Mountain Block Recharge) and focused recharge from mountain streams contributing to focused Mountain Front Recharge at the piedmont zone. Here, we present a multi-tool isogeochemical approach to characterize mountain flow paths and Mountain System Recharge in the northern Tulare Basin, California. We used groundwater chemistry data to delineate hydrochemical facies and explain the chemical evolution of groundwater from the Sierra Nevada to the Central Valley aquifer. Stable isotopes and radiogenic groundwater tracers validated Mountain System Recharge processes by differentiating focused from diffuse recharge, and estimating apparent groundwater age, respectively. Novel application of End-Member Mixing Analysis (EMMA) using conservative chemical components revealed three Mountain System Recharge end-members: (1) evaporated Ca-HCO3 water type associated with focused Mountain Front Recharge, (2) non-evaporated Ca-HCO3 and Na-HCO3 water types with short residence times associated with shallow Mountain Block Recharge, and (3) Na-HCO3 groundwater type with long residence time associated with deep Mountain Block Recharge. We quantified the contribution of each Mountain System Recharge process to the valley aquifer by calculating mixing ratios. Our results show that deep Mountain Block Recharge is a significant recharge component, representing 31 to 53 % of the valley groundwater. Greater hydraulic connectivity between the Sierra Nevada and Central Valley has significant implications for parameterizing groundwater flow models. Our framework is useful for understanding Mountain System Recharge processes in other snow-dominated mountain watersheds.

README

This README.txt file was generated on 2024-06-03 by Hoori Ajami

GENERAL INFORMATION

  1. Title of Dataset: Isogeochemical Characterization of Mountain System Recharge Processes in the Sierra Nevada, California
  2. Author Information

A. Researcher Contact Information
Name: Sandra Armengol Vall
Institution: Universidy of California at Riverside
Address: Department of Environmental Sciences, University of California, Riverside, CA 92521, USA
Email: sandra.armengol.vall@gmail.com

B. Principal Investigator Contact Information
Name: Hoori Ajami
Institution: Universidy of California at Riverside
Address: Department of Environmental Sciences, University of California, Riverside, CA 92521, USA
Email: hooria@ucr.edu
3. Date of data collection: 2020-05-01 - 2023-06-01
4. Geographic location of data collection: Northern Tulare Basin, California, USA
5. Information about funding sources that supported the collection of the data: National Science Foundation, Award: 1944161

SHARING/ACCESS INFORMATION

  1. Licenses/restrictions placed on the data: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication license.
  2. Recommended citation for this dataset: Armengol Vall, Sandra; Ajami, Hoori; Acero Triana, Juan S.; O'Sickman, James; Ortega, Lucia (2024), [Model Outputs] Isogeochemical Characterization of Mountain System Recharge Processes in the Sierra Nevada, California, Dryad, Dataset, https://doi.org/10.5061/dryad.0cfxpnw9t

METHODOLOGICAL INFORMATION

  1. Description of methods used for collection/generation of data: Water Resources Research paper
  2. Methods for processing the data: Water Resources Research paper
  3. Instrument- or software-specific information needed to interpret the data: Excel, text editor, The EMMA and MIX code is open source and available on https://idaea.csic.es/software/mix/

DATA-SPECIFIC INFORMATION

1.     Tables.zip  A Zipped folder. Contains eight Excel files as follows:

1.1    Table S1.xlsx Excel File  Table S1. Noble gases, tritium, X2, and 3H-3He apparent ages for the Valley Aquifer wells calculated from the US Geological Survey (GAMA) Program dataset (Bennett et al., 2017). 3H-3He apparent age was computed in iNovel using a closed system equilibration model (Aeschbach-Hertig et al., 2000; Jung et al., 2013). Nobel gas concentration is in cm3STP/g, tritium is in TU, and 3H-3He apparent age is in years. 3H/4H corresponds to uncorrected value. NA = no data, LE = large error, X2>1 and NT = no tritium, TU<0.5.

1.2.   Table S2.xlsx Excel File Table S2. Isotope carbon ranges of C-sources used in the uncertainty analysis.

1.3    Table S3.xlsx Excel File Table S3. Well location and carbon isotope composition of groundwater samples with δ13C close to the soil (-23‰) from the 2008 GAMA database in the Mountain Aquifer Range Aquifer of the northern Tulare Basin. NA=no reported data.

1.4   Table S4.xlsx Excel File Table S4. Amount of dissolved C attributed to recharge water (Crecharge), calcite dissolution (Ccalcite), reduction of SO4 (C SO4) and methanogenesis (C CH4) and measured Ca, SO4 and Ct in groundwater. Units are mmol/L.

1.5.  Table S5.xlsx Excel File Table S5. Measured 14C values (pmC), carbon percentages for each process, determination of the initial 14C activity, and 14C apparent age (years before 1950). The 14C non-corrected age was obtained using 14Cmeasured as A0.

1.6.  Table S6.xlsx Excel File Table S6. Total CEC and composition of the exchange complex of 11 sediment samples from the Tokopah Watershed and 20 sediment samples from the Pear Watershed in Sierra Nevada (in meq/100g soil).

1.7.   Table S7.xlsx Excel File Table S7. Measured chemical composition and calculated ion imbalance and mineral saturation indices of northern Tulare Basin groundwater samples from the US Geological Survey (GAMA) Program (Bennett 287 et al., 2017). NA= no reported data, * = reported value below the analytical detection limit (4 µg L-1).

1.8.   Table S8.xlsx Excel File Table S8. Mixing ratios, along with the averages and standard deviations of 5 MIX runs with the smallest differences between the measured and estimated values using end-members from Model F.

2.      2A.prn MIX Input file  Input file for EMMA model 2a to generate Figure 10 and perform MIX analysis
3.      B.prn MIX Input file    Input file for EMMA model B to perform MIX analysis
4.      C.prn MIX Input file    Input file for EMMA model C to perform MIX analysis
5.      D.prn MIX Input file   Input file for EMMA model D to perform MIX analysis
6.      E.prn MIX Input file    Input file for EMMA model E to perform MIX analysis
7.      F.prn MIX Input file    Input file for EMMA model F to perform MIX analysis

Methods

We used hydrochemical and isotope data from the US Geological Survey Groundwater Ambient Monitoring and Assessment (GAMA) program (Bennett et al., 2017) and processed these data for End-Member Mixing Analysis (EMMA) and mixing ratio calculations using MIX program.

Funding

National Science Foundation, Award: 1944161, Hydrologic Sciences

United States Department of Agriculture, Award: CA-R-ENS-5146-RR