TRANSIT TIME DISTRIBUTIONS IN A CHANGING WORLD: NEW THEORY FOR UNDERSTANDING AND MODELING TRANSPORT IN DYNAMIC LANDSCAPES

While transit time distributions have been widely used to characterize and model transport through groundwater systems, their use in surface water hydrology has been limited by the difficulty of dealing with the time-variability that characterizes such systems. Recently a very general approach to modeling unsteady transport through an arbitrary control volume (such as a watershed) has emerged that accounts for temporal variability in the underlying transport dynamics. This framework encapsulates all the time varying controls on transport in a new type of probability distribution called a rank StorAge Selection (rSAS) function, which can be combined with the dynamic water balance of the system to yield the time-varying transit time distribution. Here I will the ability of the model to reveal insights into the flowpath dynamics of a small, humid watershed at Plynlimon, UK with a long-term record of rainfall and streamflow chloride. While a time-invariant gamma distribution for the rSAS function produced a good fit to data, the fit was significantly improved when the distribution was allowed to vary with catchment storage. However the variation was inverse to that of a `well-mixed' system where storage has a pure dilution effect. Discharge at high storage was predicted to contain a larger fraction of recent event water than at low storage. The effective volume of storage involved in transport was 3411 mm at mean catchment wetness, but declined by 71 millimeters per 1 mm of additional catchment storage, while the fraction of event water in discharge increased by 1.4%. This `inverse storage effect' is sufficient to reproduce the observed long-memory 1/f fractal spectral structure of stream chloride. Metrics quantifying the strength and direction of storage effects are proposed as useful signatures, and point toward a unified framework for observing and modeling coupled watershed flow and transport.