Why We Have Billions in Flood Data (But You Still Can’t Find It)

At a minimum, you should be able to look at a map and know if you are standing in a flood zone.

It sounds simple. We have spent billions of tax dollars scanning the entire surface of the United States down to centimeter accuracy. We have thousands of stream gauges monitoring water levels every 15 minutes. Yet, when a flash flood hits, most people are caught completely off guard.

Why? Because the data is stuck in the “tap water” phase—it’s there, it keeps you alive, but it isn’t packaged for consumption.

In this episode, Kevin Bullock explains how he turned a frustration with fragmented government data into Hydra Atlas, a mobile app that acts as a personal flood safety tool.

Key Takeaways

1. The “Accessibility Gap” is a Business Model Data availability does not equal data accessibility. Kevin notes that while FEMA, NOAA, and the USGS produce incredible datasets, they are often siloed. You might check a weather app for rain, a FEMA map for insurance zones, and a USGS site for river levels. Aggregating these into a single view is where the real value lies.

2. The “Tap Water” vs. “Bottled Water” Analogy Kevin compares government open data to tap water: it’s free (or cheap), functional, and essential. Commercial data is “bottled water”—it’s the same core product, but refined, packaged, and sold for a premium (better UI, smoother animations). There is room for both, but the public “tap water” needs to be easier to drink.

3. Real Estate vs. Real Life Most flood data is geared toward property value (insurance rates, Zillow scores). But flood risk is a mobile problem. You need to know your risk when you are camping in a dry riverbed or driving through an unfamiliar town not just when you are buying a house.

4. Simplicity Requires Iteration Kevin rebuilt the UI of Hydra Atlas over ten times. When dealing with complex geospatial layers, the tendency is to show everything. The discipline is to strip it back until it answers the only question that matters: “Am I safe right now?”

5. The Power of the “Side Quest” Hydra Atlas wasn’t a VC-backed startup; it was a “Kevin project.” He used AI tools (like Claude) to help write Swift code and leveraged his LinkedIn network for beta testing. The barrier to building professional-grade geospatial tools has never been lower.

How to Apply This

If you are a data professional or developer, here is how you can use Kevin’s approach:

• Find the Friction: Don’t just make a map. Look for data that is technically “public” but practically impossible to use (e.g., buried in PDFs or archaic portals).
• Build for the “Mobile Moment”: Ask yourself where the user is when they need this answer. If they are in the field, a desktop dashboard is useless.
• Use AI to Punch Above Your Weight: Kevin is not a native mobile developer, but he used AI coding assistants to debug Swift and handle API integrations. Use these tools to bridge your skill gaps.
• Ship the “Tap Water” Version: You don’t need expensive commercial data feeds to start. valid, open government data is enough to build a Minimum Viable Product (MVP) that saves lives.

Want to see how deep the open data rabbit hole goes? Listen to the full episode to hear Kevin’s journey from aerospace engineering to building one of the most practical geospatial apps on the store.