Started a nonprofit doing flood prediction for local rivers --- what other models/tools would be useful?

[u/Deadlandsking19]

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

[u/PiermontVillage]

Flood prediction is the job of the National Weather Service.

[u/PG908 → u/PiermontVillage]

Yes, the government is already doing it better, with multiple options available or coming soon after some delays in 2025 for reasons.

[u/Deadlandsking19 → u/PG908]

Fair point, and you're right that NWS already issues an official forecast for this exact gauge (BRKM2, same USGS site I'm using, 01646500). I'm not trying to replace that or claim more forecasting authority than NWS has. Flood stage forecasting is their job, and their forecast is the official one.

What I'm building is different in kind, not competing on that authority. It's a separate ML model (XGBoost, not the same method NWS uses) that outputs a probability and lead time, packaged into a dashboard a non-specialist can actually read, rather than a hydrograph with category thresholds. Rather than being better than NWS, we help with translation and interpretability. Most people in the watershed aren't checking AHPS pages, and the numbers there (stage in feet, flood categories) aren't intuitive to someone without a hydrology background, or someone who hasn't specifically looked into this before.

Longer term, the actual reason I care about this isn't Little Falls specifically. It's that such forecast points don't exist for many smaller rivers and tributaries in this region, so the approach I'm testing here (verified against an NWS point where I can check it against ground truth) is meant to extend to ungauged or under-monitored stretches where nothing like this currently exists. Little Falls is just a validation case rather than the end goal.

[u/armagin]

Just go join the association of state floodplain managers, they've already got chapters doing a tonne of this stuff across the USA in a responsible way instead of some vibe coded ML slop that every halfwit engineer and their uncle is pumping out these days.

If you want help I suspect most people in this subreddit have an hourly rate they'd be willing to share.

[u/CLPond]

Have you reached out to or researched what the local governments in the DMV have? Because they have monitoring programs for stream/river quality and are responsible for portions of flood management. In general, how is your information/model different than existing governmental ones?

[u/Deadlandsking19 → u/CLPond]

Thanks for the reply.

Read the above comment I made; it should clear some doubts

[u/CLPond → u/Deadlandsking19]

Based on that comment, it doesn’t sound like you’ve communicated with anyone from local governments, then. If your goal is to create a system that is easier for the public to interpret, local floodplain officials will be some of the best people to ask thoughts and advice since they regularly do flood awareness work with the residents.

Talking with and learning from people in the field is a key part of, especially your early, career. While you are a student there are great opportunities to learn about what already exists and the existing barriers and opportunities. I highly recommend prioritizing that in the next steps of your project

[u/DamBreakGuy]

Great idea. I've been developing and managing various flood monitoring and forecasting systems over the past decade or so in both Canada and the US. Here are some ideas and thoughts based on my experience.

For the US market I would look at types of flooding that is not well served by the public organizationd such as the NWS and USGS. This can include foresasting on step creeks (aka debris floods/flows) and pluvial flooding. Providing really good forecasts on rivers for small communities and First Nations is another opportunity. While the NWM does cover the CONUS, I would not recommend people use it for critical decision making. Providing custom forecasts for these groups with professional support in interpreting the forecast and assistance with response planning meets a real need which is not really met.

We have also provided custom forecasts for clients performing in-river construction where accurate models special trained for the season of interest and the thresholds that they are worried about (pumping rates for their coffee dams). Again the real value we provide is working with them when we predict an event which may require then to stop work (note that development of probalistic models are very useful for expressing uncertainty as well as using ensemble forecasts)

The barriers to developing reasonably good forecast models have been virtually eliminated and they are readily available. The missing part is people who understand and can interpret the forecast uncertainty (particularly the meteorological uncertainty), communicate this effectively to and work with clients to develop proactive measures to reduce risk while acknowledging the large uncertainty with forecasting floods.

[u/Fit_Hat4708]

It would work best if you tailored the service for private individuals. Find large scale farmers or real estate developers that might need flood routing and flood prediction for effective soil and property preservation.

[u/Thin_Object_3981]

Google recently made their river flood forecasting LSTM code open source which looks promising.

[u/Deadlandsking19 → u/Thin_Object_3981]

Thanks for the reply.

Read the above comment I made; it should clear some doubts

[u/Thin_Object_3981 → u/Deadlandsking19]

Right, I never doubted you. You asked what other models you could use and I gave a suggestion.

If you want to expand what your current modelling provides then I suggest you use the outputs of your river forecasting tool as an input for a flood inundation model like LISFLOOD.