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Flood Damage in the United States, 1926-2003
A Reanalysis of National Weather Service Estimates

3. Development of the Data Sets

The national data obtained from NWS consisted of annual total damage estimates for the U.S., including three territories: Puerto Rico (since 1975), the Virgin Islands (since mid-1980s), and Guam (since 1994). The state data contained annual damage estimates for each state and, in recent years, the three territories. In the national data, we subtracted estimates for the three territories from the U.S. totals to create a more uniform time series representing only the 50 states.

NWS estimates were spot-checked against those from other agencies. Estimates that appeared to be extremely large or small compared to published accounts of events were examined especially closely. In individual events that received follow-up study by the USACE, more accurate estimates were sometimes available. However, except during 1976-1982, there exists no compelling reason to change the NWS estimates or defer to another agency’s estimates. Section 5 provides a quantitative assessment of uncertainty in the estimates and the implications for their effective use.

With a few important exceptions, the estimates presented as a result of this project have their origins in published NWS data. Obvious clerical errors have been corrected (see Section 4).

A. Resolving the Data Gap, 1976-1982

To compile a complete time series of annual estimates required finding additional flood damage estimates for the years 1976-1982. As explained in Section 2, NWS ceased publication of annual flood damage summaries after 1975. Publication of comparable damage estimates did not resume until 1983, when USACE reports made damage estimates available again at the state and national levels, but not at the river basin level.

To make the state and national data sets as complete as possible, we focused on obtaining and evaluating estimates for 1976 through 1982. The NWS website (NWS-HIC 2001) included previously unpublished national flood damage estimates for 1976-1982, and an NWS spreadsheet included unpublished state estimates for that period. However, the national estimates and the state total estimates differed by large margins. An old, undocumented NWS computer printout tallied individual floods, by state, in the years 1976-1988, but we found it to be filled with errors and inconsistencies.

Despite a curtailment of effort, the NWS continued to compile some damage estimates during 1976-1979, which served as a starting point for our reconstruction attempts. We were able to develop estimates for 1976-1979 based on information in the NWS files and reports from other sources, as described in Appendix A.

Although we tried to reconstruct estimates for 1980-1982, there were not enough sources of information, either from NWS or other agency publications, to provide estimates for those years comparable to the data in the overall data set. Furthermore, there were some large disparities between estimates found in the NWS-HIC archives for the period 1980-1982 and damage estimates provided by states, leading us to conclude that some of the damage estimates for this time period are highly unreliable (see Section 5). Therefore, estimates for 1980-1982 are not included in the reanalyzed data sets, and we judge that data published by NWS for this period is of consistently lower quality than in other years.

A few general comments can be made about 1980-1982. Flood damage descriptions in Storm Data, which were sparse in previous years, became even rarer in 1980-1981. The information that does exist for the period suggests that 1980 and 1981 were extremely dry years in most parts of the country, so flood damage was probably small compared to other years (Wagner 1982, USGS 1991, notes in NWS files). On the other hand, descriptions in Storm Data suggest that flood damage rose to a higher level in 1982, perhaps close to the average level of that time.

B. Annual National Flood Damage Estimates (1926-1979, 1983-2000)

Since flood damage estimates for 1983 through 2000 are available only for fiscal years (October-September), it is desirable to compile the entire national flood damage data set using fiscal years. Fortunately, in its annual flood damage summary for 1975, Climatological Data National Summary (NWS 1977, vol. 13, p. 117) published national flood damage estimates by month for the years 1925 to 1975. Therefore, we were able to calculate national annual damage totals based on fiscal years for 1926-1979, creating a consistent form for the full national data set.

Table 3-1 shows annual damage estimates for the United States, by fiscal year, in millions of current dollars and in millions of inflation-adjusted 1995 dollars. The implicit price deflator used to adjust for inflation is also shown in the table.

C. Annual Flood Damage Estimates for the States (1955-1979, 1983-2000)

Annual damage estimates for each of the 50 states are given in Appendix B. The estimates for 1955 through 1975 are taken from Climatological Data National Summary (NWS 1977, vol. 13, p. 121), and are based on calendar years. Estimates for 1976-1979 are based on our reanalysis of available data (described above), and are presented by calendar year to be consistent with the earlier data. The estimates for 1983-2000 are taken from Army Corps of Engineers Annual Damage Report to Congress (1993, 2001), and are based on fiscal years (October-September).

D. Annual Flood Damage Estimates in River Basins (1933-1975)

The NWS and U.S. Weather Bureau compiled annual damage estimates by river basin from 1933 through 1975, publishing them first in the Monthly Weather Review (1933-1947) and later in Climatological Data National Summary (1948-1975). To make these estimates accessible to users, we organized them by large river drainages in a uniform format for the full time period.

Table 3-1. Estimated U.S. Flood Damage, by Fiscal Year (Oct-Sep).

Fiscal
Year
Damage
(Millions of Current Dollars)
Implicit
Price Deflator*
Damage
(Millions of 1995 Dollars)
1926 9.243
1927 315.187
1928 88.155
1929 61.700 0.12854 480
1930 25.832 0.12385 209
1931 2.070 0.11091 19
1932 10.365 0.09796 106
1933 27.366 0.09541 287
1934 18.903 0.10071 188
1935 123.327 0.10265 1,201
1936 287.137 0.10377 2,767
1937 433.339 0.10815 4,007
1938 108.970 0.10499 1,038
1939 13.861 0.10387 133
1940 40.067 0.10530 381
1941 26.092 0.11244 232
1942 91.548 0.12120 755
1943 220.553 0.12773 1,727
1944 99.789 0.13058 764
1945 159.251 0.13425 1,186
1946 68.930 0.15056 458
1947 281.321 0.16667 1,688
1948 213.716 0.17615 1,213
1949 108.586 0.17594 617
1950 129.903 0.17788 730
1951 1,076.687 0.19072 5,645
1952 254.190 0.19368 1,312
1953 121.752 0.19623 620
1954 74.170 0.19817 374
1955 784.672 0.20163 3,892
1956 305.573 0.20846 1,466
1957 352.145 0.21539 1,635
1958 224.939 0.22059 1,020
1959 121.281 0.22304 544
1960 111.168 0.22620 491
1961 147.680 0.22875 646
1962 86.574 0.23180 373
1963 179.496 0.23445 766
1964 194.512 0.23792 818
1965 1,221.903 0.24241 5,041
1966 116.645 0.24934 468
1967 291.823 0.25698 1,136
1968 443.251 0.26809 1,653
1969 889.135 0.28124 3,161
1970 173.803 0.29623 587
1971 323.427 0.31111 1,040
1972 4,442.992 0.32436 13,698
1973 1,805.284 0.34251 5,271
1974 692.832 0.37329 1,856
1975 1,348.834 0.40805 3,306
1976 1,054.790 0.43119 2,446
1977 988.350 0.45892 2,154
1978 1,028.970 0.49164 2,093
1979 3,626.030 0.53262 6,808
1980 0.58145
1981 0.63578
1982 0.67533
1983 3,693.572 0.70214 5,260
1984 3,540.770 0.72824 4,862
1985 379.303 0.75117 505
1986 5,939.994 0.76769 7,737
1987 1,442.349 0.79083 1,824
1988 214.297 0.81764 262
1989 1,080.814 0.84883 1,273
1990 1,636.366 0.88186 1,856
1991 1,698.765 0.91397 1,859
1992 672.635 0.93619 718
1993 16,364.710 0.95872 17,069
1994 1,120.149 0.97870 1,145
1995 5,110.714 1.00000 5,111
1996 6,121.753 1.01937 6,005
1997 8,934.923 1.03925 8,597
1998 2,465.048 1.05199 2,343
1999 5,450.375 1.06677 5,109
2000 1,336.744 1.09113 1,225

* Source: U.S. Bureau of Economic Analysis, 2001.
— Data unavailable, see text for discussion.

The basin-level damage estimates are available in spreadsheet form from our website. Estimates are presented by calendar year. The grouping of basins within drainages is somewhat different from that commonly used to define water resources regions (e.g., U.S. Dept. of Commerce, 1978 Census of Agriculture) because, over the years, the NWS sometimes changed its groupings. We developed uniform basin definitions for the full time period by using the following organizational system:

  1. Damages are grouped by drainage (e.g, St. Lawrence Drainage, Upper Mississippi, Great Basin) starting in the eastern part of the United States and moving towards the west coast, and then alphabetically by individual or grouped river basin(s).
  2. Often, the NWS grouped individual rivers together in annual summaries. For example, damage on the White and Wabash Rivers were usually included together as one estimate. If the published sources of flood data included damage for two river basins together in one year, then data for these two (or more) rivers were added together for all other years. This was the simplest way to produce a coherent data set that could be searched and produce just one row of data for one river basin.
  3. In many of the years, damage on unnamed streams was included. If the publication did not give a stream name, damage was included in a row for the drainage called "small streams."
  4. Sometimes the publications would include a river and its small tributaries together, by saying "X River and tributaries." When damage was published in this format, it was entered into the database under the river itself. So, damage listed for some rivers in some years may include not just the river, but its small tributaries (such as creeks).
  5. Creeks that were included separately in NWS publications from the rivers to which they are tributaries were entered into the database separately. Creeks can be differentiated from rivers in the database because they are labeled "Cr.," whereas rivers are entered with the river name only. An exception to this rule is for rivers with Spanish names, such as the Rio Hondo and Rio Grande. Since users may want to search for "Rio Hondo" rather than "Hondo," "Rio" is included in the database.
  6. Users looking for damage information on rivers with branches (such as North Platte, South Platte, and Platte) should look for each of these branches. In some cases, all of the branches of one stream are included together, and in some cases they are not.
  7. Several of the streams in the data set cross drainage boundaries. If there is a question about which drainage a stream is in, a user should look in both drainages.

E. Use of the Damage Estimates

Users of these data sets should be aware that there is uncertainty in the damage estimates, with a likelihood of large errors in some estimates. Types of inaccuracy are described in Section 4, and the magnitude of errors is analyzed in Section 5. In consideration of uncertainty, recommendations regarding appropriate uses of the data are offered in Sections 6 and 7.

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A report of the University Corporation for Atmospheric Research, supported by the National Science Foundation, the National Weather Service, and the National Oceanic and Atmospheric Administration, Office of Global Programs, pursuant to NOAA Award No. NA96GP0451 through a cooperative agreement. In partnership between the Environmental and Societal Impacts Group of the National Center for Atmospheric Research and the Center for Science and Technology Policy Research, Cooperative Institute for Research in Environmental Sciences, University of Colorado.

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A report of the University Corporation for Atmospheric Research, supported by the National Science Foundation, the National Weather Service, and the National Oceanic and Atmospheric Administration, Office of Global Programs, pursuant to NOAA Award No. NA96GP0451 through a cooperative agreement. In partnership between the Environmental and Societal Impacts Group of the National Center for Atmospheric Research and the Center for Science and Technology Policy Research, Cooperative Institute for Research in Environmental Sciences, University of Colorado.

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