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Catchment modelling is used as one of multiple lines of evidence to report on progress towards Great Barrier Reef (GBR) Water Quality Protection Plan (Reef Plan) water quality targets. Progress is monitored via the Paddock to Reef (P2R) Integrated Monitoring, Modelling and Reporting Program. Within the P2R program, the Source modelling framework is used to construct GBR specific models (McCloskey 2017) and the overarching purpose of the modelling is to assess the impact of land management changes across the GBR against Reef Plan targets. To optimise predictive capability and thereby help facilitate better targeting, the modeller is faced with two common problems. Firstly, assessing the quality of model inputs and outputs and secondly, where possible, improving modelling performance. While observation datasets such as flow are often adequate, water quality data are scarcer, sporadically sampled, and frequently well downstream of their source. To further improve the water quality model validation data pool, the modelling team have attempted to tabulate all relevant datasets that can be used in model evaluation. However, utilising all available datasets to assess and improve performance can be an arduous task. As such, small catchment studies can initially be overlooked as a validation source in large “lumped” catchment scale modelling studies due to scale and the inherent spatial and temporal mismatch issues. As a small illustrative case study, we firstly designed a simple methodology to disaggregate the lumped modelled hillslope loads for a grazing landuse in a subcatchment. We then discuss the benefit of paddock scale research sites for informing the GBR Source modelling. In the GBR Source framework, spatially variable Revised Universal Soil Loss Equation (RUSLE) was used to generate the hillslope sediment loads for rangelands. Sediment loads are lumped and reported for a single landuse (typically1 km2 – 30km2) for a given sub-catchment at a daily timestep. However the modelled daily loads are initially generated at a finer scale, typically, 30m by 30m 900 m2. As the individual grid calculations are not recorded at model runtime, they needed to be recorded prior to aggregation in the model. This enabled evaluations between GBR Source modelled loads and the much smaller catchment study data to be made at appropriate scales. The disaggregation and assessment of modelled loads outlined in this paper facilitated small to large scale hillslope erosion comparisons. For the two case study sites, erosion and cover are shown to be well predicted at the average annual scale and areas for further improvement and investigation have been highlighted. We recommend further sites across the GBR be assessed. Validating disaggregated modelled data against plot scale experimental data, provides an alternative data set for validation previously not utilised. The approach shows a lot of potential to improve confidence in modelled sediment generation predictions.

Great Barrier Reef Source modelling: Assessing hillslope erosion modelling performance at paddock scale experimental sites