scholarly journals Integrating Evacuation and Storm Surge Modeling Considering Potential Hurricane Tracks: The Case of Hurricane Irma in Southeast Florida

2021 ◽  
Vol 10 (10) ◽  
pp. 661
Author(s):  
Mahyar Ghorbanzadeh ◽  
Linoj Vijayan ◽  
Jieya Yang ◽  
Eren Erman Ozguven ◽  
Wenrui Huang ◽  
...  
Keyword(s):  
Storm Surge ◽  
Element Model ◽  
South Florida ◽  
Individual Decision ◽  
Evacuation Modeling ◽  
Case Study Analysis ◽  
Storm Surge Modeling ◽  
Shelter Availability ◽  
Hurricane Irma

Hurricane Irma, in 2017, made an unusual landfall in South Florida and the unpredictability of the hurricane’s path challenged the evacuation process seriously and left many evacuees clueless. It was likely to hit Southeast Florida but suddenly shifted its path to the west coast of the peninsula, where the evacuation process had to change immediately without any time for individual decision-making. As such, this study aimed to develop a methodology to integrate evacuation and storm surge modeling with a case study analysis of Irma hitting Southeast Florida. For this purpose, a coupled storm surge and wave finite element model (ADCIRC+SWAN) was used to determine the inundation zones and roadways with higher inundation risk in Broward, Miami-Dade, and Palm Beach counties in Southeast Florida. This was fed into the evacuation modeling to estimate the regional clearance times and shelter availability in the selected counties. Findings show that it takes approximately three days to safely evacuate the populations in the study area. Modeling such integrated simulations before the hurricane hit the state could provide the information people in hurricane-prone areas need to decide to evacuate or not before the mandatory evacuation order is given.

scholarly journals Integrating storm surge modeling with traffic data analysis to evaluate the effectiveness of hurricane evacuation

2021 ◽  
Author(s):  
Wenrui Huang ◽  
Kai Yin ◽  
Mahyar Ghorbanzadeh ◽  
Eren Ozguven ◽  
Sudong Xu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Storm Surge ◽  
South Florida ◽  
Traffic Data ◽  
Maximum Wind ◽  
South West ◽  
Storm Surge Modeling ◽  
Hurricane Forecasting ◽  
Evacuation Traffic ◽  
Hurricane Irma

AbstractAn 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.

scholarly journals Hurricane Irma Simulation at South Florida Using the Parallel CEST Model

2021 ◽  
Vol 3 ◽  
Author(s):  
Yuepeng Li ◽  
Qiang Chen ◽  
Dave M. Kelly ◽  
Keqi Zhang
Keyword(s):  
Storm Surge ◽  
Message Passing ◽  
High Performance ◽  
Message Passing Interface ◽  
Field Measurements ◽  
South Florida ◽  
Computational Time ◽  
Linear Speedup ◽  
Lagrangian Advection ◽  
Hurricane Irma

In this study, a parallel extension of the Coastal and Estuarine Storm Tide (CEST) model is developed and applied to simulate the storm surge tide at South Florida induced by hurricane Irma occurred in 2017. An improvement is also made to the existing advection algorithm in CEST. This is achieved through the introduction of high-order, monotone Semi-Lagrangian advection. Distributed memory parallelization is developed via the Message Passing Interface (MPI) library. The parallel CEST model can therefore be run efficiently on machines ranging from multicore laptops to massively High Performance Computing (HPC) system. The principle advantage of being able to run the CEST model on multiple cores is that relatively low run-time is possible for real world storm surge simulations on grids with high resolution, especially in the locality where the hurricane makes landfall. The computational time is critical for storm surge model forecast to finish simulations in 30 min, and results are available to users before the arrival of the next advisory. In this study, simulation of hurricane Irma induced storm surge was approximately 22 min for 4 day simulation, with the results validated by field measurements. Further efficiency analysis reveals that the parallel CEST model can achieve linear speedup when the number of processors is not very large.

The process of change in accelerated experiential dynamic psychotherapy (AEDP): A case study analysis.

2018 ◽  
Vol 28 (2) ◽  
pp. 213-232
Author(s):  
Rayna D. Markin ◽  
Kevin S. McCarthy ◽  
Amy Fuhrmann ◽  
Danny Yeung ◽  
Kari A. Gleiser
Keyword(s):  
Study Analysis ◽  
Dynamic Psychotherapy ◽  
Process Of Change ◽  
Case Study Analysis

On the Origins of Administrative Rent: Doing Business in a Russian Region N

2010 ◽  
pp. 58-80 ◽  
Author(s):  
A. Oleinik
Keyword(s):  
Rent Seeking ◽  
Individual Decision ◽  
Resource Rent ◽  
Competitive Edge ◽  
Doing Business ◽  
Russian Region ◽  
Positive Gain ◽  
Access To The Field ◽  
Quantitative And Qualitative Methods

In the article two types of rent are differentiated: resource rent and administrative rent. The latter is linked to restrictions on the access to the field of interactions. The contribution of the theory of public choice and the theory of rent-seeking and directly-unproductive activities is further developed by shifting the emphasis from individual decision-making to interactions between three actors: C, who controls access to the field, A, who gets a competitive edge as a result, and B, who assumes a subjacent position with regard to both A and C, yet still receives a positive gain from transacting. Domination by virtue of a constellation of As, Bs, and Cs interests is illustrated with the help of an in-depth case study of a Russian region. This study combines quantitative and qualitative methods, as well as their triangulation.

Count Me In!: Ethnic Data Disaggregation Advocacy, Racial Mattering, and Lessons for Racial Justice Coalitions

JCSCORE ◽  
2018 ◽  
Vol 3 (1) ◽  
pp. 91-124
Author(s):  
OiYan A. Poon ◽  
Jude Paul Matias Dizon ◽  
Dian Squire
Keyword(s):  
Asian American ◽  
People Of Color ◽  
Racial Justice ◽  
Racial Equity ◽  
Equity In Education ◽  
Case Study Analysis ◽  
Data Disaggregation ◽  
Racial Solidarity ◽  
The University

This article presents a case study of the 2006-2007 Asian American and Pacific Islander (AAPI) student-led Count Me In! (CMI) campaign. This successful campaign convinced the University of California (UC) to account for 23 AAPI ethnic identities in its data system. Celebrated as a victory for AAPI interests in discourses over racial equity in education, which are often defined by a Black- white racial paradigm, CMI should also be remembered as originating out of efforts to demonstrate AAPI solidarity with Black students and to counter racial wedge politics. In the evolution of the CMI campaign, efforts for cross-racial solidarity soon faded as the desire for institutional validation of AAPI educational struggles was centered. Our case study analysis, guided by sociological frameworks of racism, revealed key limitations in the CMI campaign related to the intricate relations between people of color advocating for racial justice. We conclude with cautions for research and campaigns for ethnically disaggregated AAPI data, and encourage advocates and scholars to address AAPI concerns over educational disparities while simultaneously and intentionally building coalitions for racial equity in higher education.

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