Rapid Inland Flood Situational Awareness Using Forecasted Precipitation Data

Inland flooding can be a major contributor to damage during a hurricane. As is well known, tropical cyclone events with relatively slow forward speed or that stall in near-coastal environments, such as Hurricane Florence and Hurricane Harvey, have the potential to unleash vast amounts of precipitation over short periods of time. The result is the potential for widespread flash flooding and flooding covering large geographic areas, larger than typical inland flood events that may be a result of convective-type events. Predicting the extent of flooding from these events can be a complex meteorological, hydrologic, and hydraulic challenge, but computational models that can provide estimates of flooding (e.g., timing, extent, depth) can greatly enhance the situational awareness for decision makers at the Federal, State, and local level, including first responders. During hurricane Florence, the Rapid Infrastructure Flood Tool (RIFT) was used to develop daily estimates of flooding over a wide geographic area, from Northern Virginia to South Carolina. RIFT is a two-dimensional hydrodynamic model that is forced by precipitation forecasts, such as the National Weather Service Quantitative Precipitation Forecast. RIFT provided estimates of maximum potential for flooding and duration of flooding over the wide geographic area and these results communicated to Federal stakeholders, in addition to state and local emergency operation centers. This talk will discuss the response process to provide rapid situational awareness, a description of the demonstrated use cases (e.g., rescue, evacuation, resource allocation) of rapid flood information in the immediacy of the event, lessons learned in communicating flood information, and post-event model verification and validation.