Jeremy David Bricker

Essential services are necessary for individuals to recover from and adapt to disruptive events, yet the relationship between access to such services and recovery trajectory is poorly understood. Data on household recovery times are typically only available through surveys, which are limited in scale and scope. Further, the availability of all open and accessible essential services facilities in a region may not be recorded anywhere. Location‐based services (LBS) data from cell phones offers new opportunities for estimating this relationship. Using LBS data, we approximate facility availability and household recovery times following Hurricane Irma in Southwest Florida in 2017 and then statistically model the importance of access for recovery incorporating social vulnerability, local storm parameters, and infrastructure outage variables. We show that power, cell service, and school outages rank highest in importance, followed by measures of access to essential services. These results underscore the importance of including access metrics for predicting community recovery and evaluating resilience as well as the need for planning and policies that improve access to essential services both in times of stability and disruption.

Experiences from Hurricane Katrina and the Tohoku Tsunami illustrate that elevated coastal roads and railroads can be effective countermeasures to coastal flood inundation and damage. In Mississippi, a railroad embankment was reported to have limited the extent of inundation, while an at-grade coastal highway did not. In Tohoku, Japan, elevated coastal highways strongly reduced the extent of the inundation zone. A simple analysis shows that the additional expenditure required to elevate the coastal highway in Mississippi is less than 1% of the direct damages caused in the state by Hurricane Katrina, illustrating the economic benefit of elevating coastal roads as multifunctional flood defences.

Appropriate management of coastal flood risk is critical for creating resilient communities. An important part of this is estimating what buildings will become uninhabitable due to a flood event such as a tropical cyclone. To increase the accuracy of these estimations, habitability functions are developed to quantify the relationship between hydrodynamic hazards and the probability of a building becoming uninhabitable following Hurricane Irma. Hazards like maximum flood depths are determined by modeling Hurricane Irma flooding in Delft3D-FM coupled with the wave model SWAN. These modeled hazard levels are then extracted at building locations where Location Based Services (LBS) data provide information on buildings that were uninhabitable following Hurricane Irma. The developed habitability functions provide valuable insights into how different hydrodynamic parameters and regression models perform for estimating building habitability, where maximum depth is generally the best predictor of habitability. Furthermore, we find that while wooden structure habitability is significantly influenced by hazard level, concrete structure habitability is not. These findings provide novel methods for estimating coastal flooding induced building uninhabitability, enhancing how planners can prepare for floods.

Appropriate management of coastal flood risk is critical for creating resilient communities. An important part of this is estimating what buildings will become uninhabitable due to a flood event such as a tropical cyclone. To increase the accuracy of these estimations, habitability functions are developed to quantify the relationship between hydrodynamic hazards and the probability of a building becoming uninhabitable following Hurricane Irma. Hazards like maximum flood depths are determined by modeling Hurricane Irma flooding in Delft3D-FM coupled with the wave model SWAN. These modeled hazard levels are then extracted at building locations where Location Based Services (LBS) data provide information on buildings that were uninhabitable following Hurricane Irma. The developed habitability functions provide valuable insights into how different hydrodynamic parameters and regression models perform for estimating building habitability, where maximum depth is generally the best predictor of habitability. Furthermore, we find that while wooden structure habitability is significantly influenced by hazard level, concrete structure habitability is not. These findings provide novel methods for estimating coastal flooding induced building uninhabitability, enhancing how planners can prepare for floods.

Appropriate management of coastal flood risk is critical for creating resilient communities. An important part of this is estimating what buildings will become uninhabitable due to a flood event such as a tropical cyclone. To increase the accuracy of these estimations, habitability functions are developed to quantify the relationship between hydrodynamic hazards and the probability of a building becoming uninhabitable following Hurricane Irma. Hazards like maximum flood depths are determined by modeling Hurricane Irma flooding in Delft3D-FM coupled with the wave model SWAN. These modeled hazard levels are then extracted at building locations where Location Based Services (LBS) data provide information on buildings that were uninhabitable following Hurricane Irma. The developed habitability functions provide valuable insights into how different hydrodynamic parameters and regression models perform for estimating building habitability, where maximum depth is generally the best predictor of habitability. Furthermore, we find that while wooden structure habitability is significantly influenced by hazard level, concrete structure habitability is not. These findings provide novel methods for estimating coastal flooding induced building uninhabitability, enhancing how planners can prepare for floods.

Appropriate management of coastal flood risk is critical for creating resilient communities. An important part of this is estimating what buildings will become uninhabitable due to a flood event such as a tropical cyclone. To increase the accuracy of these estimations, habitability functions are developed to quantify the relationship between hydrodynamic hazards and the probability of a building becoming uninhabitable following Hurricane Irma. Hazards like maximum flood depths are determined by modeling Hurricane Irma flooding in Delft3D-FM coupled with the wave model SWAN. These modeled hazard levels are then extracted at building locations where Location Based Services (LBS) data provide information on buildings that were uninhabitable following Hurricane Irma. The developed habitability functions provide valuable insights into how different hydrodynamic parameters and regression models perform for estimating building habitability, where maximum depth is generally the best predictor of habitability. Furthermore, we find that while wooden structure habitability is significantly influenced by hazard level, concrete structure habitability is not. These findings provide novel methods for estimating coastal flooding induced building uninhabitability, enhancing how planners can prepare for floods.

Appropriate management of coastal flood risk is critical for creating resilient communities. An important part of this is estimating what buildings will become uninhabitable due to a flood event such as a tropical cyclone. To increase the accuracy of these estimations, habitability functions are developed to quantify the relationship between hydrodynamic hazards and the probability of a building becoming uninhabitable following Hurricane Irma. Hazards like maximum flood depths are determined by modeling Hurricane Irma flooding in Delft3D-FM coupled with the wave model SWAN. These modeled hazard levels are then extracted at building locations where Location Based Services (LBS) data provide information on buildings that were uninhabitable following Hurricane Irma. The developed habitability functions provide valuable insights into how different hydrodynamic parameters and regression models perform for estimating building habitability, where maximum depth is generally the best predictor of habitability. Furthermore, we find that while wooden structure habitability is significantly influenced by hazard level, concrete structure habitability is not. These findings provide novel methods for estimating coastal flooding induced building uninhabitability, enhancing how planners can prepare for floods.

In the aftermath of Hurricane Ike in 2008 in the United States, the “Ike Dike” was proposed as a coastal barrier system, featuring floodgates, to protect the Houston‐Galveston area (HGA) from future storm surges. Given its substantial costs, the feasibility and effectiveness of the Ike Dike have been subjects of investigation. In this study, we evaluated these aspects under both present and future climate conditions by simulating storm surges using a set of models. Delft3D Flexible Mesh Suite was utilized to simulate hydrodynamic and wave motions driven by hurricanes, with wind and pressure fields spatialized by the Holland model. The models were validated against data from Hurricane Ike and were used to simulate synthetic hurricane tracks downscaled from several general circulation models and based on different sea level rise projections, both with and without the Ike Dike. Flood maps for each simulation were generated, and probabilistic flood depths for specific annual exceedance probabilities were predicted using annual maxima flood maps. Building damage curves were applied to residential properties in the HGA to calculate flood damage for each exceedance probability, resulting in estimates of expected annual damage as a measure of quantified flood risk. Our findings indicate that the Ike Dike significantly mitigates storm surge risk in the HGA, demonstrating its feasibility and effectiveness. We also found that the flood risk estimates are sensitive to hurricane intensity, the choice of damage curve, and the properties included in the analysis, suggesting that careful consideration is needed in future studies.