Using Existing Indicators to Bridge the Exposure Data Gap: A Novel Natural Hazard Assessment.
Adam K Williams1, James K Summers2, Linda C Harwell2
1Oak Ridge Associated Universities, 1 Sabine Island Drive, Gulf Breeze, FL 32561, USA.
Sustainability
|April 11, 2025
Summary
Extreme natural hazard events are increasing, necessitating climate resilience research. A new method simplifies calculating natural hazard exposure, improving data integration for climate change and resiliency studies.
Area of Science:
- Environmental science
- Climate science
- Risk assessment
Background:
- Extreme natural hazard events are increasing globally, driving the need for climate resilience research.
- Assessing climate change and natural hazard resiliency often involves complex methodologies to understand cumulative impacts.
- Indicator frameworks, like the Climate Resilience Screening Index (CRSI), help parse complex data but are limited by data availability.
Purpose of the Study:
- To develop a simplified methodology for quantifying natural hazard exposure.
- To facilitate the integration of natural hazard exposure data into climate resilience research and indices.
- To address limitations in data availability and computational burden associated with traditional methods.
Main Methods:
- Utilized data from the Federal Emergency Management Agency's (FEMA) National Risk Index (NRI).
- Disaggregated NRI data to obtain underlying metrics of natural hazard exposure.
- Created a new composite value representing the spatial extent of natural hazard events, bypassing complex computations.
Main Results:
- A novel methodology was established to represent natural hazard exposure using spatial extent data.
- This approach alleviates the need for extensive computation typically required for quantifying hazard exposure.
- The new method allows for more efficient integration of exposure data into resilience assessments.
Conclusions:
- The developed methodology offers a streamlined approach to assessing natural hazard exposure.
- This simplification enhances the usability of exposure data in climate resilience research and indicator development.
- Improved data integration can lead to more effective strategies for addressing climate change impacts.
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