{"id":375621,"date":"2020-10-27T07:23:56","date_gmt":"2020-10-27T14:23:56","guid":{"rendered":"https:\/\/www.esri.com\/about\/newsroom\/?post_type=blog&#038;p=375621"},"modified":"2022-03-29T14:33:15","modified_gmt":"2022-03-29T21:33:15","slug":"predictive-model-saves-louisiana-national-guard-vital-time","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/about\/newsroom\/blog\/predictive-model-saves-louisiana-national-guard-vital-time","title":{"rendered":"In Back-to-Back Hurricanes, Louisiana National Guard Calls on Predictive Model"},"author":5252,"featured_media":0,"parent":0,"menu_order":0,"template":"","format":"standard","meta":{"_acf_changed":false,"sync_status":"","episode_type":"","audio_file":"","podmotor_file_id":"","podmotor_episode_id":"","castos_file_data":"","cover_image":"","cover_image_id":"","duration":"","filesize":"","filesize_raw":"","date_recorded":"","explicit":"","block":"","itunes_episode_number":"","itunes_title":"","itunes_season_number":"","itunes_episode_type":"","_links_to":"","_links_to_target":""},"categories":[13602,211],"tags":[921,165752,201112,296652],"industry":[],"esri-blog-category":[478642],"esri_blog_department":[478242],"class_list":["post-375621","blog","type-blog","status-publish","format-standard","hentry","category-natural-disasters","category-public-safety","tag-disaster-response","tag-hurricane","tag-modeling","tag-national-guard","esri-blog-category-disaster-response","esri_blog_department-public-safety"],"acf":{"video_source":"","video_start":"","video_stop":"","short_description":"The Louisiana National Guard consumes geospatial model and maps to guide storm-recovery and COVID-19 operations.","pdf":{"host_remotely":false,"file":"","file_url":""},"flexible_content":[{"acf_fc_layout":"sidebar","layout":"standard","image_reference":null,"image_reference_figure":"","spotlight_image":null,"section_title":"","spotlight_name":"","position":"Right","content":"The Louisiana National Guard consumes geospatial model and maps to guide storm-recovery and COVID-19 operations.\r\n\r\nKey Takeaways\r\n<ul>\r\n \t<li>Models that run myriad geospatial queries quantify weather damages to help responders anticipate needs.<\/li>\r\n \t<li>Shared maps provide teams with crucial context to assess and act.<\/li>\r\n \t<li>High-resolution maps and dashboards show current conditions and guide restoration efforts.<\/li>\r\n<\/ul>","snippet":""},{"acf_fc_layout":"content","content":"Hurricane Delta made landfall in Louisiana in mid-October, resulting in two casualties, flooding neighborhoods, and leaving thousands of residents without electricity. The storm hit just six weeks after Hurricane Laura devastated the same region, and just as power had been restored. With back-to-back hurricanes, the state\u2019s emergency responders have been calling on new models and maps to anticipate where help will be needed most.\r\n\r\nHurricane Delta\u2014the third to hit the state this year, and the fourth major storm\u2014left a deluge of more than 15 inches of rain that damaged homes and businesses already reeling from Laura\u2019s winds, which tied an 1856 storm for the strongest gusts to hit the state.\r\n\r\nWith a hurricane bearing down, Colonel Greg St. Romain, commander of Louisiana National Guard\u2019s 225th Engineer Brigade, used maps informed by a new predictive model to guide his team into position.\r\n\r\n\u201cThe storm surge map helped me pre-position the right types of equipment for a windstorm versus a flooding event,\u201d Colonel St. Romain said. \u201cWe have high-water vehicles, we have boat systems, and we have engineering equipment to clear roads so emergency vehicles and power companies can access impacted areas.\u201d"},{"acf_fc_layout":"image","image":375681,"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"The maps, showing where wind would cause the greatest damage, were developed using models built with a geographic information system (GIS). During Hurricane Laura, the standard storm surge model showed significant flooding for areas near Lake Charles. However, as the hurricane approached land on August 28, 2020, a high-resolution storm surge model coupled with a consequence model revealed high winds as the greatest threat.\r\n\r\n\u201cTime is of the essence, and having the right tools and the right data, is essential to make effective personnel and equipment decisions,\u201d Colonel St. Romain said.\r\n<h3><strong>Arriving at a Predictive Model<\/strong><\/h3>\r\nThe consequence model was developed at Louisiana State University (LSU), born from the need to bridge the gap between a high-level storm surge model and an understanding of local impacts. It uses the high-resolution Advance Circulation (ADCIRC) model of storm surge provided by a team of researchers at the University of North Carolina and Notre Dame University. The model is visualized through the Coastal Emergency Risk Assessment software to predict impacts on an inventory of infrastructure assets, businesses, buildings, homes and people (see sidebar). Together, these models have proven their predictive power.\r\n\r\n\u201cWhen I first came here, Hurricane Isaac had just impacted the state [August 21, 2012], causing massive flooding in LaPlace, which previously hadn\u2019t experienced any significant flooding from storm surge,\u201d said Brant Mitchell, director, Stephenson Disaster Management Institute (SDMI) at LSU. \u201cWe went back and looked at the data and analyzed the ADCIRC outputs and it successfully predicted approximately 90 percent of the extent of flooding 48 hours prior to landfall. The model wasn\u2019t leveraged by the emergency management community then, which would have helped the response. So, we set out to provide the output from the model in a manner that can be easily understood.\u201d"},{"acf_fc_layout":"image","image":375691,"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"Emergency management professionals have trouble looking at complex models in the midst of lifesaving and property-saving measures. They\u2019re busy allocating resources and triaging calls for assistance. Mitchell realized that emergency managers and public officials needed a way to quickly grasp the information in the models.\r\n\r\n\u201cDecision makers need tools that tell them exactly what\u2019s going on,\u201d Mitchell said.\r\n\r\nThe National Weather Service (NWS) model is fast and can be run on a desktop computer. Speed is crucial to understand the potential impacts while meteorologists are developing the hurricane advisory. The <a href=\"https:\/\/www.nhc.noaa.gov\/surge\/slosh.php\">NWS\u2019s Sea, Lake and Overland Surges from Hurricanes (SLOSH) model<\/a> doesn\u2019t have the granularity or resolution \u00a0of the ADCIRC model that researchers run on supercomputers or the data inputs of the consequence model. \u201cEven with a supercomputer, it takes approximately 90 to 120 minutes to run the model,\u201d Michell said. \u201cThat doesn\u2019t provide the National Weather Service sufficient time to integrate it into the development of their advisory.\u201d\r\n\r\nThe more granular model fits perfectly with the emergency response mission. To make the details easy to consume and share, Mitchell and the team from SDMI deliver detailed maps via <a href=\"https:\/\/storymaps.arcgis.com\/\">ArcGIS StoryMaps<\/a>, share data, and print large maps to convey actionable details.\r\n<h3><strong>Models Inform Operations<\/strong><\/h3>\r\nThe SDMI consequence model pinpoints a hurricane\u2019s impact on people, homes, businesses, hospitals, and critical infrastructure\u2014details of great importance to first responders.\r\n\r\n\u201cThe model presents an overview of damages in a manner that is easy to understand,\u201d Mitchell said. \u201cIt serves as a decision-making tool on whether to call for evacuations and where to prioritize post-disaster actions such as search and rescue.\u201d\r\n\r\nIn the case of Hurricane Laura, the ADCIRC and consequence model saved a lot of needless work when it showed that storm surge wasn\u2019t likely inside the city of Lake Charles. With Hurricane Laura designated a Category 4 Hurricane, the National Weather Service warned residents of Louisiana of the potential of up to 20 feet of flooding and life threatening storm surge."},{"acf_fc_layout":"image","image":375701,"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"\u201cWe have an armory in Lake Charles, which is used as a staging area, and they were talking about relocating those resources,\u201d said Mike Liotta, GIS manager, civilian with Louisiana\u2019s Military Department. \u201cAfter looking at the consequence model, I was able to update our leadership that our staging area should not be impacted by the storm surge.\u201d\r\n\r\nHaving the maps and models of the projected damage also helped troops stage the right equipment for clean-up and to stand down the search and rescue mission. It typically takes 24 hours to completely switch missions, but thanks to the predictive view, the 225th Engineer Brigade was ready to go.\r\n<h3><strong>Maps Support Impact Areas<\/strong><\/h3>\r\nGIS outputs take the form of a real-time common operational picture (COP) within an emergency operation center (EOC) where both Mitchell and Liotta can be found during an emergency. Staff with phones or tablets in the field use apps to collect and sync much of the data that a COP displays. The team also uses GIS to plot outputs of the high-resolution model onto large maps for boots-on-the ground first responders who often work in off-the-grid areas without communication signals.\r\n\r\n\u201cI like having something printed in my hand when I leave the office and head to an impact area,\u201d Colonel St. Romain said. \u201cI can lay it on the hood of a vehicle and really study it and understand where I need things to be. I use it as a kind of sand table to maneuver our equipment and personnel.\u201d"},{"acf_fc_layout":"gallery","gallery_images":[376331,377491,377461,377471,377481]},{"acf_fc_layout":"content","content":"Huddling around the paper map with a pen in hand continues to be a great way to collaborate with a shared context. However, it\u2019s never just one map and done.\r\n\r\nColonel St. Romain was an engineer officer within the ranks for many years, before taking command in May. \u201cI\u2019ve had opportunities to work with our GIS department in the past,\u201d Colonel St. Romain said. \u201cI know what Mike Liotta and his team are capable of delivering. If I\u2019m not comfortable with the incoming information, I reach out to him to reinforce a decision or provide me with more details of an area I\u2019m concerned about.\u201d\r\n<h2><strong>Taking Care of Consequences<\/strong><\/h2>\r\nAfter Hurricane Laura left considerable damages, Colonel St. Romain shifted his focus to a long-lasting and far-reaching debris removal exercise, and again relied on GIS.\r\n\r\n\u201cIf I had an available vehicle, we were utilizing it throughout the event,\u201d Colonel St. Romain said. \u201cOur operations spanned from the southwest coast of Louisiana to the northern parishes.\u201d"},{"acf_fc_layout":"gallery","gallery_images":[375741,375731,375751,375761]},{"acf_fc_layout":"content","content":"The team from SDMI deployed a real-time truck tracking dashboard at the state EOC to inform and reassure leaders that all equipment was where it needed to be. Mitchell, previously a member of the National Guard and currently a lieutenant colonel in the Army Reserves, designed what\u2019s known as the ComTrac system to track resources as they move after a major disaster.\r\n\r\n\u201cThe National Guard moves commodities, whether it be food, water, tarps, and other vital resources,\u201d Mitchell said. \u201cComTrac gives everyone the ability to identify where each truck is located once it leaves the Regional Staging Area.\u201d\r\n\r\nThe high-resolution confidence model and the ability to track resources in real-time have given the Louisiana National Guard new inputs for better understanding.\r\n\r\n\u201cIt\u2019s never a guessing game,\u201d Colonel St. Romain said. \u201cWe rely on best available tools to make the most educated decisions. The consequence model definitely reinforced our decisions to readjust and pivot to certain parishes.\u201d\r\n\r\n&nbsp;\r\n\r\n&nbsp;"},{"acf_fc_layout":"sidebar","layout":"standard","image_reference":null,"image_reference_figure":"","spotlight_image":null,"section_title":"","spotlight_name":"","position":"Center","content":"<h2><strong>Detailed Data Provides Trusted Guidance<\/strong><\/h2>\r\nA group of researchers, academics, and software developers at Louisiana State University collaborated with the Department of Homeland Security Science and Technology (DHS S&amp;T) Center of Excellence at the University of North Carolina to create the consequence model.\r\n\r\n\u201cWe developed a major Python script that runs geospatial queries of the information,\u201d said Brant Mitchell, director, Stephenson Disaster Management Institute at LSU. \u201cOnce we get the storm surge output, we conduct geospatial analytics to determine where there will be damage and what the potential impacts from the storm surge may be.\u201d\r\n\r\nThe model contains very detailed data that was collected after Hurricane Katrina for the Governor\u2019s Office of Homeland Security and Emergency Preparedness. All of the state\u2019s critical infrastructure and businesses were collected for all 64 parishes. An in-depth database contains details on more than 100,000 points of infrastructure and assets. Census data provides details on people.\r\n\r\n\u201cWe discovered that ADCIRC was nearly 90 percent accurate 48 hours out, when we evaluated it post-Hurricane Isaac,\u201d Mitchell said. \u201cWith that kind of reliability, it\u2019s information you can feel confident making a decision with, especially if it comes to an evacuation order.\u201d","snippet":""}],"references":null},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>In Back-to-Back Hurricanes, Louisiana National Guard Calls on Predictive Model<\/title>\n<meta name=\"description\" content=\"A high-resolution storm surge and consequence model helped the Louisiana National Guard pre-position the right hurricane response equipment.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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