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.

在极端事件方面，灾难风险研究对过去事件的依赖已被证明是不足的。这种缺陷源于有限的记录（例如，由于地质过程和人类记录之间时间尺度的巨大差异）以及风险的所有三个组成部分的动态性质，即风险变化（例如气候变化），暴露（例如，城市增长）和脆弱性（例如基础设施老化）。本文提供了一个框架，用于通过向下的反事实变化来建模关键未实现事件，以供将来进行风险建模和评估时考虑。过去的灾难通常被视为固定事件，因此，所学到的教训本质上受到此定义的限制；向下的反事实思维提供了一种手段，可以收集更多的见解并获得更大的后果空间。因此，我们已经确定了一个指导框架的必要性，以便在适用于自然灾害和人为灾害的灾害风险建模的背景下纳入向下的反事实思想。向下的反事实框架首先依赖于确定过去的事件，该事件可能会或可能不会被视为重大灾难。在确定事件之后，放宽过去事件的历史参数，以识别导致向下恶化后果的细微变化。可以继续进行多次更改，直到达到搜索结束条件为止。该框架特别适用于可能由于数据有限或自然灾害发生率有限而过去目录稀少的地区。因此，该框架是在新加坡的背景下展示的，通过对过去的人为，环境，地震，火山和暴风雨灾害事件进行的五个案例研究，一个历史悠久的自然灾害事件受到限制的城市国家。该框架可以帮助利用从未实现的灾难中学到的经验教训，通过知情的政策和计划来支持更具弹性的未来。