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Updated Methodology and Results for Report Card 2014 Modelling pollutant load changes due to improved management practices in the Great Barrier Reef catchments: updated methodology and results Technical Report for Reef Report Card 2014 Prepared by Contact Gillian McCloskey 07 42225447 David Waters 07 45291395 Ownership of intellectual property rights Unless otherwise noted, copyright (and any other intellectual property rights, if any) in this publication is owned by the State of Queensland. Creative Commons This material is licensed under a Creative Commons - Attribution 3.0 Australia licence. Creative Commons Attribution 3.0 Australia License is a standard form license agreement that allows you to copy, distribute, transmit and adapt this publication provided you attribute the work. A summary of the licence terms is available from www.creativecommons.org/licenses/by/3.0/au/deed.en.The full licence terms are available from www.creativecommons.org/licenses/by/3.0/au/legalcode. To reference this volume McCloskey, G., Waters, D., Baheerathan, R., Darr, S., Dougall, C., Ellis, R., Fentie, B., Hateley, L. 2017. Modelling pollutant load changes due to improved management practices in the Great Barrier Reef catchments: updated methodology and results – Technical Report for Reef Report Card 2014, Queensland Department of Natural Resources and Mines, Brisbane, Queensland. Disclaimer The information contained herein is subject to change without notice. The Queensland Government shall not be liable for technical or other errors or omissions contained herein. The reader/user accepts all risks and responsibility for losses, damages, costs and other consequences resulting directly or indirectly from using this information. Acknowledgments: This project is part of the Queensland and Australian Government’s Paddock to Reef program. The project is funded by the Queensland Department of Natural Resources and Mines ‘Queensland Regional Natural Resource Management Investment Program 2013–2018’ with support from the Department of Science, Information Technology, Innovation and the Arts (DSITIA). Technical support was provided by a number of organisations and individuals, including Environmental Monitoring and Assessment Science (DSITIA), Queensland Hydrology (DSITIA) and the Commonwealth Scientific and Industrial Research Organisation (CSIRO). We would also like to thank the reviewers for providing feedback on this report. Source Catchments modelling – Updated methodology and results Executive Summary Declining water quality from agricultural land uses, is one of the major pressures affecting the health and resilience of the Great Barrier Reef (GBR). In response to this, Reef Plan was established as a joint commitment by the Australian and Queensland governments, which sets targets for water quality improvement. The long term goal of Reef Plan is to ensure the quality of the water entering the GBR has no detrimental impact on the health and resilience of the Reef. To achieve the targets, improvements in land management are being driven by a combination of the Australian Government’s reef investments, along with Queensland Government and industry led initiatives in partnership with regional Natural Resource Management (NRM) groups. Annual progress made towards the targets is monitored through the Paddock to Reef Integrated Monitoring, Modelling and Reporting Program (P2R). Catchment modelling is one of multiple lines of evidence used to report on the progress being made towards the water quality targets. Other components of the program include: paddock scale monitoring and modelling of the effectiveness of land management practices, monitoring of the prevalence of improved practices over time, catchment loads monitoring, catchment indicators, and finally, marine monitoring. This report provides the most recent baseline load estimates and reports on progress towards Reef Plan targets for Report Card 2014 (RC2014) for all six GBR NRM regions, including modelled load reductions for sediment, nutrients, and pesticides resulting from the adoption of improved management practices. The report also provides an update on the methodology described in the 2013 catchment modelling technical reports. The eWater Ltd Source Catchments water quantity and quality modelling framework is used to simulate how catchment and climate variables affect runoff and constituent transport by integrating a range of component models, data and knowledge. Major updates to the six GBR Source Catchment models occur on a five year cycle to align with the Reef Plan funding cycle. Major updates have occurred to the models as part of the RC2014 Source Catchments modelling. The next major update will occur in 2018. The RC2014 updates include eWater upgrades to the Source platform, upgrades to the GBR component models developed and maintained by the Queensland Government, and updates to input data sets. These updates include recalibration of the hydrology using an alternative rainfall runoff model, an extended model run period, changes to the algorithm used on the remote sensing ground cover imagery, updates to paddock model simulations, significant changes to the management practice adoption framework, and numerous minor changes that are discussed in the body of this report. The model run period was extended by five years and now runs from 1986–2014. The extended run period allows the models to be validated against an additional five years of monitoring data. An improved hydrological calibration performance was achieved using the Sacramento Rainfall-Runoff model in comparison to the previously used SimHyd Rainfall-Runoff model. This is especially the case for calibrating high flows, which was identified as the component of the previous calibration needing to 3 Source Catchments modelling – Updated methodology and results be improved. Furthermore, the Sacramento model is used by the Queensland Government in water planning models, thus allowing calibration tools to be developed in partnership. There were three significant changes to the ground cover inputs used in the calculation of hillslope erosion. Firstly, estimates of ground cover levels under trees have been developed, which were previously unavailable. Secondly, the temporal resolution of ground cover data has increased from one to four scenes per year. Finally, an improvement was made to how the cover term in the soil erosion models (C-factor) was derived from the remotely sensed data. Combined, these changes reduced the average cover estimates in all NRM regions by approximately 20%. This results in a higher hillslope load being generated. Improvements were made to the sugarcane paddock model which had an impact on dissolved inorganic nitrogen (DIN) loads across the GBR. Firstly, a modification was made to the DIN generation algorithm which improved the correlation between fertiliser inputs and DIN runoff concentration. This was derived from the GBR wide pool of experimental data to improve the prediction of DIN in runoff across a season. Secondly, functionality was added to enable a proportion of the DIN reported as deep drainage from the sugarcane paddock modelling to be returned to streamflow. This approach enabled improvements to water quality as a result of reduced fertiliser application to be expressed in streamflow which was not possible previously. DIN deep drainage is known to be a major loss pathway, and the inclusion of the new approach is a major improvement to the modelling of DIN. In the previous Report Cards, management practices were described using an ABCD management practice framework. Management practices are now described in terms of their relative water quality risk from low to high. Not all management practices are equal, and the updated frameworks allows a percentage weighting to each practice depending on its relative potential influence on off-farm water quality. Soil, nutrient, and pesticide management practices are decoupled in the new management data, meaning that a parcel of land can move from a C to B practice for nutrients, for example, without improving the soil and pesticide practices. This means there are many combinations of management practices in the paddock modelling (e.g. 15 for cropping, 39 for sugarcane in most regions). Practices such as recycling pits were also added in the Burdekin and Burnett Mary sugarcane industry. A number of minor and regionally specific model updates were also undertaken to improve model performance. These include: an improved gully density map in Cape York, Burdekin and Fitzroy regions; instream deposition and remobilisation enabled in Cape York model; updating of constituent generation values (EMC/DWC) where additional monitored data was available within a region; and updated land use data for expanding industries such as bananas. Collectively these changes result in a better representation of catchment processes, and thus improved model performance. The average annual baseline load for all constituents for Report Card 2014 (RC2014) are presented in Table 1. 4 Source Catchments modelling – Updated methodology and results Table 1 Baseline GBR constituent loads TSS TN DIN DON PN TP DIP DOP PP PSII TE) (kt/y) (t/yr) (t/yr) (t/yr) (t/yr) (t/yr) (t/yr) (t/yr) (t/yr) (kg/yr) 9,398 48,275 11,868 17,972 18,435 12,045 2,294 851 8,871 7,493 Cumulative load reductions are presented in Figure 1. Reef Plan rate performance in terms of load reductions from very good to poor (refer www.reefplan.qld.gov.au). According to the Reef Plan ratings, ‘very good’ progress has been made towards the fine sediment load reduction target
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