Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water‐Tagging Enabled Hydrologic Models
- Oregon State Univ., Corvallis, OR (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Oregon State Univ., Corvallis, OR (United States)
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- NSF National Center for Atmospheric Research, Boulder, CO (United States)
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, $$\overline{T_{V}}$$, 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 $$\overline{T_{V}}$$ 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 $$\overline{T_{V}}$$ 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.
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Grant/Contract Number:
- AC05-76RL01830
- OSTI ID:
- 3000212
- Report Number(s):
- PNNL-SA--204994
- Journal Information:
- Journal of Advances in Modeling Earth Systems, Journal Name: Journal of Advances in Modeling Earth Systems Journal Issue: 10 Vol. 17; ISSN 1942-2466
- Publisher:
- American Geophysical Union (AGU)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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