Improvements to Probabilistic Tidal Turbine-Fish Interaction Model Parameters

Conference Paper

Title: Improvements to Probabilistic Tidal Turbine-Fish Interaction Model Parameters
Publication Date:
April 27, 2015
Conference Name: 3rd Marine Energy Technology Symposium (METS)
Conference Location: Washington DC, USA
Pages: 6
Technology Type:

Document Access

Attachment: Access File
(377 KB)


Tomichek, C.; Colby, J.; Adonizio, M. (2015). Improvements to Probabilistic Tidal Turbine-Fish Interaction Model Parameters. Paper Presented at the 3rd Marine Energy Technology Symposium (METS), Washington DC, USA.

Atlantic sturgeon (Acipenser oxyrinchus) are a protected species that are known to traverse the area occupied by Verdant Power’s Roosevelt Island Tidal Energy (RITE) Project in the East Channel of the East River, New York City (NYC). To acquire regulatory permits for the installation and operation of the project, it was required to determine the likelihood of a kinetic hydropower system (KHPS) turbine strike on these species. A probability based model, known as the KHPS-Fish Interact ion Model was developed to quantify the risk of the turbine striking these fish and used for the Federal permitting process.


The methodology, original assumptions and associated probability estimates behind the model are presented, along with parameter updates based on recently collected data. At RITE, the model quantifies the risk to Atlantic sturgeon by the Verdant Power horizontal axis, 3-bladed open-rotor turbines. Although the primary focus of the model was turbine interaction with Atlantic sturgeon in the East River, NYC, it was developed so that it could be used and updated at various sites where KHPS are considered as part of a project’s environmental compatibility evaluations.


Research conducted by Verdant Power since 2011 in collaboration with the Atlantic Cooperative Telemetry (ACT) Network detecting previously tagged Atlantic sturgeon has shed insight into some of the parameter values. As information is learned from the results of the adaptive management monitoring plans, modeling parameters have been modified based on actual data. Three of the seven model parameters have been recently updated from a basis of best assumptions to be a determination from data collected in situ, as discussed in this paper.

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