- On 18th April 2016
- In Dredging
- By William
Adaptive Management (AM) is an iterative decision framework that allows a decision-making to be more flexible and refined towards future uncertainties as monitoring data and the effects of actions become better understood. AM is especially useful for dredging projects where the potential environmental impacts are inherently uncertain, or where there is a low level of confidence in the predicted effects.
By improving the understanding of the environment, through baseline monitoring and modelling during the project design phase, impacts can be better predicted and projects optimised in relation to cost and avoiding environmental impacts.
During the project execution phase, surveillance monitoring and adaptive management allow for swift responses and the identification of suitable solutions, without losing time or exceeding budgets. Stakeholder consultation ensures that suitable opportunities are explored and all parties are aware of the strengths of this flexible approach.
This review first discusses the benefits of AM and then explores its use in a recent project. Although AM has potential disadvantages; potentially conflicting with prevailing law and statutory approaches to protecting the environment. During the execution phase the AM approach made new methods possible and resulted in significant cost savings for the client and continued environmental protection.
Managing Dredging Projects
Due to the inherent variability of the natural environment, between different locations and over time, the prediction of the environmental impacts of marine infrastructure works and dredging activity can be uncertain. Additionally, licensing permits often stipulate adherence to environmental legislation and specified environmental thresholds. The careful planning of projects is therefore essential, yet not every aspect of the project can be foreseen or predicted with sufficient confidence at the outset.
Adaptive management (AM) is a decision-based framework that facilitates flexible decision making and can be refined in response to future uncertainties through a monitoring-evaluation-adjustment cycle (CEDA, 2015). This allows project managers to remain flexible, offering several solutions to changing or unforeseen circumstances and ultimately leading to the desired result.
Whilst monitoring baseline conditions offers an initial understanding of the environment, modelling is often required to provide sufficient detail of site complexity prior to the start of works. Consequently, potential impacts can be better predicted making the project more robust to uncertainty. Surveillance monitoring and AM, during and following project execution, also allow for impacts to be identified and remedial action to be implemented in a stepwise procedure to address unforeseen circumstances encountered as a project progresses.
The AM approach is widely acknowledged as a useful tool for protecting the environment while carrying out dredging and marine infrastructure projects, using stakeholder consultation, monitoring and surveying to assist in achieving timely delivery, reducing financial outlay and avoiding negative environmental impacts throughout the projects lifespan.
The case study chosen to illustrate the application of AM is a medium scale dredging project in a small estuary in the South East of England. Exo Environmental and Svašek Hydraulics teamed up to collect data on the hydrology, morphology, and characteristics of the estuarine environment. The data were used to create a hydrodynamic and morphodynamic 2D model of the environment to support the proposed dredging project.
Baseline monitoring involved deploying acoustic Doppler technology to understand hydrodynamic fluctuations during a whole astronomical tidal cycle, allowing natural variability to be distinguished from future changes and variation caused by dredging activity. A multi-parameter water quality sonde was deployed to measure background depth, pH, conductivity, temperature, dissolved oxygen and turbidity. Using water samples, turbidity was correlated to suspended solids through laboratory testing.
A van Veen grab sampler was also used to collect sediment samples to allow bed material characterisation, and also cohesive strength measurements were made to assess the sites’ resilience to erosion. This additional baseline monitoring provided background data and model input.
Determining the effects of dredging can be carried out by assessing the physical and ecological processes at the project site and surroundings. Given the complexity and vulnerability of estuaries, advice is often based on expert judgment and will likely be conservative, limiting the number of options for a dredging strategy.
A hydraulic model was created to predict the behaviour of dredged material in relation to the physical and ecological processes, and from this multiple dredging strategies could be assessed and a more cost effective dredging strategy identified. Accurate model predictions depend heavily on a good understanding of local hydrodynamics, and the monitoring data gathered by Exo Environmental was essential for that purpose. Bathymetric measurements created an accurate digital terrain model, and by comparing the model with hydrodynamic measurements the model settings could be adapted in order to verify the model predictions with reality.
The model predicted that dredged material could be safely discharged into the creek during the flood or ebb tide without harming the environment and there was also the potential for sediment discharge to improve the local ecological quality of the eroding mudflats and saltmarshes.
For the modelling process Svašek used its in-house model FINEL2D. This model simulates flow and transport processes in rivers and coastal waters. Additionally, using robust procedures for ebbing and flooding of tidal flats, FINEL2D is also suitable for modelling flow and morphology in estuaries.
FINEL2D has a flexible grid generation, extending both over a large area covering the majority of the North Sea and the English Channel, whilst simultaneously using cell sizes of just a few square meters to provide greater cell density and resolution at the point of sediment dispersal. This large-scale and detailed small-scale resolution provides greater accuracy of the model output compared to a simulation at a large-scale only. Compared to models using small cell sizes throughout, the simulation times with FINEL2D are substantially shorter, enabling 14-day period simulations to be completed within a day. Consequently, the model could be updated as new information and data became available, allowing AM of the dredging strategy throughout the project.
The model outcomes changed the initial project design significantly, from an initial option proposing local sediment containment and storage, to an option where sediment was dispersed within the estuary, reducing the maintenance dredging cost by approximately 50%.
However, when dealing with the marine environment uncertainties always remain present. Therefore, AM introduces a sequence of events including monitoring, impact assessments and management actions, that are implemented when the outcomes and impacts of the project are uncertain or difficult to predict.
AM can be supported through an Adaptive Management Plan (AMP). Generated through stakeholder consultation in the initial project design phase, this defines: roles and responsibilities; procedures; compliances; and tiered management actions in response to agreed trigger levels.
Throughout project execution, the results of the ongoing surveillance monitoring provide feedback information on the impact of the different activities and corroboration of the predictive accuracy of the design models and areas for refinement. Utilising these data, AM actions for the dredging design may be implemented in a stepwise procedure while the project is proceeding, creating an increasingly efficient and cost-effective project design whilst minimising environmental impact.
These corrective actions, described by the AMP, are constantly reviewed and adapted in response to additional data and follow a source-pathway-receptor model. For example, a dredging activity (source) causes an environmental change such as a sediment plume that, through dispersion and deposition processes (pathway), can impact a defined spatial area of sensitivity (receptor).
Surveillance monitoring of the receptor is undertaken to qualitatively and quantitatively identify an impact. In cases where environmental receptors react slowly to impacts, dual monitoring of the pathway and receptor can be employed to allow early detection. Defined trigger levels agreed upon in the AMP and identified through surveillance monitoring, then result in designated AM actions to allow suitable and timely mitigation of a potential impact.
Although monitoring activities come at a cost, the flexibility of the approach makes it more efficient to deal with inevitable uncertainties, minimise the waste of resources and avoid prolonged project duration. These benefits also improve the outcomes for the environment and the client.
Throughout the project, public and stakeholder engagement is carried out in order to develop a common understanding of the uncertainties and the opportunities, securely controlled by surveillance monitoring and AM.
It is of key importance for everyone involved to understand the flexibility of the approach, which can influence the amount of effort required to succeed with the project.
The approach utilised for this project made new methods a possibility and resulted in significant cost savings. Furthermore it also provided a solution to the ongoing maintenance of the site, rather than a one-off solution.
Contact us for more information on how we can successfully manage your next dredging project.