Brian Blanton (RENCI), Rick Luettich (UNC), Peter Vickery (Applied Research Associates/IntraRisk), Jeff Hanson (US Army Crops of Engineers), Kevin Slover (Dewberry & Davis), Tom Langan (NC Floodplain Mapping Program), Technical Report TR-12-03, North Carolina Floodplan Mapping Program Intermediate Submission Number Three Report on Production Simulations and Statistical Analyses, Renaissance Computing Institute, 2012.
As part of the State of North Carolina Department of Emergency Management Floodplain Modernization Program, a partnership was assembled to develop a state-of-the-art system to compute surge water levels and waves along the North Carolina coastal region waters. Experts in the fields of coastal storm surge, hurricane and extra-tropical winds, wind-driven waves, geospatial information systems (GIS), and high-performance computational systems have worked together in this effort to further advance North Carolina’s leading role in flood analysis and mapping. The Renaissance Computing Institute (RENCI), the Institute of Marine Sciences (IMS), Applied Research Associates, the US Army Corps of Engineers, and Dewberry have worked together to complete the production simulation and statistical analysis phase of the project.
In previous phases of this FEMA Flood Insurance Study (FIS), comprehensive inputs to the overall system have been developed (seamless DEM, high-resolution ADCIRC grid, validation studies, and hurricane climate representation via JPM) and described in previous Submittal documents. Submittal One was approved by FEMA March 23, 2009, Submittal Two received conditional approval from FEMA on November 1, 2010 and final responses to comments on Submittal Two were provided to FEMA on September 8, 2011. In Submittal Three, we describe the various aspects of the production phase of the project, in which the probabilistic hurricanes and historical extratropical storms are used to drive the comprehensive modeling system to determine the surge and wave hazard levels at specified return periods. While this is a computationally intensive process, the bulk of the work leading up to this phase is critical to ensure that this phase is as robust and efficient as possible. The production phase of this project is where prior work comes together into a statistical dataset that will subsequently be used in the mapping phase of the FIS.