BOX 1.2

Committee Charge

The committee will

  1. Examine the current methods of constructing FEMA flood maps and the relationship between the methods used to conduct a flood map study (detailed study, limited detailed study, automated approximate analysis, or redelineation of existing hazard information), the accuracy of the predicted flood elevations, and the accuracy of predicted flood inundation boundaries.

  2. Examine the economic impacts of inaccuracies in the flood elevations and floodplain delineations in relation to the risk class of the area being mapped (based on the value of development and number of inhabitants in the risk zone).

  3. Investigate the impact that various study components (i.e., variables) have on the mapping of flood inundation boundaries:

    1. Riverine flooding

      • The accuracy of digital terrain information

      • Hydrologic uncertainties in determining the flood discharge

      • Hydraulic uncertainties in converting the discharge into a floodwater surface elevation

    1. Coastal flooding

      • The accuracy of the digital terrain information

      • Uncertainties in the analysis of the coastal flood elevations

    1. Interconnected ponds (e.g., Florida)

      • The accuracy of the digital terrain information

      • Uncertainties in the analysis of flood elevations

  1. Provide recommendations for cost-effective improvements to FEMA’s flood study and mapping methods.

  2. Provide recommendations as to how the accuracy of FEMA flood maps can be better quantified and communicated.

  3. Provide recommendations on how to better manage the geospatial data produced by FEMA flood map studies and integrate these data with other national hydrologic information systems.

to the committee and by conducting case studies in North Carolina and Florida (see “Case Studies” below). The results of the first three tasks formed the basis for the recommendations in Tasks 4, 5, and 6.


Case studies were carried out to examine factors that affect riverine flood map accuracy and to assess the costs and benefits of more accurate flood maps. Most of the hydrologic, hydraulic, elevation, and economic analyses were carried out in collaboration with the North Carolina Floodplain Mapping Program. North Carolina was selected because flood maps developed using high-accuracy lidar data were available for nearly the entire state, enabling comparison of traditional and new data and techniques. The North Carolina studies focused on three physiographic regions, including the mountainous city of Asheville (Buncombe County), the rolling hills of Mecklenburg County, and the flat coastal plain of Pasquotank and Hertford Counties (Figure 1.2). Two coastal plain counties were analyzed because the most comprehensive development and insurance information needed for the benefit-cost analysis was available in Pasquotank County, but more comprehensive hydraulic information was available in Hertford County.

The committee used benefit-cost analyses to assess the economic impacts of inaccuracies in floodplain boundaries and flood elevations (Task 2). Such methods, which are used by FEMA for determining the benefits and costs of different mapping approaches, are based on measuring economic impacts, favorable and unfavorable, in monetary terms.4 The committee’s assessment relied on FEMA reports as well as a case study in Mecklenburg and Pasquotank Counties and the City of Asheville. The case study compared the costs of creating new digital flood maps with two result-


Benefit-cost analysis differs from economic impact analysis, which traces direct and indirect spending effects through the economy. For example, an economic impact analysis might trace the results of a prediction of a particular type of flood to the amount of damage. A direct effect of flooding is damage to the house, and indirect effects include fewer pizzas but more plywood purchased.

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement