The hydrologic community uses geochemical tracers to determine the age distribution of water exiting a catchment, with transit time distributions (TTDs) important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages. Here, we present a ‘sequential precipitation input tagging’ (SPIT) framework to tag all input precipitation events at regular intervals over an extended period (monthly tags over seven years). SPIT is applied at six National Ecological Observatory Network sites to calculate TTDs and derive from these mean transit times (MTT), fractions of young water (Fyw), and hydrologic tracer concentrations (δQ-δ18O and δ2H) within a water-tagging enabled version of the Weather Research and Forecast hydrologic model. Throughout seven simulation years, the fraction of simulated discharge derived from tagged events increased each year, with the final year’s tagged stream water fraction (TSWF) ranging 21% to 100%. When the TSWF was ≥75%, simulated MTTs range 190 days to 850 days and Fyw 1% to 24%, with a root mean squared error (RMSE) of 456 days and 14.5%. The RMSE for δ18O is 1.08‰ and δ2H 6.58‰. Low TSWF values early in the simulation period highlights the need to apply SPIT over many years to fully understand the TTD. At daily timescales, model MTT and Fyw exhibit a power-law relationship with precipitation, discharge, and groundwater. The successful implementation of SPIT within a tracer-enabled version of an operational hydrologic model allows for a reproducible approach to calculate water transit times and hydrologic tracers.