Utilising catchment modelling as a tool for monitoring Reef Rescue outcomes in the Great Barrier Reef catchment area

Water quality improvement plans (WQIPs) are currently being implemented within the Great Barrier Reef (GBR) catchment area through the Australian Government ‘Reef Rescue’ package to reduce the runoff of sediments, nutrients and pesticides into the GBR lagoon. End-of-catchment pollutant load targets have been set for a selection of priority GBR catchments to determine the effectiveness of catchment management actions over time. However, our ability to detect changes in water quality at the end-ofcatchment and to assess this against the set targets over short time frames (i.e. a few years) is limited. This is particularly so for large dry tropical catchments such as the Burdekin River, which has high inter and intra annual flow variability, and where considerable time lags exist before water quality improvement may occur at the end-of-catchment. Due to lag times in response to changed management practices and a noisy water quality signal associated with inter-annual flow variability, it would take greater than 10 years to detect reductions in pollutant loads which is outside the current targets of the Reef Rescue timeframe. In addition, the level of uncertainty in the calculation of pollutant loads can equal or exceed the proposed resource condition or pollutant load targets. Hence the only way to assess the effectiveness of management actions on water quality in the short term in such a system is to utilise modelling tools (e.g. SedNet or WaterCAST models), to predict material transport and delivery and management scenario forecasting. Receiving water models, such as ChloroSim are also required to relate these end-of-catchment pollutant loads to ecosystem response. Water quality guidelines (trigger values) for the Great Barrier Reef can be then used within these receiving water models to revise end-of-river targets. This paper provides an overview of challenges currently faced by natural resource managers and science providers tasked with measuring Reef Rescue outcomes in the GBR catchment and lagoon, and presents a coupled monitoring and modelling approach recently developed for the Burdekin, Black-Ross and Tully-Murray WQIPs. We note that this approach also has errors which may propagate through the scaling of monitoring and modelling data (e.g. paddock to sub-catchment scale, end-of-catchment to marine) and that other means, such as Bayesian Belief Networks may be required to reduce these additive errors. Our ‘upscaling’ approach from the paddock to the GBR lagoon provides a clear framework to assist in assessing the performance of water quality improvement in the GBR as a result of the Reef Rescue initiative