An efficient artificial intelligence model for prediction of tropical storm surge

2016 ◽  
Vol 82 (1) ◽  
pp. 471-491 ◽  
Author(s):  
M. Reza Hashemi ◽  
Malcolm L. Spaulding ◽  
Alex Shaw ◽  
Hamed Farhadi ◽  
Matt Lewis
2017 ◽  
Vol 11 (1) ◽  
pp. 9 ◽  
Author(s):  
James L. Wilson, PhD ◽  
Ruth Little, MPH ◽  
Lloyd Novick, MD, MPH

Objective: To develop a simple, cost-effective method for determining the size and geographic distribution of medically fragile (MF) individuals at risk from tropical storm surges for use by emergency management planners.Design: The study used Geographic Information System (GIS) spatially referenced layers based on secondary data sources from both state and federal levels. Setting: The study setting included the eastern North Carolina coastal counties that would be affected by tropical storm surges.Subjects: The initial MF population was extrapolated from national estimates for five conditions and then applied to US Census block population. These conditions included insulin dependent diabetes, chronic obstructive pulmonary disease, congestive heart failure, end stage renal disease, and patients receiving long-term oxygen treatment.Main outcomes: The main outcome of this study was a series of local and regional maps that portrayed the geographic distribution and estimated counts of potentially at-risk MF population from a tropical storm surge scenario.Conclusions: Maps depicting the geographic distribution and potential numbers of MF individuals are important information for planning and preparedness in emergency management and potentially engaging the public.


Hydrology ◽  
2018 ◽  
Vol 5 (1) ◽  
pp. 13 ◽  
Author(s):  
Walter Silva-Araya ◽  
Félix Santiago-Collazo ◽  
Juan Gonzalez-Lopez ◽  
Javier Maldonado-Maldonado

1984 ◽  
Vol 1 (19) ◽  
pp. 108 ◽  
Author(s):  
David L. Kriebel ◽  
Robert G. Dean

A numerical model is developed and applied to estimate the frequency distribution of severe erosion events. The proposed method is an extension of existing Monte Carlo storm surge simulation models. Hurricane and tropical storm meteorological parameters are randomly selected to generate a series of synthetic storms; the storm surge for each storm is estimated using a Bathystrophic storm surge model. The storm surge hydrograph is then used as input to a numerical erosion simulation model which determines beach profile response for each storm based on wave energy dissipation per unit volume as a general erosion forcing mechanism. Five 100-year random simulations are performed from which the return periods of storm surge and erosion, i.e. volume eroded and dune recession, are estimated.


2014 ◽  
Vol 12 (4) ◽  
pp. 403-410 ◽  
Author(s):  
Christian M. Appendini ◽  
Adrián Pedrozo-Acuña ◽  
Arnoldo Valle-Levinson

Author(s):  
Navid H. Jafari ◽  
Qin Chen ◽  
Jack Cadigan

Hurricane Laura made landfall on the southwest Louisiana coast near Cameron, LA on August 26th. As Laura approached the Louisiana coast, the Coastal Emergency Risks Assessment predicted a storm surge of approximately 5.2 m (17 ft), which marked the strongest surge to impact southwest Louisiana since the catastrophic Hurricane Rita in 2005. As a result, a team led by LSU and NEU mobilized to deploy surge and wave sensors and collect drone imagery at Rockefeller Wildlife Refuge and Cameron, LA on August 25th before the arrival of tropical storm winds. Rockefeller Refuge was selected to measure the capacity of wetlands and breakwaters to attenuate hurricane surge and waves, and pressure sensors were strategically placed at locations of civil infrastructure at Cameron to capture hurricane-induced overland flow (see Fig. 1). After the surge water receded, LSU retrieved the sensors, collected RTK elevation transects and multispectral drone imagery, and surveyed infrastructure damage along the southwest corridor of Louisiana, following the Highway 82 from Abbeville to Cameron.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/IevnFZ2YVfI


2020 ◽  
Vol 206 ◽  
pp. 103317 ◽  
Author(s):  
J. Freeman ◽  
M. Velic ◽  
F. Colberg ◽  
D. Greenslade ◽  
P. Divakaran ◽  
...  

Author(s):  
Ho-Sik Eum ◽  
◽  
Jong-Jib Park ◽  
Kwang-Young Jeong ◽  
Young-Min Park

MAUSAM ◽  
2021 ◽  
Vol 48 (4) ◽  
pp. 579-586
Author(s):  
JYE CHEN

The tropical storm surge models depend critically on the maximum surface wind and shape of the wind profile. Since none of them are easy to measure, designing the parametric wind models for the storm surge prediction becomes divergent. Two widely used, but very different, wind models are examined. The study of their parameters showed that their resulting maximum wind and the shape of the wind profiles are similar. This property is a very useful guide for evaluating different surge models.    


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