Mapping the Unheard: Analyzing Tradeoffs Between Fisheries and Offshore Wind Farms Using Multicriteria Decision Analysis

Abstract

Identifying offshore wind energy sites involves analyzing multiple variables, such as wind speed, proximity to the coastline, and sociocultural factors. This complex decision-making process often involves many stakeholders, resulting in conflicting data and goals. Decision analysis that promotes collaboration, transparency, understanding, and sustainability is key. This study presents a unique model of human–environment interaction that reconciles different perspectives and visualizes the balance between fisheries and wind power. Using three multicriteria decision models (weighted aggregated sum product assessment [WASPAS], technique for order of preference by similarity to ideal solution [TOPSIS], and analytical hierarchy process [AHP]), we analyze the decision mix for wind farm selection and assess the impacts on fisheries using historical data. Our approach was applied to an upwelling system in California, generating ten tailored decision scenarios for different stakeholder groups. The results showed that adaptation scores for specific call areas in northern California decreased when the weight of fishery factors increased, and there was a tendency for high-scoring areas to shift southward as fishery parameters increased. The results of the sensitivity analysis showed that the first-order sensitivity scores of WASPAS were better correlated with the weights compared to TOPSIS, whereas the second-order sensitivity scores were generally lower, indicating a reduced interdependence of our model.