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Shifts in rain-snow partitioning drive faster water transit times in the US Pacific Northwest
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  • Published: 01 April 2026

Shifts in rain-snow partitioning drive faster water transit times in the US Pacific Northwest

  • Zachariah Butler1,2,
  • Stephen P. Good1,3,
  • Huancui Hu4,
  • Xingyuan Chen4,
  • Mark S. Raleigh1,5,
  • Catalina Segura1,6 &
  • …
  • Aubrey Dugger7 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Climate sciences
  • Environmental sciences
  • Hydrology
  • Water resources

Abstract

Water transit times strongly influence water quality, temperature, and seasonal hydrologic response of river systems. How water transit times may shift under future climates remains unconstrained, especially in mountainous regions experiencing rapid snowpack declines. Here, we estimated historical (2006–2013) and future (2086–2093) water transit times in five headwater catchments within the U.S. Pacific Northwest using sequential precipitation input tagging within the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model. Our results indicate water transit times are 18% (35–64 days) faster on average under the Representative Carbon Pathways (RCP) 8.5 climate scenario due to shifts in rain-snow partitioning, with higher fractions of younger water in the wet season and older water in the dry season. These results suggest shifts in rain-snow partitioning in snowmelt dominated catchments of the Pacific Northwest will shorten water transit times leading to likely impacts on regional water quality, temperature, and hydrologic seasonality.

Data availability

All of the codes used for the study are published on the River Corridor and Watershed Biogeochemistry SFA, ESS-DIVE repository accessed via https://data.ess-dive.lbl.gov/view/doi:10.15485/2562910. This includes txt and c-shell files used for modeling set-up in the SPIT framework, Jupyter Notebooks used for downloading and managing model outputs, observed $delta$ Q data, and python codes used to manage data as well as create the figures in this manuscript. SnowCloudMetrics is available at https://www.snowcloudmetrics.app/ with code available at https://github.com/SnowCloudMetrics. There are no guidelines and legislation needed to conduct this research in Naches River Basin, nor was any permission needed and acquired.

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Acknowledgements

This research was supported by the U.S. Department of Energy (DOE), Office of Science Biological and Environmental Research (BER) program, as part of BER’s Environmental System Science program. This contribution originates from the River Corridor Scientific Focus Area (SFA) at Pacific Northwest National Laboratory (PNNL). PNNL is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. DOE or the U.S. Government. Special thanks to the distinguished graduate research fellowship between PNNL and Oregon State University for providing support through the PNNL River Corridor SFA. We thank the reviewers for their helpful comments and suggestions that allowed this paper to be published.

Author information

Authors and Affiliations

  1. Water Resources Graduate Program, Oregon State University, Corvallis, OR, USA

    Zachariah Butler, Stephen P. Good, Mark S. Raleigh & Catalina Segura

  2. School of Civil and Construction Engineering, Oregon State University, Corvallis, OR, USA

    Zachariah Butler

  3. Department of Biological and Ecological Engineering, Oregon State University, Corvallis, OR, USA

    Stephen P. Good

  4. Atmospheric, Climate, and Earth Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA

    Huancui Hu & Xingyuan Chen

  5. College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, USA

    Mark S. Raleigh

  6. Forest Engineering, Resources and Management, Oregon State University, Corvallis, OR, USA

    Catalina Segura

  7. National Center for Atmospheric Research, Boulder, CO, USA

    Aubrey Dugger

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  1. Zachariah Butler
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  2. Stephen P. Good
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Contributions

Z Butler developed the methods, wrote the manuscript, and prepared the figures. S Good developed the research formation and reviewed the manuscript. H Huancui develop the model and reviewed the manuscript. X Chen reviewed the manuscript. M Raleigh prepared SI Figure 2 and reviewed the manuscript. C Segura reviewed the manuscript. A Dugger contributed to model development and reviewed the manuscript.

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Correspondence to Zachariah Butler.

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Butler, Z., Good, S.P., Hu, H. et al. Shifts in rain-snow partitioning drive faster water transit times in the US Pacific Northwest. Sci Rep (2026). https://doi.org/10.1038/s41598-026-46539-1

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  • Received: 03 November 2025

  • Accepted: 26 March 2026

  • Published: 01 April 2026

  • DOI: https://doi.org/10.1038/s41598-026-46539-1

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