Mapping the Zone: Improving Flood Map Accuracy (2009)

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1 Introduction F looding is the nation’s leading cause of disaster, ties and individuals understand and are insured against contributing to nearly two-thirds of all federal their true flood risk (e.g., Box 1.1). disasters and causing approximately $50 bil- lion in property damage in the 1990s (Downton et al., COMMITTEE CHARGE AND APPROACH 2005). Much of the damage occurs in floodplains—the low, relatively flat areas adjoining inland and coastal This report is the second undertaken by the waters, including areas subject to a 1 percent or greater National Academies to examine FEMA map modern- chance of flooding in any given year. A house in the ization. The first study, Elevation Data for Floodplain 1 percent annual chance (100-year) floodplain has a Mapping (NRC, 2007), assessed the data needed 26 percent chance of being damaged by flooding during to map floodplains. It concluded that the existing a 30-year mortgage, compared to a 9 percent chance of National Elevation Dataset (NED) is not sufficiently being damaged by fire. Insurance companies generally accurate to support accurate floodplain mapping and consider residential flooding too costly to insure because recommended that a program be established to col- floods can be widespread and cause catastrophic losses lect high-accuracy, high-resolution digital terrain data (Figure 1.1). The National Flood Insurance Program nationwide. This second report broadens the analysis (NFIP) was established in 1968 to slow increasing flood to other factors that affect flood map accuracy, assesses disaster relief costs by offering federal flood insurance the benefits and costs of more accurate flood maps, and to owners of property in floodplains, provided their suggests ways to improve flood mapping, risk com- communities regulate new development in these areas munication, and management of flood-related data (FEMA, 2002). The premium that property owners pay (Box 1.2). is related to their risk of flooding, which is determined This study was initially requested by managers of by the location of their property on Flood Insurance FEMA’s Risk Analysis Division, and managers from Rate Maps (FIRMs; hereafter called flood maps) pro- the National Oceanic and Atmospheric Administra- duced by the Federal Emergency Management Agency tion’s (NOAA’s) Coastal Services Center later added (FEMA). The accuracy of floodplain boundaries drawn their support. Of particular interest to NOAA are on these maps directly determines how well communi- the accuracy of geodetic data, which are relied on for all types of flood studies; the accuracy of bathymetric Of the 1,720 federal disasters declared from 1953 to 2007, flood- data, which are needed for storm surge modeling; and ing contributed to 1,100 disasters, severe storms to 984 disasters, the usefulness of integrating NOAA inundation map and fire to 845 disasters. See <http://www.fema.gov/news/disasters. libraries into a national map system. fema>. Presidential Executive Order 11988. The committee addressed Tasks 1, 2, and 3 by gath- See <http://www.floodsmart.gov/floodsmart/pages/flood_facts. ering information from the literature and presentations jsp>.  

 MAPPING THE ZONE FIGURE 1.1  Flooding in downtown Cedar Rapids, Iowa, June 13, 2008. Floodwaters inundated about 100 city blocks, including May’s Island, where City Hall and the courthouse sit. SOURCE: Stephen Mally. Used with permission. Figure 1-1.eps bitmap image BOX 1.1  Flooding in Conklin, New York, June 28, 2006 Improving the accuracy of maps can change the floodplain boundary and, thus, which properties are designated within the floodplain. Landowners often seek to avoid this designation,a which can have the effect of increasing insurance premiums, reducing property values, restricting development, and/or requiring costly mitigation efforts, such as raising the elevation of structures. At the same time, home and business owners have a strong financial interest in having their structures properly insured against flood damage. Residents of communities that are not in mapped 100-year floodplains often have no idea they are vulnerable to property losses until they are inundated. Yet one-third of flood insurance claims are for areas beyond the 100-year floodplain.b For example, the largest flood recorded in the Binghamton, New York, area extended beyond the 100-year floodplain to areas where flood insurance is not required, catching residents of the Conklin community off guard. As reported in the Press & Sun-Bulletin:c When Abby Mack moved into her home on Grandview Avenue in Conklin four years ago, her bank told her she didn’t need flood insurance. A check of information-based flood maps—which officials rely on to predict the frequency and impact of floods—shows her home is above the flood plain. But as the Susquehanna River continued to rise through the twilight hours of June 28, it became clear that her home and others on her street were threatened. Police evacuated bewildered residents shortly before the river began creeping up their tidy lawns and driveways and pouring into basements. . . . The Mack residence, which lost a hot water heater, other major appliances and carpeting, fared relatively well. The damage was much more extensive just down the street and in other places in Conklin that, according to the maps, shouldn’t have been touched by the flood. . . . “The whole flood plain has to be studied and re-evaluated,” said Debbie Preston, supervisor of the Town of Conklin, where the recent flood ruined hundreds of properties and forced the evacuation of the entire town. _______ aPresentation to the committee by Patty Templeton Jones, Flood Committee of the Institute for Business and Home Safety, on November 8, 2007. bSee <http://www.floodsmart.gov/floodsmart/pages/flood_facts.jsp>. cT. Wilber, 2006, Floods 2006—Are Tier flood maps wrong? Press & Sun-Bulletin, July 9. 

INTRODUCTION  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: a. 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 b. Coastal flooding • The accuracy of the digital terrain information • Uncertainties in the analysis of the coastal flood elevations c. Interconnected ponds (e.g., Florida) • The accuracy of the digital terrain information • Uncertainties in the analysis of flood elevations 4. Provide recommendations for cost-effective improvements to FEMA’s flood study and mapping methods. 5. Provide recommendations as to how the accuracy of FEMA flood maps can be better quantified and communicated. 6. 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 because the most comprehensive development and North Carolina and Florida (see “Case Studies” below). insurance information needed for the benefit-cost The results of the first three tasks formed the basis for analysis was available in Pasquotank County, but more the recommendations in Tasks 4, 5, and 6. comprehensive hydraulic information was available in Hertford County. CASE STUDIES The committee used benefit-cost analyses to assess the economic impacts of inaccuracies in flood- Case studies were carried out to examine factors plain boundaries and flood elevations (Task 2). Such that affect riverine flood map accuracy and to assess the m ­ ethods, which are used by FEMA for determining costs and benefits of more accurate flood maps. Most the benefits and costs of different mapping approaches, of the hydrologic, hydraulic, elevation, and economic are based on measuring economic impacts, favorable analyses were carried out in collaboration with the and unfavorable, in monetary terms. The committee’s North Carolina Floodplain Mapping Program. North assessment relied on FEMA reports as well as a case Carolina was selected because flood maps developed study in Mecklenburg and Pasquotank Counties and using high-accuracy lidar data were available for nearly the City of Asheville. The case study compared the the entire state, enabling comparison of traditional and costs of creating new digital flood maps with two result- new data and techniques. The North Carolina studies focused on three physiographic regions, including the Benefit-cost analysis differs from economic impact analysis, mountainous city of Asheville (Buncombe County), which traces direct and indirect spending effects through the the rolling hills of Mecklenburg County, and the flat economy. For example, an economic impact analysis might trace the coastal plain of Pasquotank and Hertford Counties 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 (Figure 1.2). Two coastal plain counties were analyzed indirect effects include fewer pizzas but more plywood purchased. 

10 MAPPING THE ZONE FIGURE 1.2  Physiographic provinces and location of counties studied in North Carolina. Hydrologic, hydraulic, and elevation data were analyzed in Buncombe, Mecklenburg, and Hertford Counties; benefits and costs were assessed in Buncombe, Mecklenburg, and Pasquotank Counties. SOURCE: North Carolina Floodplain Mapping Program. Used with permission. Figure 1-2.eps bitmap image ing benefits: avoided flood losses for new buildings from either incomplete understanding of events and and avoided repairs to infrastructure through accurate processes or a lack of data, and they can be reduced floodplain delineation and setting flood insurance with additional information. Knowledge uncertainty premiums to better match estimates of actual risk. The associated with riverine flooding (Task 3a) was exam- assumption was that if the benefit-cost ratio was greater ined through flood modeling and mapping case studies than 1, even when only a subset of benefits was con- in Mecklenburg and Hertford Counties and the City sidered, society would gain by improving map accuracy. of Asheville. Natural variability was quantified through The analysis was based on a comparison of buildings the analysis of flood frequency from recorded annual designated as either in or out of the floodplain under maximum flood flows and stages at 21 USGS stream different mapping approaches. gages in the case study areas and other portions of The importance of accurate elevation data (Task 3) the coastal plain of North Carolina. The NRC (2000) was evaluated by comparing maps made using the report examined uncertainties in discharge, water sur- U.S. Geological Survey (USGS) National Elevation face elevation, and economic damage, and concluded Dataset and lidar. For the hydrology and hydraulics that mathematical flaws in the formal uncertainty analysis (Task 3), the committee followed the National analysis method preclude determining the precision of Research Council (NRC, 2000) report by distinguish- the uncertainty estimates. Consequently, the commit- ing two sources of uncertainty: natural variability and tee did not attempt a formal uncertainty analysis, in knowledge uncertainty. The inherent variability of which uncertainties from various sources are combined nature leads to uncertainty that can never be elimi- mathematically to determine the total uncertainty in nated. For example, the magnitude of future floods flood map variables. cannot be forecast precisely, no matter how much time, Shallow flood frequency (Task 3c) was analyzed effort, or money is invested in flood modeling and using data from 10 USGS stream gages in southwest mapping. In contrast, knowledge uncertainties arise Florida, an area subject to shallow flooding associated 

INTRODUCTION 11 with interconnected ponds. However, comprehensive mation. Chapter 2 describes how FEMA Flood Insur- case studies to quantify factors that affect the accuracy ance Rate Maps are created, maintained, and used for of coastal and interconnected pond maps (Tasks 3b and insurance, regulatory, and other purposes. Chapter 3 3c) were not practical because capabilities to model examines the importance of elevation data in flood map coastal and shallow flood processes are rapidly evolv- accuracy and describes how land and water surfaces are ing. In contrast, methods for riverine flood mapping defined relative to geodetic datums. Chapters 4 and 5 are more mature and well established. Consequently, analyze factors that affect the accuracy of flood map- the committee simply outlined the accuracy and ping of inland and coastal regions. Chapter 6 assesses uncertainty associated with coastal flooding and inter­ the economic benefits of more accurate flood maps. connected ponds. Chapter 7 discusses ways to communicate flood hazard and risk. Methods used to estimate base flood eleva- ORGANIZATION OF THE REPORT tions are summarized in Appendix A. Biographical sketches of committee members (Appendix B), a glos- This report examines FEMA’s mapping methods sary of commonly used terms (Appendix C), and a list and recommends ways to improve flood map accuracy of acronyms and abbreviations (Appendix D) appear at and to communicate and manage flood-related infor- the end of the report.