Exploring the nexus between coastal tourism growth and eutrophication: Challenges for environmental management

Coastal tourism has witnessed rapid growth over the past two decades, often accompanied by increasing environmental concerns, particularly eutrophication in sensitive marine zones. This study explores the relationship between coastal tourism expansion and eutrophication across the Mediterranean region from 2000 to 2023 using Support Vector Machines (SVMs) as a predictive analytical model. By integrating long-term environmental monitoring data with tourism statistics, the study identifies key drivers of water quality deterioration. Results reveal that areas with intense tourism activity exhibit significantly elevated nutrient levels, with a 40 % rise in nitrogen and phosphorus concentrations and a shift in TRIX index values from mesotrophic to eutrophic conditions. SVM analysis accurately predicted eutrophication zones with over 90 % classification accuracy, highlighting seasonal peaks in degraded water quality corresponding to high tourist influx. Regions with integrated environmental management demonstrated greater ecological resilience. The findings emphasize the need for strategic planning and predictive modeling in balancing tourism development and environmental protection. Incorporating machine learning tools into coastal management can enhance early detection and targeted intervention in eutrophication-prone areas.