| NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
| Recipient: |
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| Initial Amendment Date: | September 21, 2023 |
| Latest Amendment Date: | September 21, 2023 |
| Award Number: | 2345641 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Daan Liang
dliang@nsf.gov (703)292-2441 CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
| Start Date: | October 1, 2023 |
| End Date: | September 30, 2024 (Estimated) |
| Total Intended Award Amount: | $50,000.00 |
| Total Awarded Amount to Date: | $50,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
2425 CAMPUS RD SINCLAIR RM 1 HONOLULU HI US 96822-2247 (808)956-7800 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
2540 Dole Street, Holmes 310 HONOLULU HI US 96822-2247 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
HDBE-Humans, Disasters, and th, Special Initiatives |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
This Grants for Rapid Response Research (RAPID) project collects ephemeral data to better understand the compounding impacts of Maui wildfires and Hurricane Dora and reveal the differences between residents and tourists in their behavioral responses as affected by infrastructure failures. It examines the sources of warning information, protective action decision-making, and evacuation logistics at the individual level. In the meantime, the project captures the operation states of disaster warning operations in Maui under the loss of cell and electric power services. Failures at each system are documented, as well as the cascading effect among inter-connected infrastructure systems. The research outcomes expand the existing body of scientific knowledge on warning and evacuation while advancing the understanding of informal networks and decision-making in the absence of official guidance.
The hurricane-fueled fast-moving Maui wildfire offers a unique research opportunity to explore the intricacies of decision-making in the absence of official warnings. This event has three unique characteristics. First, Maui has a large percentage of tourists who may exhibit different patterns in warning reception, protective action decision-making, and evacuation logistics. Second, none of the 80 warning sirens placed around the island were activated in response to the wildfire threat. Its absence, coupled with the loss of cell phone and power services, severely limited access to timely official warnings. Third, the cascading failures of critical infrastructure systems highlighted the interdependencies among them and the devastating consequences. This project collects and analyzes multi-dimensional data on heterogeneous behavioral responses by residents and tourists with varying degrees of warning information, as well as the ways in which these responses were affected by critical infrastructure failures (i.e., damages/disruptions to transportation, power, and communication network interoperability). The rich datasets not only bolster future digital twin-empowered applications but also contribute to the enhancement of emergency management in cyber and physical domains. In addition, the project engages and trains multiple Native Hawaiian students in data collection and analysis.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This project investigates human decision-making and the role of infrastructure during the rapid and devastating Maui wildfire, which was fueled by a hurricane in August 2023. The study is driven by three key factors: Maui’s significant tourist population, which may react differently to warnings and evacuation instructions; the failure to activate any of the island's 80 warning sirens; and widespread cell and power outages that severely limited access to official alerts. The research team analyzed data on residents' behavioral responses, focusing on varying levels of warning information and the impact of critical infrastructure failures, such as damage to transportation, power, and communication networks.
A survey of 660 survivors highlighted the catastrophic effects of these failures, with only 20% receiving warnings via telecommunications due to power and signal outages, 51% of them saw the wildfire coming, 24.5% saw others evacuated, 13% face-to-face warning from peers. Despite the lack of clear evacuation instructions, many participants displayed remarkable resourcefulness in determining evacuation routes, destinations, modes of transport, and preparation. However, that only 16.2% of people have a family emergency plan and 20% of respondents took more than 30 minutes to prepare for the evacuation indicates the gaps in preparedness level. While 75% of respondents evacuated by own vehicle, 13% of them evacuated by foot. 12% went to a public shelter, 25% went to a public place, 27% went to a relative's house, and 26% went to a friend's house.
The wildfire experience significantly influenced residents' risk perception, preparedness, and information-seeking behaviors. These findings provide valuable insights for improving disaster preparedness, response, and mitigation strategies. Additionally, the team developed an agent-based evacuation model using the collected data to evaluate and optimize warning systems and planning strategies, offering critical guidance for future emergency management policies.
Last Modified: 01/26/2025
Modified by: Guohui Zhang
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