A subdivision gets built in a flood zone between inspection cycles. A “low hazard” dam quietly becomes an “intermediate” or “high” one — but nobody updates the classification because nobody’s looking at it. When a storm hits and the EAP gets activated, the address list is three years old and missing an entire neighborhood.
That scenario isn’t hypothetical. It’s what happens when downstream risk is changing as populations and land use change, extreme rainfall and flood exposure are increasing in some locations, traditional downstream hazard assessment is manual, resource-intensive, and updated infrequently, and regulators are being asked to do more with limited staffing and large dam portfolios.
This case study describes how a U.S. state dam safety program worked with Rezatec to build an automated geospatial workflow that screens downstream exposure across a large dam portfolio — and what the results looked like.
The problem: manual assessment can’t keep pace with development
State dam safety programs are responsible for hundreds or thousands of dams spread across dozens of counties. Hazard classifications are supposed to reflect what’s actually downstream — people, buildings, roads, critical infrastructure. But, those classifications often lag behind reality.
Between review cycles, new homes get built inside inundation zones. Roads get extended through downstream corridors. A dam that was correctly classified as “low hazard” five years ago may have 50 new addresses in its inundation footprint today. Nobody catches it until an event forces a closer look.
The manual process — pulling satellite imagery, cross-referencing address databases, checking inundation maps one dam at a time — takes weeks for a single county. For a state program with hundreds of regulated dams and a small team, that’s not a realistic refresh cycle. It means classifications go stale, EAP address lists fall behind, and emergency responders work from incomplete data during the events that matter most.
This state needed a way to screen downstream exposure across its full portfolio — automatically, repeatedly, and without adding staff.
What the workflow was designed to do
The Rezatec workflow targets three specific problems:
1. Hazard classification review
Keep hazard ratings appropriate as downstream exposure changes. When new buildings appear inside an inundation zone, the workflow flags that the current classification may no longer be accurate. It doesn’t reclassify the dam — it tells the regulator where to look.
2. Emergency response and preparedness
Improve access to at-risk downstream information during time-sensitive events. During a rapid pool rise or spillway concern, responders need current address lists and road closure points — not data from the last inspection cycle.
3. EAP inventory support
Support dam operators with dynamic address and infrastructure mapping. Rather than maintaining static address lists that decay over time, the workflow produces address inventories that can be refreshed whenever updated data is available.
These aren’t separate tools either. They’re all outputs from a single automated pipeline.
How it works
Data integration
The workflow pulls dam inventory and hazard ratings provided by the regulator or NID sources. Inundation zones come from hydraulic modeling or terrain-based screening. Base maps include satellite imagery and street maps. Updated datasets can be uploaded to rerun the workflow.
That last point matters. This isn’t a one-time analysis. When the regulator gets new inundation mapping or an updated NID extract, they upload it and the workflow runs again against the same dam portfolio.
Automated address lists
The system identifies buildings, addresses, and road networks within and near inundation zones. It considers inundation polygons and buffer zones, uses reverse geocoding to assign addresses, and links each building to one or more inundation zones.
The output is a structured table: every building in or near each inundation zone, with an address, a location, and a zone linkage. That’s the kind of data emergency managers actually need during an event — not a map they have to interpret, but a list they can hand to a dispatcher.
Identifying roads at risk
The workflow identifies major roads and road crossings within inundation zones. It allows users to add, edit, or remove closure points and supports road closure planning during emergency response.
Road closures during a dam incident are one of the first operational decisions emergency managers make. Having the crossings pre-identified — with editable closure points — means that planning doesn’t start from scratch every time.
Hazard and exposure analytics
The system counts addresses within each inundation zone and buffer. It detects year-on-year development change — what the project team calls “hazard creep.” And it flags dams that may need follow-up review.
For example, thirty new houses go in downstream over five years, and by that time a low-hazard classification stops reflecting reality. The workflow catches that automatically.
Mapped and tabular outputs
Results include interactive mapping of dams and inundation zones. Users can filter and sort by hazard class, EAP status, county, and update year. Address lists are grouped by inundation zone. Emergency response data is exportable, and not just in a summary view.
The central office can export the entire emergency response plan from the Downstream Hazard platform as a shapefile and share it directly with local emergency response teams. That shapefile includes the identified hazards within the platform: address lists, road closure points, and inundation zone boundaries. Export formats also include Excel, CSV, and PNG, depending on the downstream use.
That matters operationally. A state-level regulator running the central platform doesn’t need every county emergency manager to log into the system. They export the shapefile, send it to the local team, and the local team loads it into whatever GIS or mapping tool they already use. The emergency response plan travels to the people who execute it — in a format they can act on.
The interactive map gives a portfolio-wide view: hazard-rated dams color-coded by classification, overlaid with inundation zones, buffer rings, and building addresses. For a regulator managing hundreds of dams, that view answers the first question — “where do I focus?”
What the workflow demonstrated
The pilot demonstrated that manual analysis could be reduced from weeks to hours. It improved accuracy and repeatability, provided faster access to inundation extents and at-risk addresses, and proved scalable across large dam portfolios.
Weeks to hours is the headline number, and it’s significant. But the repeatability point may matter more over time. A manual analysis depends on whoever runs it — their data sources, their judgment calls about which buildings count, their willingness to re-check last year’s work. The automated workflow produces the same result every time it runs on the same input. When you need to defend a hazard classification decision or demonstrate that you reviewed downstream exposure, that consistency matters.
Lessons learned
Input quality and refresh cycles matter. Outputs must support specific use-cases for operational and emergency response workflows. Screening should support review, not replace engineering judgment. Change tracking improves governance and traceability.
The third point deserves emphasis: this workflow is a screening tool. It tells you which dams have growing downstream exposure and which addresses fall inside inundation zones. It does not tell you whether a dam is safe, whether a hazard classification should change, or what to do during an event. Those decisions still require an engineer.
The change-tracking point is practical, too. When a regulator can show that they ran the screening in January and again in June, and that the June run identified 12 new addresses in a buffer zone, that creates a documented basis for action. It also creates a record that they were looking — which matters for governance.
What comes next
Future development includes on-demand inundation zone uploads and building data pulls with push notifications, automated real-time data refresh from NID, USGS alerts, satellite imagery, and planning databases, and identification of specific consequential infrastructure types — for example, hospitals and schools.
The consequential infrastructure piece is worth watching. A dam with 10 houses downstream is different from a dam with a hospital downstream, even if the address count is the same. Flagging those facilities specifically would add a prioritization layer that regulators currently maintain manually.
Is your downstream data current?
Geospatial downstream screening can improve emergency information access, hazard classification review, and prioritization at scale. It’s most practical for large dam portfolios, most valuable when outputs are easy to use, and works with engineering judgment.
If your program manages more than a few dozen dams and your downstream address lists haven’t been refreshed in the past year, that gap is compounding right now — quietly, one new building permit at a time.
Contact the Rezatec team below to scope a pilot for your dam portfolio