Sewage and Algae Blooms

This project aims to create a potential warning system for Harmful Algae Blooms (HABs) by tracking multiple pollution pathways including Combined Sewer Overflows (CSOs), toxic runoff, and nonpoint source pollution — environmental issues particularly acute in New England. • We will collect and monitor federal, state, and local data describing when and where CSOs occur, while simultaneously tracking water quality chemical indicators that signal toxic runoff events. This integrated approach combines CSO discharge timing and precipitation-triggered water quality anomalies (indicative of potential toxic runoff) to create a comprehensive pollution event detection system. • Using satellite imagery acquired 24-72 hours following identified pollution events (CSOs, water quality runoff indicators, potentially heavy rainfall as well), we will monitor and detect HABs using the ABD (Algal Bloom Detection) repository, a production-ready open-source system that combines machine learning algorithms with satellite data analysis. The ABD system provides sophisticated anomaly detection capabilities specifically designed for HAB identification using multiple satellite sensors and validated machine learning approaches. • The system will correlate ground-measured chemical pollution indicators with satellite-detected bloom formations to improve prediction accuracy through ABD's integrated validation framework that combines One-Class Support Vector Machine, Random Forest, and Isolation Forest algorithms for robust detection. • We will eventually (in the spring of 2026) design an accessible app for New Englanders that displays CSO locations, common toxic runoff sites, and HAB formations with their pollution sources identified. Users will receive notifications when HABs exist in their area, with specific information about the likely pollution pathway (CSO vs. runoff vs. combined sources). The app will enable community members to contribute both photographic documentation and simple chemical test results to validate ABD's automated detection results. This project addresses the critical gap left by potential federal cuts to EPA monitoring systems, particularly the cyAN web app, while providing environmental justice communities with comprehensive water quality information across multiple pollution pathways.