Investigating Mountain Watershed Headwater‐To‐Groundwater Connections, Water Sources, and Storage Selection Behavior With Dynamic‐Flux Particle Tracking.

Climate change will impact mountain watershed streamflow both directly—with changing precipitation amounts and variability—and indirectly—through temperature shifts altering snowpack, melt, and evapotranspiration. To understand how these complex processes will affect ecosystem functioning and water resources, we need tools to distinguish connections between water sources (rain/snowmelt), groundwater storage, and exit fluxes (streamflow/evapotranspiration), and to determine how these connections change seasonally and as climate shifts. Here, we develop novel watershed‐scale approaches to understand water source, storage, and exit flux connections using a dynamic‐flux particle tracking model (EcoSLIM) applied in California's Cosumnes Watershed, which connects the Sierra Nevada and Central Valley. This work develops new visualizations and applications to provide mechanistic understanding that underpins the interpretation of isotopic field data at watershed scales to distinguish sources, flow paths, residence times, and storage selection. In our simulations, streamflow comes primarily from snow‐derived water while evapotranspiration generally comes from rain. Most streamflow starts above 1,000 m while evapotranspiration is sourced relatively evenly across the watershed and is generally younger than streamflow. Modeled streamflow consists primarily of water sourced from precipitation in the previous 5 years but before the current water year, while ET consists primarily of water from precipitation in the current water year. ET, and to a lesser extent streamflow, are both younger than water in groundwater storage. However, snowmelt‐derived streamflow preferentially discharges older water from snow‐derived storage. Dynamic‐flux particle tracking and new approaches presented here enable novel model‐tracer comparisons in large‐scale watersheds to better understand watershed behavior in a changing climate. Plain Language Summary: Climate change will alter the hydrologic cycle: storms will be more intense and higher temperatures will result in less snow, earlier melt, and more early‐season water use by plants. To understand the combined effect of these changes, we need models to simulate water flows and precisely study the effects of rain, snowmelt, subsurface storage, streamflow, and plant water uptake. These models can show us how water flows between different components of the landscape, and how this flow changes seasonally and in response to climate change. This study develops new modeling tools that simulate the Cosumnes River in the Sierra Nevada (California, USA) and will help interpret field data at watershed scales. The majority of simulated streamflow originates from snow while plants rely on rainfall for evapotranspiration (ET). Most streamflow starts as precipitation above 1,000 m while ET comes from water that falls evenly across the watershed. Water used for ET is generally younger than streamflow: most streamflow is 1–5 years old, while most ET is less than 1 year old. Both ET and streamflow are younger than water stored in the subsurface. These new modeling tools, called dynamic‐flux particle tracking, will help us predict how watersheds will behave as climate changes. Key Points: Dynamic‐flux particle tracking (DFPT) is a novel technique to investigate watershed function and connectionWater source wedge plots illustrate connectivity between source water elevation, precipitation phase, and water exit pathways and locationDFPT shows how source phase and watershed conditions influence age‐ranked storage selection behavior [ABSTRACT FROM AUTHOR]