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.

Holistic approaches are needed to investigate the capacity of current water resource operations and infrastructure to sustain water supply and critical ecosystem health under projected drought conditions. Drought vulnerability is complex, dynamic, and challenging to assess, requiring simultaneous consideration of changing water demand, use and management, hydrologic system response, and water quality. We are bringing together a community of scientists from the U.S. Geological Survey, National Center for Atmospheric Research, Department of Energy, and Cornell University to create an integrated human-hydro-terrestrial modeling framework, linking pre-existing models, that can explore and synthesize system response and vulnerability to drought in the Delaware River Basin (DRB). The DRB provides drinking water to over 15 million people in New York, New Jersey, Pennsylvania, and Delaware. Critical water management decisions within the system are coordinated through the Delaware River Basin Commission and must meet requirements set by prior litigation. New York City has rights to divert water from the upper basin for water supply but must manage reservoir releases to meet downstream flow and temperature targets. The Office of the Delaware River Master administers provisions of the Flexible Flow Management Program designed to manage reservoir releases to meet water supply demands, habitat, and specified downstream minimum flows to repel upstream movement of saltwater in the estuary that threatens Philadelphia public water supply and other infrastructure. The DRB weathered a major drought in the 1960s, but water resource managers do not know if current operations and water demands can be sustained during a future drought of comparable magnitude. The integrated human-hydro-terrestrial modeling framework will be used to identify water supply and ecosystem vulnerabilities to drought and will characterize system function and evolution during and after periods of drought stress. Models will be forced with consistent input data sets representing scenarios of past, present, and future conditions. The approaches used to unify and harmonize diverse data sets and open-source models will provide a roadmap for the broader community to replicate and extend to other water resource issues and regions.