Integrating High-Resolution Tracer Data with Soil Moisture and Precipitation Dynamics to Characterize Streamflow Age Distribution in a Headwater Catchment

The partitioning of rainfall into different hydrological components, such as lateral subsurface flow,  overland flow, and soil water storage, is essential for understanding and predicting streamflow responses and contaminant transport. This study investigates flow processes within shallow sub-surface layers and streamflow responses in an agricultural headwater catchment by utilizing high-resolution data of oxygen (δ¹⁸O) and hydrogen (δ²H) stable isotopes of water. We used weekly data from grab and event streamflow samples (ranging from 15 minutes to 2 hours based on the anticipated event length) in a tracer-based transport model to estimate water travel times and examine how catchment characteristics and climate factors influence storage water release and travel time distributions with a StorAge Selection function approach. We tested two conditions for the activation of preferential flow paths: i) based on soil moisture only, and ii) based on both soil moisture and precipitation intensity. The results show that calibrating a tracer-based transport model, coupled with soil moisture and precipitation intensity data, improve the tracer simulation of quick responses in stream flow (increase in Nash-Sutcliffe Efficiency from 0.21 to 0.51) and can greatly enhance the accuracy of streamflow age distribution estimates in headwater catchment compared to using soil moisture data only. Particularly in summer months with intense precipitation, the catchment shows dominant infiltration-excess overland flow processes resulting in young water to reach to the stream. The results also demonstrate that during wet conditions, a significant portion of event water bypasses through fast flow paths. These results highlight the importance of tracer data in understanding the interplay between catchment characteristics, rainfall intensity, and water storage release.