RunoffRadar

RunoffRadar is a mobile + web app that helps watershed groups, municipalities, and environmental consultants predict and document high-risk nutrient runoff events that lead to harmful algal blooms. It combines local rainfall forecasts, soil saturation proxies, land-cover data, and user-entered observations (photos, odor, water color, simple test-strip readings) to generate a “runoff risk” map and prioritized inspection routes. The MVP focuses on being operationally useful: alerts when conditions cross thresholds, a lightweight field checklist, and a clean exportable report for regulators or grant reporting. This is a combination traditional + AI app: traditional geospatial rules for baseline risk, plus AI to classify field photos (e.g., scum, turbidity cues) and to summarize weekly activity into stakeholder-ready updates. It’s not a silver bullet—data quality and local calibration matter—but it can reduce wasted field time and make monitoring more proactive than reactive.