What can flux tracking teach us about water age distribution patterns and their temporal dynamics

The complex interactions of runoff generation processes underlying the hydrological response of streams remain incompletely understood at the catchment scale. Extensive research has demonstrated the utility of tracers for both inferring flow paths distributions and constraining model parameterizations. While useful, the common use of linearity assumptions, i.e. time-invariance and complete mixing, in these studies provides only partial understanding of actual process dynamics. Here we use long term (< 20 yr) precipitation, flow and tracer (chloride) data of three contrasting upland catchments in the Scottish Highlands to inform integrated conceptual models investigating different mixing assumptions. Using the models as diagnostic tools in a functional comparison, water and tracer fluxes were tracked with the objective of characterizing water age distributions in the three catchments and establishing the wetness-dependent temporal dynamics of these distributions. The results highlight the potential importance of partial mixing which is dependent on the hydrological functioning of a catchment. Further, tracking tracer fluxes showed that the various components of a model can be characterized by fundamentally different water age distributions which may be highly sensitive to catchment wetness, available storage, mixing mechanisms, flow path connectivity and the relative importance of the different hydrological processes involved. Flux tracking also revealed that, although negligible for simulating the runoff response, the omission of processes such as interception evaporation can result in considerably biased water age distributions. Finally, the modeling indicated that water age distributions in the three study catchments do have long, power-law tails, which are generated by the interplay of flow path connectivity, the relative importance of different flow paths as well as by the mixing mechanisms involved. In general this study highlights the potential of customized integrated conceptual models, based on multiple mixing assumptions, to infer system internal transport dynamics and their sensitivity to catchment wetness states.