Understanding impacts of dredging activities
Large-scale dredging campaigns can remove millions of tonnes of material from the seabed, creating dredge-induced suspended sediment plumes (dredge plumes), potentially transported over great distances.
Sediment plumes can reduce the amount of light reaching the seabed and in low-energy areas, result in increased sediment deposition on the seafloor. Sensitive benthic marine communities (e.g. coral, seagrass and sponge communities) have the potential to be negatively affected by the additional sediment in the water column or deposited on the seafloor, creating unwanted ecological impacts. The scale of these impacts require assessment.
Increasing confidence in the use of dredge plume model predictions
Dredge plume modelling is a useful tool that is designed to predict the dispersion and fate of dredge plumes. The outputs from these models are often used as part of the Environmental Impact Assessment (EIA) process to predict the fate of dredge plumes and the impact these plumes may have on the receiving environment.
There has been much debate on how modelling should be undertaken, with inconsistencies in how they are applied for EIA purposes. In light of this, environmental regulators have generally taken a precautionary approach when using these outputs to evaluate environmental impacts and any monitoring that may be required as part of the dredge activities regulatory approval.
To address this challenge, CSIRO has prepared a dredge plume modelling guideline to assist in establishing consistent modelling approaches, providing improved robustness and assurance in modelling outcomes. It is hoped that the availability of this guideline and its use will lead to improved public confidence in the EIA process and will reduce the monitoring and management burden associated with large-scale dredge activities.
The Guideline draws heavily on learnings from the WAMSI Dredging Science Node and provides recommendations on a number of concepts including source estimation, modelling strategy, uncertainty evaluation, and the need for a public database to capture EIA data to improve future modelling exercises.