Standard Presentation (12 minutes) Australian Marine Sciences Association 2025 Conference

Improving coastal clean-up with GIS-based predictive modelling (119721)

Michael Traurig 1 2 , Emily Nicholson 2 , Chloe Sato 3 , Kay Critchell 1
  1. School of Life and Environmental Sciences, Deakin University, Melbourne, Victoria, Australia
  2. School of Aggriculture, Food and Ecosystem science, University of Melbourne, Melbourne
  3. DCCEEW, Canberra

Coastal environments, continuously impacted by human activities and natural processes, face significant challenges from marine debris accumulation. This study utilises GIS-based models to optimise clean-up resource allocation in the Whitsundays, northeast Queensland, Australia. We developed a gravity model to predict visitation and amenity value of beaches, and a wave exposure model to estimate debris deposition from non-local sources. Our findings indicate that exposure and gravity are key influences on debris accumulation, with non-local debris being a major contributor. The gravity model, which was validated against external visitation data, proved effective in assessing amenity value but has limitations in high-value, remote locations.

Using beach clean-up data as training points, we predicted debris accumulation and calculated gravity across the Whitsundays coastline, identifying high-priority clean-up sites. Our approach provides NGOs prioritisation choices based on stakeholder preferences, balancing environmental preservation with recreational and economic benefits. This study emphasises the importance of volunteer organisations in both clean-up efforts and data collection, which are crucial for monitoring and managing marine debris accumulation. Our adaptable methodology can be replicated in other regions with sufficient clean-up data, supporting global marine debris management efforts.