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Title: Baseflow Age Distributions and Depth of Active Groundwater Flow in a Snow‐Dominated Mountain Headwater Basin

Abstract

Abstract Deeper flows through bedrock in mountain watersheds could be important, but lack of data to characterize bedrock properties limits understanding. To address data scarcity, we combine a previously published integrated hydrologic model of a snow‐dominated, headwater basin of the Colorado River with a new method for dating baseflow age using dissolved gas tracers SF 6 , CFC‐113, N 2 , and Ar. The original flow model predicts the majority of groundwater flow through shallow alluvium (<8 m) sitting on top of less permeable bedrock. The water moves too quickly and is unable to reproduce observed SF 6 concentrations. To match gas data, bedrock permeability is increased to allow a larger fraction of deeper and older groundwater flow (median 112 m). The updated hydrologic model indicates interannual variability in baseflow age (3–12 years) is controlled by the volume of seasonal interflow and tightly coupled to snow accumulation and monsoon rain. Deeper groundwater flow remains stable (11.7 ± 0.7 years) as a function mean historical recharge to bedrock hydraulic conductivity (R/K). A sensitivity analysis suggests that increasing bedrock K effectively moves this alpine basin away from its original conceptualization of hyperlocalized groundwater flow (high R/K) with groundwater age insensitive to changes in water inputs. Instead, this basinmore » is situated close to the precipitation threshold defining recharge controlled groundwater flow conditions (low R/K) in which groundwater age increases with small reductions in precipitation. Work stresses the need to explore alternative methods characterizing bedrock properties in mountain basins to better quantify deeper groundwater flow and predict their hydrologic response to change.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]; ORCiD logo [5]
  1. Desert Research Institute Reno NV USA
  2. U.S. Geological Survey Denver CO USA
  3. U.S. Geological Survey Menlo Park CA USA
  4. Natural and Environmental Sciences (NES) Department Western Colorado University Gunnison CO USA
  5. Lawrence Berkeley National Laboratory Berkeley CA USA, Rocky Mountain Biological Laboratory Gothic CO USA
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER); USGS; National Science Foundation (NSF)
OSTI Identifier:
1735771
Alternate Identifier(s):
OSTI ID: 1760264; OSTI ID: 1786763
Grant/Contract Number:  
DE‐AC02‐05CH11231; AC02-05CH11231; G16AP00196; 1624073
Resource Type:
Published Article
Journal Name:
Water Resources Research
Additional Journal Information:
Journal Name: Water Resources Research Journal Volume: 56 Journal Issue: 12; Journal ID: ISSN 0043-1397
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; stream water age; mountains; gas tracers; baseflow; hydrologic model; particle tracking

Citation Formats

Carroll, Rosemary W. H., Manning, Andrew H., Niswonger, Richard, Marchetti, David, and Williams, Kenneth H. Baseflow Age Distributions and Depth of Active Groundwater Flow in a Snow‐Dominated Mountain Headwater Basin. United States: N. p., 2020. Web. doi:10.1029/2020WR028161.
Carroll, Rosemary W. H., Manning, Andrew H., Niswonger, Richard, Marchetti, David, & Williams, Kenneth H. Baseflow Age Distributions and Depth of Active Groundwater Flow in a Snow‐Dominated Mountain Headwater Basin. United States. https://doi.org/10.1029/2020WR028161
Carroll, Rosemary W. H., Manning, Andrew H., Niswonger, Richard, Marchetti, David, and Williams, Kenneth H. Mon . "Baseflow Age Distributions and Depth of Active Groundwater Flow in a Snow‐Dominated Mountain Headwater Basin". United States. https://doi.org/10.1029/2020WR028161.
@article{osti_1735771,
title = {Baseflow Age Distributions and Depth of Active Groundwater Flow in a Snow‐Dominated Mountain Headwater Basin},
author = {Carroll, Rosemary W. H. and Manning, Andrew H. and Niswonger, Richard and Marchetti, David and Williams, Kenneth H.},
abstractNote = {Abstract Deeper flows through bedrock in mountain watersheds could be important, but lack of data to characterize bedrock properties limits understanding. To address data scarcity, we combine a previously published integrated hydrologic model of a snow‐dominated, headwater basin of the Colorado River with a new method for dating baseflow age using dissolved gas tracers SF 6 , CFC‐113, N 2 , and Ar. The original flow model predicts the majority of groundwater flow through shallow alluvium (<8 m) sitting on top of less permeable bedrock. The water moves too quickly and is unable to reproduce observed SF 6 concentrations. To match gas data, bedrock permeability is increased to allow a larger fraction of deeper and older groundwater flow (median 112 m). The updated hydrologic model indicates interannual variability in baseflow age (3–12 years) is controlled by the volume of seasonal interflow and tightly coupled to snow accumulation and monsoon rain. Deeper groundwater flow remains stable (11.7 ± 0.7 years) as a function mean historical recharge to bedrock hydraulic conductivity (R/K). A sensitivity analysis suggests that increasing bedrock K effectively moves this alpine basin away from its original conceptualization of hyperlocalized groundwater flow (high R/K) with groundwater age insensitive to changes in water inputs. Instead, this basin is situated close to the precipitation threshold defining recharge controlled groundwater flow conditions (low R/K) in which groundwater age increases with small reductions in precipitation. Work stresses the need to explore alternative methods characterizing bedrock properties in mountain basins to better quantify deeper groundwater flow and predict their hydrologic response to change.},
doi = {10.1029/2020WR028161},
journal = {Water Resources Research},
number = 12,
volume = 56,
place = {United States},
year = {Mon Dec 14 00:00:00 EST 2020},
month = {Mon Dec 14 00:00:00 EST 2020}
}

Journal Article:
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https://doi.org/10.1029/2020WR028161

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