In addition to reeking havoc, natural disasters have starkly illustrated the inadequacy of pre- and post-disaster planning and action by the United States government. In 1992, Hurricane Andrew devastated portions of southern Florida, causing the Federal Emergency Management Agency (FEMA) to receive harsh criticism for not better predicting the extent of the damage. Congress determined that the reliance on computer models could have drastically improved the scale of response to Hurricane Andrew and in the future these systems would provide the necessary information to best prepare for and react to natural disasters across the nation.
The criticism propelled FEMA to perfect the development of the Consequence Assessment Tool Set (CATS), which had been in the works within the agency for several years. CATS is an adaptation of a computer modeling and monitoring tool developed by FEMA with the Defense Department to deal with nuclear disasters, which FEMA expanded to address natural disasters as well. FEMA utilizes CATS to provide Federal, state, and local emergency managers with an accurate, unified description of an impending or recent disaster, so they can make well-informed decisions that result in the delivery of fast, effective, efficient, and fair services to victims.
CATS incorporates the models of physical effects, diverse digitized databases (demographics, resources, and infrastructure), remote sensing information, modern communications systems, and Geographic Information Systems (GIS) to serve all phases of emergency management for various hazards. In the preparedness phase, emergency managers at all levels are trained using realistic CATS-generated scenarios geared to their community, so that they can provide a better, more integrated response when the emergency does occur. CATS model projections are used in the mitigation phase to identify and prioritize key emergency disaster-relief resources, such as bridges and hospitals, so that efforts are focused on protecting them, maximizing coping capability following the disaster. CATS also uses model estimates to identify the scale of the disaster during the response phase so resources are appropriately distributed to service disaster victims. For long lead time disasters, such as hurricanes, this identification can be performed pre-disaster, allowing resources to move into place even before the disaster strikes. In the recovery phase, essential infrastructure needed for disaster relief such as hospitals, airports and roads are categorized first by the CATS model then by the CATS coordinated remote sensing activities as usable or unusable for the emergency support function. Any additional vital resources that are needed can then be moved into the disaster zone as quickly as possible.
One of the most important potential advantages of accurate damage predictions is to encourage evacuation. In the past, officials have often had to advise residents to get out of harm's way based only on potential hurricane storm surge. Now local officials can advise evacuation based on a detailed prediction of storm surge and wind damage. Using CATS computer-mapping technology, officials can paint a vivid picture of what a decision to stay might really mean.
The predictive ability of CATS has proven itself to be impressively accurate, impacting disaster relief procedures across the United States. After the Northridge earthquake, FEMA calculated that 560,000 households would be affected; the agency received 600,000 applications for help. In 1995, FEMA predicted that Hurricane Marilyn would damage 5,100 households in the Virgin Islands; 5,300 applied for assistance. When Hurricane Eduardo was rumbling toward the U.S. coastline in the summer of 1996, FEMA accurately identified areas of potential water contamination and quickly moved fresh-water supplies to those sites ahead of the storm. Since U.S. population growth is greatest in high-risk areas, such as the coasts and earthquake prone zones, CATS will undoubtedly continue to play an integral role in disaster mitigation and effective emergency response for years to come.