WAMSI 2 - Dredging Node - Theme 3 - Synthesis Report - Characterisation and prediction of dredge-generated sediment plume dynamics and fate.

Brief description

Dredge plume modelling is often used in Environmental Impact Assessment (EIA) of large-scale port and coastal developments to quantify and model the transport and fate of sediments released during dredging operations. The objectives of the WAMSI Dredging Science Node (DSN) Theme 3 was to provide insights and guidance on ways to improve the modelling and monitoring of passive dredging plumes to support the EIA and management of dredging programs, with a focus on the Pilbara region of Western Australia. By carefully designing a number of laboratory, field and numerical model investigations, Theme 3 advanced the modelling and measurement (via remote sensing) of dredging generated plumes. Under an agreement with WAMSI, unprecedented access was granted to baseline, dredging and monitoring data from a major dredging project in the Pilbara region. Effort focused on modelling the dynamics and fate of total suspended solids (TSS) in the passive dredging plume, with the goal of identifying the most important processes and model parameters. Those processes included in-canopy sediment transport processes, the bed schematization and cohesive sediment transport model parameters. The utility of applying remote sensing techniques to monitor sediment plumes and establishing background conditions was also explored. Importantly, the research program was undertaken to ensure the model output parameters and their representations and analyses, were compatible with the critical effects thresholds (e.g. 14 day running percentiles, daily light integral) that were being generated by the biological themes of the WAMSI DSN (see Themes 4 to 7).

Lineage

Statement: The focus areas of the Theme 3 research program were to develop better TSS algorithms for remote sensing, improve understanding of the modified sediment transport process over canopies, and carefully develop a model hindcast to investiage model sensitivity and assess ecological pressure field prediction. Further details are in the synthesis report