Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water-Tagging Enabled Hydrologic Models
Butler, Z., Good, S., Hu, H., Chen, X., Dugger, A. L.. (2025). Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water-Tagging Enabled Hydrologic Models. Journal of Advances in Modeling Earth Systems, doi:https://doi.org/10.1029/2024ms004765
| Title | Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water-Tagging Enabled Hydrologic Models |
|---|---|
| Genre | Article |
| Author(s) | Z. Butler, S. Good, H. Hu, X. Chen, Aubrey L. Dugger |
| 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 7 years were applied at six National Ecological Observatory Network sites to calculate TTDs and derive mean virtual tracer age, (Formula presented.), fractions of young water, Fyw, and hydrologic tracer concentrations (water isotopes δ18O and δ2H) 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, Ftag, increased each year, with the final year's Ftag ranging from 66% to 100% and highlights the need to apply SPIT over many years to understand TTDs. When the Ftag was >75%, simulated (Formula presented.) ranged 179–923 days and Fyw 0.6%–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 (Formula presented.) and Fyw (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. |
| Publication Title | Journal of Advances in Modeling Earth Systems |
| Publication Date | Oct 1, 2025 |
| Publisher's Version of Record | https://doi.org/10.1029/2024ms004765 |
| OpenSky Citable URL | https://n2t.net/ark:/85065/d7xs60wc |
| OpenSky Listing | View on OpenSky |
| RAL Affiliations | HAP |