Generation and Transport of Dredge Plumes – Synthesis of Knowledge and Considerations for Management DREDGING SCIENCE NODE

WAMSI THEME 2/3 –DR CHAOJIAO SUN- CSIRO

Acknowledgments CSIRO: Paul Branson, Nick Mortimer, Stephanie Contardo, Kenji Shimizu, Graham Symonds. Graham was the theme leader from November 2013 to June 2015.

UWA: Ryan Lowe, Marco Ghisalberti, Andrew Pomeroy, Mike Cuttler

Curtin: Peter Fearns, Passang Dorji, Mark Broomhall, Helen Chedzey

Marine Environmental Review: Des Mills

DWER: Ray Masini, Hans Kemps

Deltares: technical support and expert input

David van Senden, Des Mills, Lynard de Wit, and Mark van Koningsveld for helpful discussions

Claus Pedensen,Mark Bailey, Murray Burling, Nugzar Margvelashvili, Des Mills, David van Senden, Tim Green for contribution to the Workshop on Guidelines for Dredge Plume Modelling in Environmental Impact Assessment.

Andy Steven for continued strong support for this project.

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Acknowledgments This research was enabled by data provided by Chevron Australia Pty.

Chevron Australia Pty Ltd predicted (during Environmental Impact Assessment processes) and were approved to have some effect on corals due to the Gorgon (or Wheatstone) dredging campaign. Dredging effects that will be discussed in the following presentation are within the levels that were predicted and approved.

The State Government of Western Australia and WAMSI partners for funding this research. This project was made possible through investment from Woodside Energy, Chevron Australia, BHP Billiton as environmental offsets and by co-investment from the WAMSI Joint Venture partners.

We acknowledge the use of Fugro’s Airborne LiDAR Bathymetry datasets of the North West Shelf of Australia, which were Acquired & Owned by ©Fugro.

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Research objectives and management needs The objectives are:

• Better predict, measure and monitor relevant pressure-field parameters associate with dredge-generated sediments

• Collect pressure-field data in a consistent and effective manner The key management issues addressed by this theme are to develop protocols for

• the incorporation of contemporary understanding, algorithms and parameters in representative numerical models;

• the collection of data to optimize plume modelling; • the process of testing and validating model assumptions and

predictions.

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Compendium of Best Practice

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Chain of processes and stages from dredging to impact

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(Eekelen et al. 2015)

Approaches

Approaches

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• Literature review • Field studies • Lab experiments • Numerical modelling

Literature review

Field studies

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Onslow: sediment dynamics and optical properties (coincide with inshore and offshore dredging of the Wheatstone Project) Northern Ningaloo: sediment dynamics over coral reef communities SW Australia: seagrass meadows

Lab experiments Numerical Modelling

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• A hindcast model for the entire Chevron Wheatstone dredging campaign has been developed using the best bathymetry, forcing, boundary conditions, and extensive supercomputing resources

• Tank experiment to estimate TSS concentration and Particle Size Distributions (PSDs)

• Sediment transport through idealized canopies

Dredge plume model output

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Research projects

Sources of dredge plume

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(Courtesy of Hans Kemps)

Theme 2 Research projects Project 2.1 Generation and release of sediments by dredging and the estimation of dredge plume source terms: a review (Mills and Kemps, 2017). Project 2.2 Estimating dredge source terms – a review of contemporary practice in the context of Environmental Impact Assessment in Western Australia (Kemps and Masini, 2017).

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Theme 3 research projects Project 3.1 Literature review (Curtin/UWA/CSIRO)

Project 3.2 Plume characterisation (Curtin University)

Project 3.3 Sediment transport processes over benthic ecosystems (UWA)

Project 3.4 Numerical modelling of dredge plumes (CSIRO)

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Research outcomes

Theme 2 outcomes Project 2.1: Generation and release of sediments by hydraulic dredging

•Particle generation by break up of soil or rock material by dredging processes

•Sediment release by dredgers (TSHD and CSD)

•Near-field plume behaviour

•Sediment source strength for the far-field dredge plume

Project 2.2: Estimating dredge source terms: a review of contemporary practice

• Examined ontemporary practice on far-field source term estimation in EIA studies in Western Australia.

•Recommend the development of a Western Australian dredge source terms “data library”

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Project 3.1 Literature review Plume characterisation using in situ and remote sensing

• common measures of optical “turbidity” monitoring reviewed • nearly 70 published remote sensing TSS algorithms identified

Sediment transport processes over benthic ecosystems • mechanistic models of sediment transport in submerged canopies are severely

lacking • new field and laboratory studies of near-bed hydrodynamics and sediment

transport in benthic canopies are necessary

Numerical modelling of dredge plumes in EIA studies • limited consistency among different EIA studies on source terms • Reporting of parameterizations and parameter values are inconsistent among

different studies and often non-existent. • Uncertainty in model prediction not well understood

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Project 3.2 – Plume Characterisation: Remote Sensing

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• Light is a key factor impacting biological processes in shallow coastal waters

• In turbid dredge plumes, changes in light intensity and spectral nature are most directly affected by TSS concentration

• The best estimates of change in light intensity/colour will be derived from the best possible estimates of TSS

• The best remotely sensed TSS estimates will be derived from a locally tuned algorithm. In the absence of the locally tuned algorithm, we need a robust (transferrable) algorithm.

Motivation

Attenuation of light with TSS

Figure X: Positive TSS annual anomaly in the Pilbara region taken from MODIS Aqua imagery during 2014.

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• New TSS algorithm for the Pilbara. Assessment of “off the shelf” algorithms, and a framework for comparing new algorithms.

• Development of a 10 year TSS baseline and natural variability.

• Anomaly analysis to discern plume extent at different time scales.

• New “local” model for estimating light at depth in turbid plumes, including spectral quality.

• Demonstration of the differences in TSS reported by different satellite sensors.

Outcomes

Project 3.2 – Plume Characterisation: Remote Sensing

Project 3.2: Plume Characterisation: Remote Sensing

Key findings:

New remote sensing algorithm developed – ◦ Demonstrated as robust in terms of applicability across different water

conditions. ◦ Can be tuned to any sensor. ◦ Crucial tool for baseline and monitoring.

Residual knowledge gaps:

Different conditions impact the measurements. ◦ Different optical characteristics of ambient and dredged sediment can make

algorithms site specific. ◦ Different measurement methods produce different results.

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Project 3.3 – Sediment transport processes over benthic ecosystems

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• Most coastal ecosystems have benthic canopies (e.g., coral reefs, seagrass meadows, etc.)

• Reduced bed shear stresses in canopies → reduced sediment transport

• Need for improved sediment transport formulations accounting for canopies

• Applying sediment transport models based on open (bare) sediment can grossly underestimate sediment deposition within canopies

Pilbara dredging project

Coral reef canopy

Seagrass canopy

Motivation

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Project 3.3 – Sediment transport processes over benthic ecosystems

• New approach to predict the settling velocities of carbonate sediments using common grain size techniques

• Unique field observations of sediment transport over coral reef and seagrass canopies

• New models developed to predict the modification of bed shear stresses and near bed flows in the presence of benthic ecosystems

• A new framework for improving sediment transport predictions (deposition and resuspension)

Outcomes

Key findings: New approach and model to predict bed shear stresses in the presence of benthic ecosystems

Can be used to improve estimates of sediment resuspension and deposition in these environments

Residual knowledge gaps:

Field quantification of rates of deposition across a broader range of different habitats

Cohesive sediment transport in the presence of canopies

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Project 3.3 – Sediment transport processes over benthic ecosystem

Project 3.4 Numerical Modelling of dredge plumes

Dredge plume modelling is a complex undertaking, and is particularly challenging at the EIA stage due to unknown conditions

Need to improve the confidence of regulators to approve and increase the clarity for proponents and modellers on what is required

Uncertainty in modelling results from a number of complex processes, such as generation of plume, resuspension and deposition of ambient sediment and dredged sediment

Need for guidelines to improve model prediction and consistency in reporting

Need for guidance to translate model output into ecologically relevant pressure fields

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Motivation

Project 3.4 Numerical Modelling of dredge plumes

Guidelines on EIA dredge plume modelling on:

• estimating source terms using empirical models

• modelling resuspension in an environment with large range in bed shear stress

• number of sediment fractions

• model calibration and validation

• the process of testing and validating model assumptions and predictions

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Outcomes

• The latest empirical models applied for source term estimation and produced good agreement with observations

• Modelling ambient sediment improved simulation of resuspension process • Number of sediment fractions and settling velocity recommended • Ecological pressure fields calculated: light, TSS, deposition for duration,

frequency and intensity • Model skill evaluation, statistical presentation of model results

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Project 3.4 Numerical Modelling of dredge plumes Key findings

Project 3.4 numerical modelling of dredge plumes: Residual knowledge gaps:

• Knowledge of sediment transport model parameters for WA conditions • Interdependence of model parameters require the knowledge of reasonable

model parameter combinations • Advanced model parameter estimation techniques required (due to number

of parameters)

• Modelling of dynamic plume (highly turbulent and unsteady) ◦ Significant progress using computational fluid dynamics (CFD) to model the

hopper overflow, and a parametric model for parameters (de Wit 2015) ◦ More research is needed to model the dynamic flume computationally

efficiently which can be applied in an EIA study

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Project 3.4 numerical modelling of dredge plumes: Residual knowledge gaps

Source term empirical model application • The range of parameters difficult to establish • Additional terms for prop wash and ancillary vessel operation

needed

Ecological pressure fields: • challenges in modelling the full probability distribution of TSS to

access ecological impact • Deposition difficult to model and measure

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Project 3.4: Links to other projects and themes

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Assess model skill using MODIS TSS data Assess near-bed light using the light model developed by Project 3.2 Investigated pressure fields relevant to coral mortality developed by Theme 4

Consideration for management

Recommendations Pre-dredging survey:

If practical, TSS data, coincident reflectance, or vertical profiles of irradiance measurements (hyperspectral preferably)

Ambient sediment cover and benthic habitat properties

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Recommendations A data library including all relevant data from future EIA studies, requiring future EIA submissions to record in a database including • Source terms

• geotechnical characteristics of the substrates • Particle size distributions and physical properties • Dredge types, dredging logs, and operating characteristics

• Model input data and subsequent validation data (including metocean conditions)

• Model parameters • key model parameters and assumptions • Key source term parameters

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Conclusions • New TSS algorithm for Pilbara region developed. New “local” model for estimating light at depth in turbid plumes, including spectral quality.

• New models developed to predict the modification of bed shear stresses and sediment transport in the presence of benthic ecosystems

• New modelling guidelines developed to improve consistency and modelling process in EIA dredge plume modelling • Source term estimation • resuspension (modelling of ambient sediment) • pressure fields for ecological impact prediction • Reporting of model parameters and results • Model skills

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For more details: Tomorrow’s talks on

Project 3.2 Plume characterisation – Remote sensing by Peter Fearns

Project 3.3 Sediment transport processes over benthic ecosystems by Ryan Lowe

Project 3.4 Modelling far-field dredging generated sediment plumes – guidance for proponents and consultants by Paul Branson

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Thank you CHAOJIAO SUN, RYAN LOWE, PETER FEARNS, PAUL BRANSON