Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models

Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 25 September 2025 V1 Latest version Share on Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models Authors : Zachariah Butler 0009-0007-0883-7103 [email protected] , Stephen Good , Huancui Hu , Xingyuan Chen , and Aubrey Dugger Authors Info & Affiliations https://doi.org/10.22541/au.175883065.54032160/v1 Published Journal of Advances in Modeling Earth Systems Version of record Peer review timeline 113 views 97 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Determining the age distribution of water exiting a catchment is important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages, yet forward modeling of individual events may not systematically capture the full transit time distribution (TTD). Here, we present a ‘sequential precipitation input tagging’ (SPIT) framework to tag all input precipitation at regular intervals during extended model simulations. Monthly tags over seven years were applied at six National Ecological Observatory Network sites to calculate TTDs and derive mean virtual tracer age, fractions of young water, F yw , and hydrologic tracer concentrations (water isotopes \(\delta\) 18 O and \(\delta\) 2 H) within a tagging enabled version of the Weather Research and Forecast hydrologic model (WRF-Hydro). Throughout seven simulation years, the fraction of simulated discharge derived from tagged events, F tag , increased each year, with the final year’s F tag ranging from 66% to 100% and highlights the need to apply SPIT over many years to understand TTDs. When the F tag was >75%, simulated ranged 179 days to 923 days and F yw 0.6% to 23.9%, with daily values exhibiting a power-law relationship with precipitation, discharge, and groundwater. Through implementation of SPIT, we find this hydrologic model configuration performs poorly in estimation of and F yw (root mean squared error of 469 days and 14.4% respectively), suggesting it misrepresents subsurface mixing. Thus, the SPIT framework provides a reproducible approach to calculate watershed transit times within tagging enabled models and thereby assess and improve representation of hydrologic processes.  A novel framework is developed to sequentially tag input precipitation and estimate water transit times and hydrologic tracers  Framework is used in a hydrologic model and compared with observed stable water isotope data to assess correlations to model characteristics  A substantial time (2-7+ years) needs to be tagged before tagged water significantly contributes to total discharge at six study sites Supplementary Material File (2024ms004765rr_merged_pdf.pdf) Download 8.66 MB Information & Authors Information Version history V1 Version 1 25 September 2025 Peer review timeline Published Journal of Advances in Modeling Earth Systems Version of Record 16 Oct 2025 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords headwater watershed hydrologic modeling national water model (nwm)/wrf-hydro stable water isotopes water transit times Authors Affiliations Zachariah Butler 0009-0007-0883-7103 [email protected] Water Resources Graduate Program, Oregon State University Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory 4 National Science Foundation National Center for Atmospheric Research View all articles by this author Stephen Good Water Resources Graduate Program, Oregon State University View all articles by this author Huancui Hu Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory 4 National Science Foundation National Center for Atmospheric Research View all articles by this author Xingyuan Chen Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory 4 National Science Foundation National Center for Atmospheric Research View all articles by this author Aubrey Dugger View all articles by this author Metrics & Citations Metrics Article Usage 113 views 97 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Zachariah Butler, Stephen Good, Huancui Hu, et al. Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models. Authorea . 25 September 2025. DOI: https://doi.org/10.22541/au.175883065.54032160/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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