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

摘要

The complex interactions of runoff generation processes underlying thehydrological response of streams remain not entirely understood at thecatchment scale. Extensive research has demonstrated the utility of tracersfor both inferring flow path distributions and constraining modelparameterizations. While useful, the common use of linearity assumptions,i.e. time invariance and complete mixing, in these studies provides onlypartial understanding of actual process dynamics. Here we use long-term(<20 yr) precipitation, flow and tracer (chloride) data of threecontrasting upland catchments in the Scottish Highlands to inform integratedconceptual models investigating different mixing assumptions. Using themodels as diagnostic tools in a functional comparison, water and tracerfluxes were then tracked with the objective of exploring the differencesbetween different water age distributions, such as flux and resident waterage distributions, and characterizing the contrasting water age pattern ofthe dominant hydrological processes in the three study catchments toestablish an improved understanding of the wetness-dependent temporaldynamics of these distributions.The results highlight the potential importance of partial mixing processeswhich can be dependent on the hydrological functioning of a catchment.Further, tracking tracer fluxes showed that the various components of amodel can be characterized by fundamentally different water agedistributions which may be highly sensitive to catchment wetness history,available storage, mixing mechanisms, flow path connectivity and therelative importance of the different hydrological processes involved. Fluxtracking also revealed that, although negligible for simulating the runoffresponse, the omission of processes such as interception evaporation canresult in considerably biased water age distributions. Finally, the modelingindicated that water age distributions in the three study catchments do havelong, power-law tails, which are generated by the interplay of flow pathconnectivity, the relative importance of different flow paths as well as bythe mixing mechanisms involved. In general this study highlights thepotential of customized integrated conceptual models, based on multiplemixing assumptions, to infer system internal transport dynamics and theirsensitivity to catchment wetness states.