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Abstract An integrated storm surge modeling and traffic analysis were conducted in this study to assess the effectiveness of hurricane evacuations through a case study of Hurricane Irma. The Category 5 hurricane in 2017 caused a record evacuation with an estimated 6.8 million people relocating statewide in Florida. The Advanced Circulation (ADCIRC) model was applied to simulate storm tides during the hurricane event. Model validations indicated that simulated pressures, winds, and storm surge compared well with observations. Model simulated storm tides and winds were used to estimate the area affected by Hurricane Irma. Results showed that the storm surge and strong wind mainly affected coastal counties in south-west Florida. Only moderate storm tides (maximum about 2.5 m) and maximum wind speed about 115 mph were shown in both model simulations and Federal Emergency Management Agency (FEMA) post-hurricane assessment near the area of hurricane landfall. Storm surges did not rise to the 100-year flood elevation level. The maximum wind was much below the design wind speed of 150–170 mph (Category 5) as defined in Florida Building Code (FBC) for south Florida coastal areas. Compared with the total population of about 2.25 million in the six coastal counties affected by storm surge and Category 1–3 wind, the statewide evacuation of approximately 6.8 million people was found to be an over-evacuation due mainly to the uncertainty of hurricane path, which shifted from south-east to south-west Florida. The uncertainty of hurricane tracks made it difficult to predict the appropriate storm surge inundation zone for evacuation. Traffic data were used to analyze the evacuation traffic patterns. In south-east Florida, evacuation traffic started 4 days before the hurricane’s arrival. However, the hurricane path shifted and eventually landed in south-west Florida, which caused a high level of evacuation traffic in south-west Florida. Over-evacuation caused Evacuation Traffic Index ( ETI ) to increase to 200% above normal conditions in some sections of highways, which reduced the effectiveness of evacuation. Results from this study show that evacuation efficiency can be improved in the future by more accurate hurricane forecasting, better public awareness of real-time storm surge and wind as well as integrated storm surge and evacuation modeling for quick response to the uncertainty of hurricane forecasting.
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Assessment of Hurricane Irma Impacts on South Florida Seagrass Communities Using Long-Term Monitoring Programs
Hurricanes are some of the largest environmental drivers of change in coastal systems. We investigated the impacts of Hurricane Irma on benthic macrophyte communities in Florida Bay (FB) and the Florida Keys National Marine Sanctuary (FKNMS), USA. Spatiotemporal analyses were performed at multiple hierarchical levels (site, zone, region) to identify potential changes in the Braun-Blanquet (BB) densities of total seagrass (TSG) and total calcareous green macroalgae (TCAL) post-disturbance and to determine whether changes were attributable to hurricane impacts or normal seasonal and inter-annual variability. There were significant decreases in TSG in one of five zones in FKNMS and in one of six zones in FB, but no change in TCAL was recorded in either system. TSG in the Lower Keys Bayside declined from a mean BB score of 2.6 to 1.2, resulting from storm-induced erosion, whereas TSG in coastal FB declined from 1.05–2.4 to 0.36–2.0, likely due to prolonged hyposalinity and low dissolved oxygen following stormwater drainage. Overall, impacts to South Florida benthic macrophyte communities from Hurricane Irma were not catastrophic and were limited in spatial extent. Our results suggest that coastal areas hit by a storm with heavy winds are more likely to sustain direct physical impacts to the benthos, whereas estuarine areas with longer residence times are more at risk of the indirect effects of stormwater runoff and retention. Our analyses placed putative hurricane impacts within the context of recent variability and historical system baselines through the use of long-term monitoring data coordinated by multiple governmental and academic entities.
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- PAR ID:
- 10122387
- Date Published:
- Journal Name:
- Estuaries and Coasts
- ISSN:
- 1559-2723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1007/s12237-019-00623-0
