The 3D Elevation Program—Flood risk management

Flood-damage reduction in the United States has been a longstanding but elusive societal goal. The national strategy for reducing flood damage has shifted over recent decades from a focus on construction of flood-control dams and levee systems to a three-pronged strategy to (1) improve the design and operation of such structures, (2) provide more accurate and accessible flood forecasting, and (3) shift the Federal Emergency Management Agency (FEMA) National Flood Insurance Program to a more balanced, less costly flood-insurance paradigm. Expanding the availability and use of high-quality, three-dimensional (3D) elevation information derived from modern light detection and ranging (lidar) technologies to provide essential terrain data poses a singular opportunity to dramatically enhance the effectiveness of all three components of this strategy. Additionally, FEMA, the National Weather Service, and the U.S. Geological Survey (USGS) have developed tools and joint program activities to support the national strategy.

The USGS 3D Elevation Program (3DEP) has the programmatic infrastructure to produce and provide essential terrain data. This infrastructure includes (1) data acquisition partnerships that leverage funding and reduce duplicative efforts, (2) contracts with experienced private mapping firms that ensure acquisition of consistent, low-cost 3D elevation data, and (3) the technical expertise, standards, and specifications required for consistent, edge-to-edge utility across multiple collection platforms and public access unfettered by individual database designs and limitations.

High-quality elevation data, like that collected through 3DEP, are invaluable for assessing and documenting flood risk and communicating detailed information to both responders and planners alike. Multiple flood-mapping programs make use of USGS streamflow and 3DEP data. Flood insurance rate maps, flood documentation studies, and flood-inundation map libraries are products of these programs.