RESEARCH ARTICLE
Spatiotemporal dynamics of water sources in a mountain river basin inferred through δ2H and δ18O of water
Lillian M. McGill,
J. Renée Brooks,
E. Ashley Steel,
Corresponding Author
Lillian M. McGill
Quantitative Ecology and Resource Management, University of Washington, Seattle, Washington
Correspondence
Lillian M. McGill, Quantitative Ecology and Resource Management, University of Washington, Seattle, WA 98105, USA. Email: [email protected]
Search for more papers by this authorJ. Renée Brooks
Pacific Ecological Systems Division, National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Corvallis, Oregon
Search for more papers by this authorE. Ashley Steel
School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington
Search for more papers by this authorLillian M. McGill,
J. Renée Brooks,
E. Ashley Steel,
Corresponding Author
Lillian M. McGill
Quantitative Ecology and Resource Management, University of Washington, Seattle, Washington
Correspondence
Lillian M. McGill, Quantitative Ecology and Resource Management, University of Washington, Seattle, WA 98105, USA. Email: [email protected]
Search for more papers by this authorJ. Renée Brooks
Pacific Ecological Systems Division, National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Corvallis, Oregon
Search for more papers by this authorE. Ashley Steel
School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington
Search for more papers by this authorFunding information Department of the Interior Northwest Climate Adaptation Science Center graduate fellowship; National Science Foundation Graduate Research Fellowship, Grant/Award Number: DGE-1762114
Abstract
In mountainous river basins of the Pacific Northwest, climate models predict that winter warming will result in increased precipitation falling as rain and decreased snowpack. A detailed understanding of the spatial and temporal dynamics of water sources across river networks will help illuminate climate change impacts on river flow regimes. Because the stable isotopic composition of precipitation varies geographically, variation in surface water isotope ratios indicates the volume-weighted integration of upstream source water. We measured the stable isotope ratios of surface water samples collected in the Snoqualmie River basin in western Washington over June and September 2017 and the 2018 water year. We used ordinary least squares regression and geostatistical Spatial Stream Network models to relate surface water isotope ratios to mean watershed elevation (MWE) across seasons. Geologic and discharge data was integrated with water isotopes to create a conceptual model of streamflow generation for the Snoqualmie River. We found that surface water stable isotope ratios were lowest in the spring and highest in the dry, Mediterranean summer, but related strongly to MWE throughout the year. Low isotope ratios in spring reflect the input of snowmelt into high elevation tributaries. High summer isotope ratios suggest that groundwater is sourced from low elevation areas and recharged by winter precipitation. Overall, our results suggest that baseflow in the Snoqualmie River may be relatively resilient to predicted warming and subsequent changes to snowpack in the Pacific Northwest.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are openly available in the EPA ScienceHub at http://doi.org/10.23719/1520140.
Supporting Information
| Filename | Description |
|---|---|
| hyp14063-sup-0001-SupInfo.docxWord 2007 document , 12 MB | Figure S1. The relationship between δ18O and δ2H for all water samples, identified by season. The solid line is the global meteoric water line (GMWL, δ2H = δ18O * 8 + 10). Eight seasonal samples and six biweekly samples were removed from analyses due to d-excess values less than 5. Figure S2. Detailed lithology of the Snoqualmie River basin. Figure S3. A comparison of the 2018 water year monthly average temperature, precipitation, and SWE at SNOTEL site 908, and monthly average discharge from USGS gage 12149000, to monthly averages of these climate metrics from the previous 30 years (1988–2018). For most climate metrics, the WY 2018 values fall within the interquartile range, and for all climate metrics and all months the WY 2018 values fall within the historical range. The most anomalous months were February and April, which were wetter than average with subsequently higher discharge. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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