The Modeling of Time-Varying Stream Water Age Distributions: Preliminary Investigations with Non-Conservative Solutes

Abstract:

Modeling the dynamics of chemical transport from the landscape to streams is necessary for water quality management. Previous work has shown that estimates of the distribution of water age in streams, the transit time distribution (TTD), can improve prediction of the concentration of conservative tracers (i.e., ones that “follow the water”) based on upstream watershed inputs. A major challenge however has been accounting for climate and transport variability when estimating TDDs at the catchment scale. In this regard, Harman (2014, in review) proposed the Omega modeling framework capable of using watershed hydraulic fluxes to approximate the time-varying TTD. The approach was previously applied to the Plynlimon research watershed in Wales to simulate stream concentration dynamics of a conservative tracer (chloride) including 1/f attenuation of the power spectra density. In this study we explore the extent to which TTDs estimated by the Omega model vary with the concentration of non-conservative tracers (i.e., ones whose concentrations are also affected by transformations and interactions with other phases). First we test the hypothesis that the TTD calibrated in Plynlimon can explain a large part of the variation in non-conservative stream water constituents associated with storm flow (acidity, Al, DOC, Fe) and base flow (Ca, Si). While controlling for discharge, we show a correlation between the percentage of water of different ages and constituent concentration. Second, we test the hypothesis that TTDs help explain variation in stream nitrate concentration, which is of particular interest for pollution control but can be highly non-conservative. We compare simulation runs from Plynlimon and the agricultural Choptank watershed in Maryland, USA. Following a top-down approach, we estimate nitrate concentration as if it were a conservative tracer and examine the structure of residuals at different temporal resolutions. Finally, we consider model modifications to account for the effects of nitrogenous biogeochemical transformations.