Interest in marine tidal turbines, particularly in coastal waters, raises concerns about collisions between marine wildlife and underwater turbine blades. Research into collision rates is limited, yet predicting the probability of collisions with fish and marine mammals is necessary in order to evaluate any possible consequences for their populations. Existing collision risk models are based on analytical solutions which assume simplistic non-behavioural traits. This paper seeks to extend these collision models to represent real behaviours of marine species by extending an existing numerical Agent-Based Model (ABM). The new ABM successfully reproduces the results of the Collision Risk Model (CRM) (Band et al.,2016) showing that the predicted collision rates are equivalent for both models. Application of the ABM to simulate migrating silver eels passing a tidal turbine in Strangford Narrows results in low rates of collisions, with just 1.1% of eels passing the Narrows predicted to collide with the turbines. Sensitivity tests with different vertical swimming behaviours were found to influence the number of eels leaving the estuary and the number of predicted collisions. The ABM could be further extended to include other behaviours (e.g. active turbine avoidance) and provides a valuable method for assessing turbine interactions based on animal behaviour.
An agent-based model to predict fish collisions with tidal stream turbines
Rossington, K.; Benson, T. (0). An agent-based model to predict fish collisions with tidal stream turbines. Renewable Energy, .