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USGS Flood Inundation Mapping Science

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Flood inundation mapping science
Loss estimation
Emerging technologies

Emerging technologies

The following technologies represent state-of-the-art tools, methodologies, and techniques that the USGS and our partners are researching and testing. Most of these techniques are experimental and not publicly available, but could significantly improve our ability to plan for and respond to flooding events in the future.

Real-time dynamic flood inundation mapping

Real-time dynamic flood inundation maps are created on-the-fly using real-time data gathered during flood events. Targeted modeling applications run flood simulations during the flooding event and produce maps.

Figure 9. This shows an example of an inundation map generated by an experimental, real-time dynamic flood inundation mapping application for a reach of the White River near Indianapolis, Ind. This automated application mines USGS streamgage and National Weather Service flood forecast data. During floods, the application automatically launches, runs a calibrated stream hydraulic model, and creates flood maps for current flood area and produces an advance flooding forecast for up to 5 days. Users can retrieve the maps, as well as monetary flood-loss estimates, through an online graphic user interface. This application is experimental and not publicly available.


In order to promote ongoing scientific studies in the Flood Inundation Mapping (FIM) Program, the USGS Water Mission Area provides small supplemental grants to ongoing or recently completed FIM projects to explore key questions to move flood inundation mapping science forward.

The intent of a ScienceFIM grant is not to make a map library or supplement a budget shortfall in an existing project, but to provide a little extra time to fully investigate and share the lessons learned from FIM projects. To that end, you must submit a short document at the end of your project discussing your investigation and results. The FIM Program will publish these documents in a yearly ScienceFIM report and share your experiences with the Flood Science Teams and our partners. This is your chance to do that "Oh, I wish I could have tested X to answer Y during that project" opportunity!

Any USGS Science Center with a current or recently completed FIM project is eligible. If you have any questions, please contact a Flood Science Team Leader or Marie Peppler, FIM Coordinator.


Flooding is a primary driver of riverine ecosystem, particularly floodplain functions like plant succession and diversity; nutrient availability, cycling, and flux; and aquatic and terrestrial animal habitat quantity and quality. USGS water and ecosystem scientists have developed geospatial tools to simulate flood extents and depths on floodplains (the fundamental science behind the FIM program), but these tools were missing an important ecosystem element: distribution of water velocities. Modeling water velocities over a floodplain is critical to understanding nutrient and sediment fluxes as well floodplain landscape features (such as wetlands and oxbow lakes) affect habitat. The EcoFIM pilot project seeks to fill in this gap.

The objective of the EcoFIM project is to develop USGS Flood Inundation Mapping (FIM) library resources for ecosystem studies. The pilot project will focus on a reach of the Maquoketa River flowing through Green Island, Iowa. The reach contains a U.S. Geological Survey (USGS) streamgage (Maquoketa River near Green Island, IA: station number 05418720. The Green Island study area is a 764 acre Wetlands Reserve Enhancement Program (WREP) easement on a damaged levee district area along the Maquoketa River. The Natural Resources Conservation Service (NRCS) restoration goals for this area include improving floodplain function, reducing future levee district repairs, and improving wildlife habitat along the Mississippi River flyway.

The EcoFIM pilot documentation assist the NRCS efforts by developing a review of influences of flood inundation on floodplain biodiversity (e.g., vegetation, fish and wildlife), biogeochemistry (e.g., nutrient cycling and flux), and ecosystem services (e.g., recreation, safe drinking water, nature viewing), and providing the types of data need to carry out Eco-FIM projects related to these topics. The EcoFIM project will also help decision makers develop map libraries that can inform No Adverse Impact (NAI) improvements to floodplain areas.


In addition to the traditional hydrologic, hydraulic and geospatial method of creating a flood-inundation map library, USGS is interested in developing and testing additional methods that can be used to make simpler, faster and less expensive maps. These maps will likely be of lower quality so it is necessary to quantify how they differ from traditional studies. With a suite of methods, communities can make informed choices to create map libraries that meet their operational and budget needs. Several methods are being documented and tested, including:

Coastal Inundation

Coastal Inundation modeling brings a new set of challenges to the program, as coastal areas are typically very complex hydrologic and hydraulic systems. Depending on the area of interest, these maps may have to consider sea-level rise or beach erosion. If the coastal area is near a river mouth, the riverine, estuarine, and ocean areas all need to be modeled together. The USGS is partnering with National Oceanographic and Atmospheric Administration (NOAA) coastal programs and forecast offices in this area of on-going study.

An example of coarse scale mapping for coastal zones is the Coastal Flood Loss Atlas for the Atlantic Coast:

Critical infrastructure analysis

For some communities, the motivation for creating a Flood Map Library is to evaluate the susceptibility of critical infrastructure to flood hazards. While flood map libraries can help identify areas and resources most at risk, it is often important to keep the details and location of priority infrastructure secure. The USGS is exploring pilot projects that are examining how flood risks can be evaluated and mapped while still maintaining the safety and privacy of the data.

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