Potomac River Play Spot Alert System

This project is a working prototype for an automated river monitoring system designed around a real kayaking decision: which Potomac River play spots may be working today.

Instead of checking the NOAA gauge manually and comparing the level against a separate play spot table, the system retrieves the latest available BRKM2 level, checks the forecast for 6:30 PM, and compares both values against a stored list of play spot ranges.

The result is a dashboard and email alert design that can show which features are currently in range, which features may be in range after work, and whether the water is expected to rise, drop, or stay about the same.

The project uses two separate components: a public dashboard and a private automation workflow. The public website displays live river information, while the email notification runs separately through Google Apps Script.

This separation is important because the website is public. Sending email directly from the browser would expose private credentials or email service keys. Instead, Google Apps Script runs privately from a Google account and can be scheduled to execute automatically.

In the implemented workflow, Google Apps Script checks the NOAA BRKM2 gauge data, reads the current river level, checks the forecast value closest to 6:30 PM, compares those values against the stored Potomac play spot ranges, and sends an email summary to the selected recipient.

• GitHub Pages displays the public river dashboard.
• Google Apps Script runs the private email automation.
• The script checks NOAA BRKM2 observed and forecast data.
• Alerts are scheduled for 6:00 AM for daily planning and 4:00 PM for after-work decision-making.
• Email permissions remain private and are not exposed on the website.

This project demonstrates how a simple information system can turn live public data into a useful personal decision-making tool.

Instead of only displaying a river level, the system connects data to a real decision: whether specific kayaking features are likely to be working now or after work.

The same logic could be applied to facilities monitoring, equipment alerts, inventory thresholds, weather notifications, or any process where users need to know when data reaches a specific condition.