# Machine-Learning-Based Model for Hurricane Storm Surge Forecasting in the Lower Laguna Madre
## 1 Introduction  
The United States mainland has experienced around 280 hurricane strikes since the 1850s. Of these hurricane impacts, nearly a hundred have been classified in the Saffir/Simpson Hurricane Wind Scale (SSHWS) as a category 3 or greater. The monetary damage that such hurricane impacts have can ascend to billions of dollars, as was the case with Hurricane Katrina in 2005 and Ike in 2008. The quantified damages are only a single measure of how destructive a hurricane can be and serve as reminders of the importance of preparation and adequate planning for such events [1, 2]. The Laguna Madre, located in South Texas, is one of the six hypersaline logoons in the world. It is a unique ecological system that provides the perfect environment for the proliferation of numerous species of flora and fauna. This lagoon, and the surrounding region, is impacted by hurricanes that affect the coastal population with flooding and storm surges. Although communities are well aware of the risks that every hurricane season brings, the tools available to prepare and plan are scarce. Storm surge research in this region is paramount to answer the needs of the population. This study seeks to provide a tool that can be used for forecasting storm surge conditions days ahead, without the usage of expensive resources and with automation capabilities. The model proposed here can help first responders and emergency bodies to assemble resources and develop plans ahead of a hurricane impact and subsequential storm surge. Coastal cities have experienced a boom in growth since the 2000s. The increase has stayed constant at a rate of approximately one percent per year. Leisure has been one of themost cited reasons for growth, and as such, the need for infrastructure in coastal cities has increased proportionately. There have been projects prompted from coastal growth, such as the construction of transportation, water and electrical infrastructure. This has brought many benefits to coastal communities and has allowed and aided their continuous growth, but at the same time, it has also raised a major weakness point. All the infrastructure necessary to sustain and expand communities in coastal areas are just new vulnerabilities. One of the major drivers of hurricane damages in coastal cities are storm surges, due to their proximity to the ocean. Storm surge refers to the abnormal rise in ocean levels beyond the predicted astronomical tides as a result of sustained winds, among other factors [3]. The state of Texas has many coastal cities that could be potentially struck by hurricanes and subsequent storm surges. Major hurricane impacts can bring destruction to vulnerable infrastructure, creating a potential avenue for billions of dollars worth of damages [4]. It is also important to mention that the danger of a hurricane storm surge is not only limited to direct structural damages; it also represents a worrying environmental risk. Many of the coastal cities that could be potentially damaged by hurricanes and storm surges also house ports. These ports expose industrial complexes to catastrophic events. As an example, Hurricane Ike brought USD 30 billion dollars in damages to the cities of Houston and Galveston, where at least 112 deaths occurred. The Houston Ship Channel is one of the busiest seaports in the world and is the host of many petrochemical complexes, which heightens the potential for an environmental disaster [5; 6]. Since storm surges have the potential to cause damages worth billions of dollars, as well as cause deaths and possible environmental disasters, it is of the utmost importance to plan accordingly when a major hurricane is approaching a coastal area. It is possible to assess the potential risk that a hurricane poses in terms of storm surge by creating a simulation of the interaction between winds, atmospheric pressure, tides, and waves.