Modelled estimates of dissolved inorganic nitrogen exported to the Great Barrier Reef lagoon.

Measuring stream pollutant loads across the Great Barrier Reef (GBR) catchment area (GBRCA) is challenging due to the spatial extent, climate variability, changing land use and evolving land management practices, and cost. Thus, models are used to estimate baseline pollutant loads. The eWater Source modelling framework is coupled with agricultural paddock scale models and the GBR Dynamic SedNet plugin to simulate dissolved inorganic nitrogen (DIN) generation and transport processes across the GBRCA. Catchment scale monitoring of flow and loads are used to calibrate the models, and performance is assessed qualitatively and quantitatively. Modelling indicates almost half (47%) of the total modelled DIN load exported to the GBR lagoon is from the Wet Tropics, and almost half of the total modelled DIN load is from sugarcane areas. We demonstrate that using locally developed, customised models coupled with a complementary monitoring program can produce reliable estimates of pollutant loads.

Modelled estimates of fine sediment and particulate nutrients delivered from the Great Barrier Reef catchments.

The eWater Source modelling framework has been modified to support the Great Barrier Reef (GBR) Dynamic SedNet catchment modelling concept, which is used to simulate fine sediment and particulate nutrient generation, loss, and transport processes across GBR catchments. Catchment scale monitored data sets are used to calibrate and evaluate models. Model performance is assessed qualitatively and quantitatively. Modelling predicts that approximately half of generated sediment is delivered to the GBR lagoon; the remainder is deposited on floodplains, trapped in reservoirs or lost through other minor processes (e.g. irrigation extractions). Gullies are the major source of sediment, with comparable contributions from hillslopes and streambanks. Hillslope sources are considered the major source of particulate nutrients across the GBR catchments. We demonstrate that using locally developed, customised models coupled with a complementary monitoring program can produce credible modelled estimates of pollutant loads and provide a platform for testing catchment scale assumptions and scenarios.