Project number: 2017-215
Project Status:
Budget expenditure: $1,680,761.30
Principal Investigator: Karen Wild-Allen
Organisation: CSIRO Oceans and Atmosphere Hobart
Project start/end date: 31 Jul 2018 - 30 Jul 2022


For the Tasmanian Salmon Industry to expand into new coastal and offshore areas it needs to demonstrate responsible stewardship and sustainable use of natural resources to maintain the support of Government agencies and the Tasmanian community. For Government agencies to assess the environmental implications of the Salmon Industry they need to understand the environmental footprint of the industry, the capacity of the environment to assimilate waste loads, vulnerable locations where impacts might be foreseen, suitable locations and times to monitor change, possible future environmental trajectories under various management scenarios, and appropriate impact mitigation strategies. With this information the State Government and Industry can demonstrate best practice in the strategic and sustainable expansion of farm sites, minimise environmental impacts and keep the Tasmanian community well informed.

An information system is required that can report and compare current water quality conditions from models and observations, provide short-term forecasts, analysis of scenario projections of plausible future conditions for planning purposes and link to decision support tools to optimise management response and monitoring programs. The modelling and information system needs to have the capability for future deployment in multiple sub-regions of interest around Tasmania. This requires a downscaling approach where high-resolution local models can be rapidly deployed within a larger scale regional model encompassing the whole of Southeast Australia.

One region with an urgent need for such a modelling and information system is Storm Bay where knowledge gaps in hydrodynamic circulation, nutrient sources and transformations, the assimilative capacity of the environment and the footprint of proposed farms, currently limit responsible industry expansion and governance.


1. To evaluate the performance of the existing hydrodynamic model of Storm Bay
2. To characterise the primary sources of nutrients into Storm Bay from ocean currents, sediment resuspension, river inputs.
3. To deliver a validated model of water quality in Storm Bay suitable for assessing future salmon farm expansion.
4. To provide an information system comprising model results, observations and synthesis analyses, with links to parallel projects (e.g. monitoring program, decision support tools, seasonal predictions).

Final report

Authors: Karen Wild-Allen John Andrewartha Mark Baird Jack Beardsley Elizabeth Brewer Lev Bodrossy Ruth Eriksen Rob Gregor David Griffin Mike Herzfeld David Hughes Pete Jansen Clothilde Langlais Nugzar Margvelashvili Andrew Martini Merinda McMahon Andrew Revill Farhan Rizwi Jenny Skerratt Cassie Schwanger Kendall Sherrin Sascha Frydman Dan Wild
Final Report • 2020-01-01 • 37.63 MB


  1. This project delivers a hindcast and near real time Storm Bay Modelling and Information System that is fit for the purpose of simulating water quality and characterising nutrients in Storm Bay from ocean currents, sediment resuspension, river and anthropogenic (including fish farm) inputs. The project has been subject to internal and external peer review, who note: ‘The authors are to be congratulated on an impressive and comprehensive modelling study and report. The work follows or exceeds current best practices in marine biogeochemical modelling and model evaluation.’
  2. The residual circulation in Storm Bay is generally clockwise, and primarily driven by freshwater input; tracers released in some side bays and at some farm sites have relatively long residence times.
  3. In summer, instabilities in the East Australia Current result in sub-mesoscale eddies and filaments entering Storm Bay with highly intermittent intrusions of warm oligotrophic water in the upper 50 m that can initiate or reinforce Marine Heat Waves, and cold nutrient-rich water at the bottom that can result in nutrient spikes. Fronts associated with 3 water masses continually move and cause large fluctuations in water quality at monitoring sites. - We recommend ongoing operation of the near real time Storm Bay Modelling and Information System, to inform the interpretation of sparse monitoring data of contemporary river plume and oceanic influence.
  4. In winter, extension of the Zeehan Current delays influx of nutrient rich sub-Antarctic water into Storm Bay, with strong interannual variability.
  5. Broad-scale simulated sediment features (kilometres and more) showed plausible sediment resuspension during extreme weather in Storm Bay; some stochastic variability was not reproduced in the model due in part to unresolved small-scale spatial variability in the hydrodynamic and/or sediment fields.
  6. Simulation of nitrogen cycling in Storm Bay shows peak surface nitrogen occurs in winter due to seasonally high river discharge and anthropogenic inputs augmented by ocean influx in late winter; in summer highly variable bottom water intrusion events bring nutrient rich sub-Antarctic water into Storm Bay. There is considerable interannual variation in nitrogen supply to Storm Bay. For the period 2016-19 on average 49% of nitrogen input to Storm Bay was from the ocean and 4% from local fish farms; loss terms included 53% exported to the ocean and 13% to local denitrification.
  7. Scenario simulations of increasing anthropogenic nutrient load predict an increase in Storm Bay water column nitrogen and chlorophyll, a small decline in bottom water dissolved oxygen and light and an increase in mesotrophic area (from formerly oligotrophic). Nitrogen budget analysis showed increasing export of nitrogen from Storm Bay to the ocean and adjacent waterways. Small systematic changes in water quality due to anthropogenic nutrient enrichment would be difficult to identify at monitoring stations due to high natural variability.
  8. New observations collected from multiple observation platforms (gliders, benthic landers, profiling moorings, small and large research vessels) at a range of spatial and temporal scales, often in locations that were difficult to sample frequently by traditional means, were fundamental to our new understanding of the influence of water masses and resuspension on water quality in Storm Bay, and essential for the demonstration of the model as fit for the purpose of simulating the water quality in Storm Bay.
  9. A laboratory resuspension process study showed a rapid increase in microbial activity and systematic decline in nutrients in overlying water during resuspension; this suggested that microbial assimilation during resuspension events can be an important pathway for nutrient transformation.
  10. Outputs from this project are made available via the Storm Bay Modelling & Information System Dashboard which has been designed with stakeholder input to meet their need for ready access to information and tools for strategic and tactical decisions. 

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