The U.S. Geological Survey (USGS) is a participant in the International
Decade of Natural Disaster Reduction.
The 1990s are designated as the International Decade of Natural Disaster
Reduction, and the U.S. is a signatory to the United Nations' treaty. Studies
by USGS researchers contribute to this treaty by defining a quantitative
basis for developing models for the loss of life and property resulting
from natural disasters. This research is conducted cooperatively with Prof.
Sarah Tebbens of the University of South Florida, Prof. Donald Turcotte
of Cornell University, and Prof. Christopher Scholz of Columbia
University. Data from the USGS, the National Oceanic and Atmospheric
Administration (NOAA) and other agencies are used to develop an understanding
of how a particular natural disaster scales, or relates, to other disasters
caused by the same phenomenon, and to disasters caused by other phenomena.
These relationships are fundamental to the development and evaluation of
national disaster planning, mitigation, and hazard reduction efforts.
In this study, USGS scientists examine the magnitude of disasters as
measured by dollars and fatalities, as well as by traditional scientific
parameters.
Natural high-energy events, such as hurricanes and earthquakes, are
complex phenomena whose cumulative size-frequency distributions exhibit
scaling properties; that is, plots of logarithms of the size and cumulative
frequency data follow a straight line. The slope of this line is the scaling
exponent. Preliminary results of this research, funded by the USGS G.K.
Gilbert Fellowship Program, suggest that the loss of life and property
due to natural disasters exhibit self-similar scaling behavior. It is
this self-similar scaling property that allows use of frequent small events
to estimate the rate of occurrence of less frequent, larger events.
Examining the scaling behavior of loss data for disasters of all scales
has important advantages because one can forecast the probability of occurrence
of a disaster over a wide range of years (1 year to 1,000 years); compare
one type of disaster with another; compare disasters in one region with
similar disasters in another region; and, measure the effectiveness of
planning and mitigation strategies.
Above Charts A-B: (A)Property losses from hurricanes in the continental U.S. by decade. (B) Loss of life due to hurricanes in the continental U.S. by decade. (Data from NOAA). Property losses due to hurricanes have grown rapidly in this century and are expected to grow more rapidly in the future. Hurricane tracking and early-warning systems developed by NOAA have dramatically reduced the loss of life due to hurricanes but have had little effect on property loss. |
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Graphs(right): 106 years of storm data for Tampa Bay region, Florida provides the basis for establishing scaling laws for wind speed and time intervals between storms. The insight provided by a log-log plot of data is shown (above) for maximum wind speed (on left) and for time intervals between storms (on right). Traditionally, data are plotted on a histogram plot (A and D). Structure in the data becomes apparent when data are replotted on logarithmic scales where two populations become clear (B) and scaling is revealed (E). Axes on the plot are converted to probability in (C and F) which permits extrapolation to forecast the probability of greater wind speeds and time intervals between storms. (Data from NOAA). |
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