Modeling Downward Counterfactual Events: Unrealized Disasters and why they Matter

Disaster risk research’s reliance on past events has proved inadequate when it comes to extreme events. This shortcoming stems from limited records (for example, due to the vast differences in timescales between geological processes and human records) and the dynamic nature of all three components of risk–drivers of change in hazard (e.g., climate change), exposure (e.g., urban growth), and vulnerability (e.g., aging infrastructure). This paper provides a framework for modeling key unrealized events through downward counterfactual changes for consideration in future risk modeling and assessment. Past disasters are typically viewed as fixed events, and the resulting lessons-learned are inherently limited by this definition; downward counterfactual thought provides a means to harvest additional insights and capture a larger consequence space. As such, we have identified a need for a guiding framework in order to incorporate downward counterfactual thought in the context of disaster risk modeling applied to both natural and anthropogenic hazards. The downward counterfactual framework relies first on identifying a past event, which may or may not have been considered a major disaster. After an event has been identified, historical parameters from the past event are relaxed in order to identify small changes that result in downward, worsening consequences. This can be continued for multiple changes until an end-of-search criteria is reached. The framework is especially relevant for regions that may have a sparse past catalog, either due to limited data or limited occurrences of natural hazards. As such, the framework is demonstrated in the context of Singapore, a city-nation that has historically had limited recorded natural hazards events, through five case studies on past anthropogenic, environmental, seismic, volcanic, and storm hazard events. This framework can help harness lessons-learned from unrealized disasters to support a more resilient future through informed policies and plans.

Abstract licence: CC BY

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