Modelling of Total Phosphorus and Nitrate Using a Travel Time Approach in the Duck River Catchment, Australia

Abstract

ABSTRACTTotal phosphorus (TP) and nitrate are important non‐conservative contaminants of streams. They vary strongly in response to climatic, hydrologic, and other drivers and are affected by different flow paths. Water residence and travel time distributions carrying information about sources of streamflow can potentially provide a basis for modelling nitrate and TP dynamics. In this study, we use a travel time model coupled with age—concentration relationships to simulate nitrate and TP concentrations in the Duck River catchment, NW Tasmania, Australia. A modified version of the Tran‐SAS model was used with time‐varying beta storage selection functions, calibrated against high‐frequency electrical conductivity (EC) observations. Concentrations of TP and nitrate were then modelled using the water TTDs coupled with age‐concentration relationships for TP and nitrate. This approach separated biogeochemical effects from water travel time and ensured consistent TTDs underpinning the transport of different nutrients. Two years (2008 and 2009 water years) of high‐frequency nutrient concentrations were used for model calibration and validation. It was initially hypothesised that the age‐concentration relationships for nitrate and TP could be temporally fixed, with the seasonal variation in residence time distribution capturing any seasonality in nutrient behaviour. The models performed moderately under this hypothesis; however, residual analysis clearly demonstrated seasonal declines in the concentrations of TP and nitrate during events across the high flow season. Simulations of TP and nitrate were markedly improved by using different source concentrations: one for the early high flow season and the other for the remainder of the year. Both Nash‐Sutcliffe Efficiency and the combined seasonal and event dynamics of nitrate and TP were markedly improved by using different source concentrations for these two different periods. This suggests that land management and biogeochemical processing are important influences on the temporal dynamics of nutrients in streams. The study informs future developments of TTD‐based water quality modelling and demonstrates the need to include temporally dynamic nutrient source concentrations for young water.