Modelling river constituent budgets in the Burnett Mary region, Queensland, Australia: An example of how it could be used in prioritising management actions

Abstract

To improve the declining water quality entering the Great Barrier Reef (GBR), the Australian and Queensland governments are funding changes to on-ground management practices through the Reef Plan Program. Reef Plan 2013, outlines specific water quality targets to address the decline in water quality entering the GBR. For example, it has set a target of 20% reduction in fine sediment export by 2018. An integrated water quality monitoring and modelling program has been established to measure and report on progress in meeting the water quality targets. Current prioritisation of on-ground management actions are based on previous modelling outputs, local knowledge and perception of areas and industries that are likely to generate disproportionately high amounts of constituents. The current Catchment modelling approach will enable more effective prioritisation to catchment areas and pollutant generation processes. This paper reports the results of the recent modelling of constituent budgets using the Source Catchments model outputs including identification of sources of supply to the river system, sinks and contributions to export to the GBR from catchments in the Burnett Mary region, and discusses how this information can be used in prioritizing on-ground management actions. This paper also highlights how examination of modelled constituent budgets can be used to (1) identify parts of the model that may be improved and (2) provide insight into the selection of water quality monitoring sites for model calibration and validation. Of the total modelled suspended sediment (TSS) supplied to the stream network, only 37% (438 kt) is exported, 46% (541 kt/y) is trapped in reservoirs (estimated by an algorithm used commonly elsewhere but modified to simulate daily sediment trapping in the Burdekin Falls Dam), 17% (198 kt/y) is lost as the result of water extraction while floodplain deposition and residual storage accounted for only 1%. The model estimates that streambank erosion, hillslope erosion and gully erosion contribute 56, 28, and 6% of the TSS exported to the GBR lagoon; with each respective erosion process supplying 29, 27, and 3% of particulate nitrogen (PN), and 28, 33, and 3%, of particulate phosphorus (PP). Particulate Nitrogen and Phosphorus budgets were similar to the TSS percent exported compared to the total amount generated. On the other hand, the model estimates that higher percentages of dissolved nutrients and Photosystem II inhibiting herbicides (PSII) that are supplied to the stream network (i.e., 68% dissolved inorganic nitrogen (DIN), 67% dissolved organic nitrogen (DON), 67% dissolved organic phosphorus (DOP) and 65% dissolved inorganic phosphorus (DIP) and 67% PSII inhibitor herbicides) are exported to the GBR lagoon. Having the functionality in the model to identify the specific pollutant sources and generation processes that contribute comparatively high constituent export to the GBR lagoon, will help to maximise progress towards water quality targets. For example, model results show that streambank erosion in the Mary catchment is identified to be contributing the highest proportion of TSS of all GBR catchments. Therefore, streambank erosion reduction through riparian revegetation and fencing off to restrict stock access may be considered to be management actions of priority in this catchment. In summary, the GBR Source Catchments modelling framework has now been developed with a range of enhancements not available in previous modelling programs. The development of the dynamic SedNet Source modelling functionality provides regional NRM groups with valuable information for prioritisation of on-ground management investment.