I'm a high school student in Northern Virginia. I work on a small project that pulls together public water data (USGS stream gauges, weather, state water quality monitoring) for local rivers and turns it into simple visualizations, trends over the time, with a goal of making this data more readable and accessible to the public.

Some of that could probably be useful in a classroom, but I don't want to guess at what teachers need and build the wrong thing. So, honest questions:

1. If you've tried to use real environmental data with students, what killed it? Formatting, too many rows, no context for what the numbers mean, no time to prep, something else?
2. What's the actual unit of a useful thing to hand you? A cleaned CSV? A CSV plus a data dictionary and a few driving questions? A full lesson plan? Something else entirely?
3. For anyone doing Meaningful Watershed Educational Experiences (MWEEs): where does the data piece usually break down?
4. Is there anything you've repeatedly wanted for a local watershed unit and just couldn't find?

I'm mostly trying to figure out whether this is worth building out or whether teachers are already covered here. Please give me feedback, even if it's "we don't need this".

I'm a high school student in Northern Virginia. I work on a small project that pulls together public water data (USGS stream gauges, weather, state water quality monitoring) for local rivers and turns it into simple visualizations, trends over the time, with a goal of making this data more readable and accessible to the public.

Some of that could probably be useful in a classroom, but I don't want to guess at what teachers need and build the wrong thing. So, honest questions:

1. If you've tried to use real environmental data with students, what killed it? Formatting, too many rows, no context for what the numbers mean, no time to prep, something else?
2. What's the actual unit of a useful thing to hand you? A cleaned CSV? A CSV plus a data dictionary and a few driving questions? A full lesson plan? Something else entirely?
3. For anyone doing Meaningful Watershed Educational Experiences (MWEEs): where does the data piece usually break down?
4. Is there anything you've repeatedly wanted for a local watershed unit and just couldn't find?

I'm mostly trying to figure out whether this is worth building out or whether teachers are already covered here. Please give me feedback, even if it's "we don't need this".

I run a nonprofit called DMV River Intelligence Network, focused on building ML tools for local watersheds. Our first chapter covers the Potomac at Little Falls, and so far we've built:

• A flood prediction model (XGBoost, USGS gauge data + weather data, ~91% recall, 6-7 hr lead time)
• A live dashboard tracking discharge, gage height, conductivity, temperature, and flood risk
• Currently extending it to predict runoff volume and pollutant load using land cover, soil, and elevation data

The idea is for this to eventually be a chapter-based structure; other people could replicate the pipeline for their own rivers as part of our organization not just us scaling one model.

Trying to figure out what else would actually be useful to build next, either for this chapter or as a model for future ones. Some things I've been considering: water quality forecasting, harmful algal bloom prediction, sediment/erosion tracking, drought risk; but I don't have a strong sense of which of these are actually valuable vs. just technically interesting to me.

If you work in hydrology, environmental science, or just live near a river and think about this stuff — what would you actually want a tool like this to predict or track? What's underserved right now?

If you want to get to know more about the project: instagram.com/dmv.rivernetwork

I run a nonprofit called DMV River Intelligence Network, focused on building ML tools for local watersheds. Our first chapter covers the Potomac at Little Falls, and so far we've built:

• A flood prediction model (XGBoost, USGS gauge data + weather data, ~91% recall, 6-7 hr lead time)
• A live dashboard tracking discharge, gage height, conductivity, temperature, and flood risk
• Currently extending it to predict runoff volume and pollutant load using land cover, soil, and elevation data

The idea is for this to eventually be a chapter-based structure; other people could replicate the pipeline for their own rivers as part of our organization not just us scaling one model.

Trying to figure out what else would actually be useful to build next, either for this chapter or as a model for future ones. Some things I've been considering: water quality forecasting, harmful algal bloom prediction, sediment/erosion tracking, drought risk; but I don't have a strong sense of which of these are actually valuable vs. just technically interesting to me.

If you work in hydrology, environmental science, or just live near a river and think about this stuff — what would you actually want a tool like this to predict or track? What's underserved right now?

If you want to get to know more about the project: instagram.com/dmv.rivernetwork

I run a nonprofit called DMV River Intelligence Network, focused on building ML tools for local watersheds. Our first chapter covers the Potomac at Little Falls, and so far we've built:

• A flood prediction model (XGBoost, USGS gauge data + weather data, ~91% recall, 6-7 hr lead time)
• A live dashboard tracking discharge, gage height, conductivity, temperature, and flood risk
• Currently extending it to predict runoff volume and pollutant load using land cover, soil, and elevation data

The idea is for this to eventually be a chapter-based structure; other people could replicate the pipeline for their own rivers as part of our organization not just us scaling one model.

Trying to figure out what else would actually be useful to build next, either for this chapter or as a model for future ones. Some things I've been considering: water quality forecasting, harmful algal bloom prediction, sediment/erosion tracking, drought risk; but I don't have a strong sense of which of these are actually valuable vs. just technically interesting to me.

If you work in hydrology, environmental science, or just live near a river and think about this stuff — what would you actually want a tool like this to predict or track? What's underserved right now?

If you want to get to know more about the project: instagram.com/dmv.rivernetwork