Dredge Plumes: Ecological risk assessment

Dredge Plumes: Ecological risk assessment

Becker, J.H.

Van Koningsveld, M. (mentor)
Vrijling, J.K. (mentor)
De Boer, G.J. (mentor)
Van Gelder, P.H.A.J.M. (mentor)
Den Heijer, C. (mentor)
Wang, Z.B. (mentor)

Civil Engineering and Geosciences

Hydraulic Engineering

Hydraulic Engineering and Water Resources Management

2011-12-16

Nowadays, the ecological effects of dredge plumes are usually managed based on the precautionary principle. Predictions of suspended sediment levels are made, which have to be compared to thresholds set by the responsible authority. Failing to comply may cause a project to be delayed and thus lead to additional costs. The precautionary principle however is vague and incorrect, since it does not take into account the benefits of the dredging activity. The proper question to ask is whether the dredging activity should be allowed to harm the ecosystem or the ecosystem should be allowed to harm the dredging activity. To be able to answer this question, ecological risk is required to be assessed in a quantitative manner. A suitable framework to do so is provided by the Ecological Risk Assessment (era), which enables a risk agent to include uncertainties explicitly. An era consists of a description of the system and its components, hazard identification, effects assessment, exposure assessment, risk characterization and an evaluation which provides feedback for a possibly updated system description. The effects assessment relates suspended sediment concentration and exposure duration to the response of a sensitive receiver. A graphical representation of this relationship is a dose-response curve, which represents the resistance of the species, or 'strength'. Field measurements or laboratory experiments are necessary to enable the development of dose-response curves for important sensitive receivers. The exposure assessment starts with the formulation of the dredge plume source term. The complex dynamic phase of the plume is not modelled, but is incorporated in the source term by means of established empirical relations. The passive phase is modelled by a hydrodynamic and transport model, which results in a time series of suspended sediment concentration levels at the location of the sensitive receiver. This is translated into a concentration and an exposure duration, which can be interpreted as the 'load'. When effects and exposure have been estimated, the risk has to be characterized. There are several ways to do this, which depend on the treatment of uncertainty. A probabilistic approach incorporates variability in exposure and effects estimates and a deterministic approach estimates one representative value for exposure and compares this with one representative dose-response relationship. A probabilistic approach enables the determination of a 'failure probability'. This provides confidence levels for the obtained results and points to gaps in knowledge. In general, insight in probabilities is assumed to enable a better risk assessment. When these methods are applied in practice, it depends on the situation at hand which technique is most suitable to estimate risk. In the design and planning phase of dredging works a probabilistic analysis is the preferred option, to identify possible new areas of investigation or research or to support the development of a monitoring strategy. It is however computationally expensive to carry out a Monte Carlo analysis to assess long-term exposure. On the other hand, when dredging works are already in progress, a deterministic analysis satisfies the desire for a quick assessment of the risks. Execution methods can in that stage still be changed and mitigating measures might still be implemented. In conclusion, for a quantitative assessment of ecological risk it is necessary to carry out a probabilistic analysis. Costs and benefits of a dredging project can then be determined, which enables a complete economic analysis and a transparent decision making process.

dredge plume
ecology
risk assessment
probabilistic
species response curve

http://resolver.tudelft.nl/uuid:98e64038-86f4-4588-92ae-40b09783f251

2014-12-16

Student theses

master thesis

(c) 2011 Becker, J.H.