HR: 1340h
AN: PA23A-1446    [Abstracts]
TI: Applications of the Time-Varying Multi-Hazard Index to Armed Conflicts and GDP Growth Rate
AU: * Isanuk, M
EM: mji2101@columbia.edu
AF: Columbia University, 2960 Broadway, New York, NY 10027 United States
AU: Skorik, A
EM: acs2031@columbia.edu
AF: Columbia University, 2960 Broadway, New York, NY 10027 United States
AU: Lerner-Lam, A
EM: lerner@ldeo.columbia.edu
AF: Lamont-Doherty Earth Observatory, 61 Route 9W, Palisades, NY 10964 United States
AB: The time-varying Multi-Hazard Index has many potential applications for comparisons against quantitative measures of sustainable development. We have compared the time-varying severity of multiple natural hazards against time-varying socio-economic data for selected countries. Our analysis compares Gross Domestic Product (GDP) growth and armed conflict occurrence against multiple hazard severity as measured by an empirical time-varying multiple hazard index. The purpose of these analyses is to establish and characterize correlations between the Multi-Hazard Index and trends in GDP and conflicts over the past 25 years. To analyze the relationship between natural hazards and armed conflicts, the Multi-Hazard Index was correlated against the number of conflicts at each intensity level for individual countries. A preliminary analysis was performed studying the apparent relationship as well as the possible existence of time lags. In a similar although more quantitative analysis, the GDP data was correlated against the Multi-Hazard Index for a particular country at different time lags. Analysis involving the conflict datasets yielded varying results from country to country. Colombia shows the strongest correlation, with all positive values of the Multi-Hazard Index followed by an escalation in conflict intensity. The results for other countries are more difficult to interpret as certain years show increases in the number of conflicts at one intensity level and a decrease for other intensity levels. Some issues that need to be addressed include the coding of the intensity for the conflict data, the dating for both conflicts and hazards, and the use of national boundaries as geographic extents. The degree of correlation between GDP growth and the Multi-Hazard Index varies from country to country as well. Our calculations for Honduras show an extremely high correlation, for example, implying a strong economic sensitivity to natural hazards, whereas for China no significant correlation was discernible. The low degree of correlation in China suggests that geographic scale plays an important role in determining hazard impacts: the national level GDP data may obscure the economic impacts of natural hazards on specific provinces and economic sectors, which contribute differently to the national GDP. We suggest an approach using sector-specific economic data for China that is disaggregated at the provincial scale.
DE: 6699 General or miscellaneous
SC: Public Affairs [PA]
MN: 2004 AGU Fall Meeting