Media in Crisis: Journalistic Norms in Natural Disaster Coverage

Nearing the end of 2017, the United States and the Caribbean were struck with back-to-back natural disasters that left the country in shock and turmoil. Among the three hurricanes that struck sequentially, Hurricane Harvey landed in Texas approximately on August 25th, 2017 and Hurricane Maria hit the Caribbean and Puerto Rico around September 20th, 2017. These disasters were a test for the new presidential cabinet of how they would handle their first natural disaster. Hurricane Maria and Hurricane Harvey caused similar levels of destruction, with Maria being a category five storm and Harvey a category four. However, the media reacted differently to the crisis that unfolded in Puerto Rico in comparison to Texas. This study focuses on how journalists and the news industry covered both disasters and compares and contrasts the manner in which they were done. Pulling in media industry knowledge, rhetoric and cultural theory, the study uncovers how disaster communication was influenced by societal values involving culture and examines how the narrative journalists participated in affected the coverage, in turn shaping public knowledge

Hurricane Harvey Hospital Flood Impacts: Accuracy of Federal Emergency Management Agency Flood Hazard Areas in Harris County, Texas

Objectives: To compare the flood impacts experienced by Harris County, Texas, hospitals with Federal Emergency Management Agency (FEMA) flood hazard areas and Hurricane Harvey&rsquo;s inundation boundary. Methods. One year following Hurricane Harvey, we created a novel data set of Hurricane Harvey&rsquo;s flood impacts in Harris County hospitals. We then mapped the hospital flood impact data in ArcGIS alongside FEMA flood hazard areas and Hurricane Harvey&rsquo;s inundation boundary to classify each hospital&rsquo;s location in high flood-risk areas and in areas purportedly affected by Hurricane Harvey. Results. Of the 66 hospitals for which flood impact information was ascertained, 16 (24%) hospitals experienced flood impacts during Hurricane Harvey. Of these 16 hospitals, 5 (31%) were located outside a FEMA flood hazard area and 8 (50%) were located outside Hurricane Harvey&rsquo;s inundation boundary. Conclusions. FEMA flood hazard areas did not accurately predict all areas of Harris County, Texas, that flooded during Hurricane Harvey or which hospitals experienced flood impacts.</p

Hurricane Harvey Research Symposium

Table of Contents: Invited Speaker Biography (p. 4) -- Schedule (p. 5) -- Poster Titles and Presenters (p. 8) -- Abstracts for Oral Presentations (p. 9) -- Abstracts for Poster Presentations (p. 24)Marine Scienc

Estimating Losses from Hurricane Harvey Using FEMA's HAZUS-MH Model

Hurricane Harvey was one of the most destructive and costliest hurricanes to ever make landfall on the Texas coast and one of the many tropical cyclones that impacted the United States during the 2017 North Atlantic Hurricane Season. In recent years, emergency managers and researchers have been using hurricane risk and vulnerability analyses developed using Geographic Information Systems (GIS) to make informed decisions on different aspects of community and regional preparedness when a tropical cyclone is forecasted to impact an area. Though there are many ways to quantify risk and vulnerability, this project uses the Federal Emergency Management Agency’s (FEMA) Hazards-US Multi-Hazards (HAZUS-MH) GIS extension to estimate and illustrate the physical, economic, and social losses associated with tropical cyclone impacts along the Texas coast, specifically in the Greater Houston Region. There are numerous ways to quantify risks associated with tropical cyclones using GIS, most of which focus on one of the three hazards involved in hurricane impact: extreme winds, heavy rainfall, and storm surge. This project addresses this shortcoming by focusing on all three hazards and modelling the physical, economic, and social losses in locations in the Greater Houston Region that were caused by Hurricane Harvey. Heavy rainfall produced the most losses, while storm surge affected the southern-most areas of the Texas coast. Wind damage from Hurricane Harvey was insignificant in comparison to the probabilistic scenarios, with losses estimated to be in the thousands of dollars, instead of in the millions or billions of dollars. The results of this study are compared to each other to see if the most vulnerable areas of the Greater Houston Region were largely affected by Hurricane Harvey

Estimating Losses from Hurricane Harvey Using FEMA's HAZUS-MH Model

Hurricane Harvey was one of the most destructive and costliest hurricanes to ever make landfall on the Texas coast and one of the many tropical cyclones that impacted the United States during the 2017 North Atlantic Hurricane Season. In recent years, emergency managers and researchers have been using hurricane risk and vulnerability analyses developed using Geographic Information Systems (GIS) to make informed decisions on different aspects of community and regional preparedness when a tropical cyclone is forecasted to impact an area. Though there are many ways to quantify risk and vulnerability, this project uses the Federal Emergency Management Agency’s (FEMA) Hazards-US Multi-Hazards (HAZUS-MH) GIS extension to estimate and illustrate the physical, economic, and social losses associated with tropical cyclone impacts along the Texas coast, specifically in the Greater Houston Region. There are numerous ways to quantify risks associated with tropical cyclones using GIS, most of which focus on one of the three hazards involved in hurricane impact: extreme winds, heavy rainfall, and storm surge. This project addresses this shortcoming by focusing on all three hazards and modelling the physical, economic, and social losses in locations in the Greater Houston Region that were caused by Hurricane Harvey. Heavy rainfall produced the most losses, while storm surge affected the southern-most areas of the Texas coast. Wind damage from Hurricane Harvey was insignificant in comparison to the probabilistic scenarios, with losses estimated to be in the thousands of dollars, instead of in the millions or billions of dollars. The results of this study are compared to each other to see if the most vulnerable areas of the Greater Houston Region were largely affected by Hurricane Harvey

Gene expression of endangered coral (Orbicella spp.) in flower garden banks National Marine Sanctuary after Hurricane Harvey

About 190 km south of the Texas–Louisiana border, the East and West Flower Garden Banks (FGB) have maintained > 50% coral cover with infrequent and minor incidents of disease or bleaching since monitoring began in the 1970s. However, a mortality event, affecting 5.6 ha (2.6% of the area) of the East FGB, occurred in late July 2016 and coincided with storm-generated freshwater runoff extending offshore and over the reef system. To capture the immediate effects of storm-driven freshwater runoff on coral and symbiont physiology, we leveraged the heavy rainfall associated with Hurricane Harvey in late August 2017 by sampling FGB corals at two time points: September 2017, when surface water salinity was reduced (∼34 ppt); and 1 month later when salinity had returned to typical levels (∼36 ppt in October 2017). Tissue samples (N = 47) collected midday were immediately preserved for gene expression profiling from two congeneric coral species (Orbicella faveolata and Orbicella franksi) from the East and West FGB to determine the physiological consequences of storm-derived runoff. In the coral, differences between host species and sampling time points accounted for the majority of differentially expressed genes. Gene ontology enrichment for genes differentially expressed immediately after Hurricane Harvey indicated increases in cellular oxidative stress responses. Although tissue loss was not observed on FGB reefs following Hurricane Harvey, our results suggest that poor water quality following this storm caused FGB corals to experience sub-lethal stress. We also found dramatic expression differences across sampling time points in the coral’s algal symbiont, Breviolum minutum. Some of these differentially expressed genes may be involved in the symbionts’ response to changing environments, including a group of differentially expressed post-transcriptional RNA modification genes. In this study, we cannot disentangle the effects of reduced salinity from the collection time point, so these expression patterns could also be related to seasonality. These findings highlight the urgent need for continued monitoring of these reef systems to establish a baseline for gene expression of healthy corals in the FGB system across seasons, as well as the need for integrated solutions to manage stormwater runoff in the Gulf of Mexico.https://www.frontiersin.org/articles/10.3389/fmars.2019.00672/fullPublished versionPublished versio

Ecosystem Restoration After Hurricane Harvey

Sarah: It was about a month before the stress of finals, and anticipation of Christmas break was upon us. I was scrolling through my emails when I noticed an opportunity to attend an 8-day winter breakout in Houston, Texas. After the devastation that Hurricane Harvey brought the city of Houston, one could expect the need for house repairs and cleanups. Instead, this trip was seeking individuals willing to help with conservation and restoration efforts. My roommate, and fellow Stew, Celia, has taught me nearly everything I know about the importance and great need for ecosystem restoration. I quickly forwarded her the email stating quite bluntly, “DUDE. We have to do this.

How Do People Describe Locations During a Natural Disaster: An Analysis of Tweets from Hurricane Harvey

Social media platforms, such as Twitter, have been increasingly used by people during natural disasters to share information and request for help. Hurricane Harvey was a category 4 hurricane that devastated Houston, Texas, USA in August 2017 and caused catastrophic flooding in the Houston metropolitan area. Hurricane Harvey also witnessed the widespread use of social media by the general public in response to this major disaster, and geographic locations are key information pieces described in many of the social media messages. A geoparsing system, or a geoparser, can be utilized to automatically extract and locate the described locations, which can help first responders reach the people in need. While a number of geoparsers have already been developed, it is unclear how effective they are in recognizing and geo-locating the locations described by people during natural disasters. To fill this gap, this work seeks to understand how people describe locations during a natural disaster by analyzing a sample of tweets posted during Hurricane Harvey. We then identify the limitations of existing geoparsers in processing these tweets, and discuss possible approaches to overcoming these limitations

Social and Emotional Support for Children and their Caregivers Post-Disasters

The purpose of this paper is to share Save the Children’s responses to Hurricane Harvey in Texas, Hurricane Maria in Puerto Rico, and Hurricane Irma in Florida in 2017. Save the Children’s response and recovery efforts in the aftermath of these disasters consisted of a wide range of services for the affected children and their caregivers, including assistance to childcare centers and organizations, and providing child-focused services, such as psychosocial support. This paper will particularly focus on the psychosocial support element of the responses