Guidelines for Analysing Coastal Flood Protection Systems after a Submersion

Storm Xynthia, which hit the French Atlantic coast on February 28th, 2010, flooded vast territories despite coastal defences. This disaster highlighted the need to further study the behaviour of the coastal flood protection systems at an adapted geographical scale by considering the kinematics of the events. This objective has been achieved through a combination of conceptual input on the definition of protection systems, significant breakthroughs in the knowledge of the mechanisms governing the flooding, and via the improvement of strategies and methods dedicated to flood analysis and representation. The developed methodology was successfully tested on four sites submerged during Xynthia (Loix, Les Boucholeurs, and Boyardville, located in Charente-Maritime, and Batz-sur-Mer, located in Loire-Atlantique). This work is intended to guide the diagnosis of sites prone to marine flooding from the first investigations until the delivery of study reports. Beyond the usual focus on hydraulic structures, it provides guidelines to better analyse the interactions with the natural environment (sea, soil, dune, wetlands, etc.) and with the built environment (roads and urban networks, ponds used for fish farming, buildings, etc.). This systemic approach, which is applied to a territory considered as a complex adaptive system, is fundamental to understanding the reaction of a territory during a marine submersion event and subsequently developing adaptation or transformation strategies.

Real-time coastal flood hazard assessment using DEM-based hydrogeomorphic classifiers

Deltas, estuaries, and wetlands are prone to frequent coastal flooding throughout the world. In addition, a large number of people in the United States have settled in these low-lying regions. Therefore, the ecological merit of wetlands for maintaining sustainable ecosystems highlights the importance of flood risk and hazard management in these regions. Typically, hydrodynamic models are used for coastal flood hazard mapping. The huge computational resources required for hydrodynamic modeling and the long-running time of these models (order of hours or days) are two major drawbacks that limit the application of these models for prompt decision-making by emergency responders. In the last decade, DEM-based classifiers based on Height Above Nearest Drainage (HAND) have been widely used for rapid flood hazard assessment demonstrating satisfactory performance for inland floods. The main limitation is the high sensitivity of HAND to the topography which degrades the accuracy of these methods in flat coastal regions. In addition, these methods are mostly used for a given return period and generate static hazard maps for past flood events. To cope with these two limitations, here we modify HAND and propose a composite hydrogeomorphic index for rapid flood hazard assessment in coastal areas. We also propose the development of hydrogeomorphic threshold operative curves for real-time flood hazard mapping. We select the Savannah river delta as a testbed, calibrate the proposed hydrogeomorphic index on Hurricane Matthew and validate the performance of the developed operative curves for Hurricane Irma. Validation results demonstrate that the operative curves can rapidly generate flood hazard maps with satisfactory accuracy. This indicates the high efficiency of our proposed methodology for fast and accurate estimation of hazard areas for an upcoming coastal flood event which can be beneficial for emergency responders and flood risk managers.

A Coastal Flood Event Database for the Southeastern Georgia and Southeastern South Carolina Coast and the Operational Implementation of a Tide Forecast Tool

Coastal flooding occurs when saltwater inundates normally dry land and the resulting impacts can range from minor flooding of low-lying areas along the coast, to significant damage to property and structures. Previous research consistently suggests that if sea-level rise continues to increase along the East Coast of the United States, coastal flooding will occur more frequently. In order to document the history of coastal flooding along the southeastern Georgia and southeastern South Carolina coast, a coastal flood event database was created for National Ocean Service tide gauges located in Charleston Harbor, South Carolina and Fort Pulaski, Georgia. Trends from the data show that coastal flooding is occurring more frequently with time at both tide gauges, particularly over the last five to ten years. Because of the increased frequency and worsening impacts of tidal flooding, a tide forecast tool is implemented operationally in an effort to improve deterministic tide forecasts. This study extends the dataset used in the Charleston Harbor forecast tool, expands the tool to Fort Pulaski, and compares the synoptic category forecast equations to an all-inclusive equation that does not differentiate by synoptic category. Results show that there is virtually no difference in the forecast accuracy between the all-inclusive forecast equation and the specific forecast equations based on synoptic category. Furthermore, the all-inclusive forecast equation can be implemented operationally, will help improve deterministic tide forecasts, and will likely aid in the decision-making process for Coastal Flood Watches, Warnings, and Advisories issued by the National Weather Service office in Charleston, South Carolina.

Knowledge Gaps Update to the 2019 IPCC Special Report on the Ocean and Cryosphere: Prospects to Refine Coastal Flood Hazard Assessments and Adaptation Strategies With At-Risk Communities of Alaska

This article reviews the status of knowledge gaps and co-production process challenges that impede coastal flood hazard resilience planning in communities of northwestern Alaska, where threat levels are high. Discussion focuses on the state of knowledge arising after preparation of the 2019 IPCC Special Report on the Ocean and Cryosphere in a Changing Climate and highlights prospects to address urgent needs. The intent is to identify some key steps necessary to advance the integration of relevant multidisciplinary observations with flood modeling and infrastructure mapping to co-produce new online hazard and risk assessment tools that inform local community planning and improve science collaboration among Federal, state, and regional partners for enhanced pre-storm preparations and post-storm recovery, including partial or complete relocation. By focusing coastal data integration for delivery of priority geospatial hazard map products through a consistent yet customized approach to adaptation planning, the broad collaborative effort in Alaska may yield a path of stakeholder service delivery that can be applied to many Arctic communities and other vulnerable regions of the world.

A Coastal Flood Early-Warning System Based on Offshore Sea State Forecasts and Artificial Neural Networks

An integrated methodological approach to the development of a coastal flood early-warning system is presented in this paper to improve societal preparedness for coastal flood events. The approach consists of two frameworks, namely the Hindcast Framework and the Forecast Framework. The aim of the former is to implement a suite of high-credibility numerical models and validate them according to past flooding events, while the latter takes advantage of these validated models and runs a plethora of scenarios representing distinct sea-state events to train an Artificial Neural Network (ANN) that is capable of predicting the impending coastal flood risks. The proposed approach was applied in the flood-prone coastal area of Rethymno in the Island of Crete in Greece. The performance of the developed ANN is good, given the complexity of the problem, accurately predicting the targeted coastal flood risks. It is capable of predicting such risks without requiring time-consuming numerical simulations; the ANN only requires the offshore wave characteristics (height, period and direction) and sea-water-level elevation, which can be obtained from open databases. The generic nature of the proposed methodological approach allows its application in numerous coastal regions.