A robust model for disaster risk and decision analysis.

摘要

There are many types of disasters, and it is a challenge to derive a single model of disaster risk and decision analysis that encompasses them all. At the same time, a general model for analyzing disaster risks and decisions could make the tasks of disaster avoidance, prevention, mitigation, rescue, rebuilding, and recovery much easier. This dissertation formulates a model of risk and decision analysis concerned with behaviors (decisions or "objectives") and stimuli (initial "risks and uncertainties" and their associated sets of choices/utilities/"levers") that are chronicled and calibrated by "metrics." Changes in this model are displayed as changes in preferences over time or as conditioned by prior choices. In practice, this dynamic model of risk and decision analysis is usually represented as one or a set of static "time slices" from the model that serve as exemplars for the policy implications the specific, practical analysis is attempting to highlight.;This dissertation showcases some specific, practical analyses---six case studies---whose underlying model is derived from this general model. Each case makes its own points about policy implications related to its specific disaster type and circumstances while, at the same time, each demonstrates the robustness and flexibility of the more general model. Each case employs qualities of a robust model as follows: 1. It outlines the essential elements and relationships in the disaster process being considered, 2. It establishes a set of data that describes and measures the disaster process being considered, 3. It offers opportunities for comparison to actual or hypothetical disasters, 4. It acts as a template to better understand and help prevent recurrences of past disasters, to react and respond to and recover from unfolding disasters, and to plan for and mitigate future disasters, and 5. It serves as a tool to communicate the risks and potential consequences of the disaster being considered and the actions necessary to mitigate its risk.