Peter Stempel

While levees safeguard over 23 million people and trillions of dollars in property, a profound, largely unrecognized flood risk crisis is emerging. Because approximately 75% of surveyed levees remain unaccredited, millions live behind levee systems that may not meet minimum federal safety standards. To overcome this accreditation bottleneck, this commentary translates research‐driven opportunities into a prioritized, three‐phase operational roadmap. First and most critically, regulators must transition from deterministic models to risk‐based probabilistic frameworks that leverage economic indicators to guide local interventions. In the mid‐term, engineering practices must integrate technical innovations, such as non‐invasive geophysical field testing methods and artificial intelligence, alongside hybrid green‐gray infrastructure solutions. Finally, achieving long‐term resilience requires embedding transdisciplinary coproduction and design‐centered alternatives into local governance. Ultimately, this framework moves beyond ‘check the box’ accreditation toward a holistic understanding of levee performance, equity, and community contexts, offering levee communities, management agencies, regulators, and researchers actionable pathways to safer, more resilient flood protection nationwide.

This paper discusses consequence prediction data useful to local emergency managers (EMs) when pre­paring for major coastal storms (hurricanes, tropical storms, nor’easters). Following an implementation research approach, findings are presented from a 2023 survey of 49 state and local EMs conducted in the New England region. Results suggest the categories of criti­cal infrastructure (CI) of greatest interest to local EMs. Results further indicate how respondents feel access to data can help them reduce unanticipated storm con­sequences. The progressive effects of climate change, together with growing societal dependence on complex CI, make it increasingly difficult for EMs to predict specific consequences of storms for coastal communi­ties. Advancements in high-resolution storm simula­tion and consequence modeling can help EMs make preparedness and response decisions, but these tools do not always deliver localized, actionable data, or they may deliver an overwhelming volume of informa­tion that is difficult to apply. To address the resulting data gap, researchers need to better understand end users’ data needs. The presented research leverages the Coastal Hazards Analysis, Modeling, and Prediction (CHAMP) project to explore the practical application of decision support tools to improve local storm pre­paredness and response. Results include best practices for simulation-based decision support tools based on stakeholder and end user input. This work contributes to a better understanding of EMs’ storm vulnerability assessments and informs continued development of decision support tools like CHAMP.

We discuss the novel application of homeland security functional exercises to evaluate emergency managers’ use of simulation-based decision support tools for response to major coastal storms (e.g., hurricanes, tropical storms, nor’easters), such as Hurricane Katrina. The U.S. Department of Homeland Security’s “Homeland Security Exercise and Evaluation Program” (HSEEP) is the universally accepted standard for emergency management exercises in the United States and provides a templated format familiar to emergency management practitioners. Using HSEEP in a scenario-based approach to end-user evaluation provides a plausible, realistic environment that encourages open and honest player feedback. We present the results of two HSEEP-based functional exercises run as part of implementation research with the Coastal Hazards Analysis, Modeling, and Prediction (CHAMP) system. CHAMP combines high-resolution storm models with a database of critical infrastructure vulnerabilities to predict storm consequences and aid decision-making. Findings suggest that the HSEEP exercise format provides a ready-made process for evaluating emergency management tools in a format comfortable and familiar to participants. User feedback and observation data collected during the CHAMP workshops and exercises are used to inform real-world activation protocols and to guide ongoing development of the CHAMP system.

Introduction: Computer-based decision support tools (DSTs) are indispensable to emergency managers (EMs). Despite their proliferation in recent years, there is a persistent disconnect between the tools developed and their use. Developing tools with end-users has been recommended to ensure they have practical relevance and achieve widespread adoption and utilization. While existing work has primarily focused on DST development, end-user engagement in DST development and implementation has received less attention. In this paper, we review the existing literature on coastal storm DST development to determine whether and how researchers are engaging EMs in the development of DSTs and their reporting on the outcomes of these efforts. Methods: We conducted a literature review of coastal storm DST development, looking for mentions of EM engagement. Our search identified 286 articles, and the review was conducted on 65 of the articles that mentioned a DST, of which six explicitly mentioned engaging EMs in development. Results: Of the 286 articles we identified, only six articles explicitly report engaging EMs in tool development, suggesting low levels of engagement. We found limited reporting on the outcomes of these efforts. We identified four approaches from the six articles reviewed: (1) conduct a needs identify emergency managers’ needs to guide the development; (2) from a collaborative team to engage emergency managers in tool development; (3) host workshops and training exercises with emergency managers using the tool to solicit feedback; and (4) use an iterative design approach to incorporate EM feedback into the tool. Conclusion: Findings of our review reveal low levels of EM engagement reported in existing literature, which may reflect a disconnect between the tools being developed and their use by EMs. We also found limited reporting on the outcomes of these efforts, suggesting that most DSTs have yet to achieve mainstream use. Recommendations for research and practice include (1) increased reporting on the engagement of EM in DST development; (2) an assessment of the barriers related to DST development and implementation for both tool developers and EMs; (3) longitudinal studies or case studies of DST development and implementation; and (4) the creation of a standardized approach or set of best practices for DST development and implementation to increase their success.

Coastal communities are unquestionably threatened by sea level rise and storm intensification. Their vulnerability is primarily function of their exposure, increasing in time, resulting into cascading effects affecting the spatial and temporal risk variability along shorelines. Many coastal communities, fearing for their future, are considering interventions aimed at improving their resilience, in particular, Natural and Nature-Based Features (NNBF) to respect the functionality of the local ecosystem and minimize negative feedback effects, that are often induced by interventions. While such features are appealing, their long-term efficiency in a changing environment is not always anticipated, and sometimes misunderstood or overestimated. In the present study, which is sponsored by the United States (US) NOAA’s “Effects of Sea-Level Rise (SLR) 2021, Coastal Resilience” Program, building on over a decade of hazard and risk assessment studies along the US New England shoreline (e.g., Grilli et al., 2017, 2020; Schuh et al., 2023), we assess the efficiency of selected NNBF in changing climate conditions, while integrating local concerns, observed trends, and supporting local ecosystem and people’s way of life.

Coastal barrier systems act as “ecosystem engineers” (EE), naturally adapting to slowly evolving seal level rise (SLR) and wave climate by regressing or transgressing. These systems adjust their morphology in response to short-term storm events and long-term changes in mean sea level and wave climate, maintaining an equilibrium between wave forcing and shoreline morphology. While predicting short-term shoreline changes due to storm events can be done with reasonable accuracy using 2DH hydro-morphodynamic models such as XBeach, predicting long-term changes is more challenging and affected by larger uncertainties. However, both accelerated SLR and more broadly climate change increase the vulnerability of coastal communities, despite even larger uncertainties, and such predictions are becoming increasingly important.

Sandy barrier systems are highly dynamic, with the most significant natural morphological changes to these systems occurring during high-energy storm conditions. These systems provide a range of economic and ecosystem benefits and protect inland areas from flooding and storm impacts, but the persistence of many coastal barriers is threatened by storms and sea-level rise (SLR). This study employed observations and modeling to examine recent and potential future influences of storms on a sandy coastal barrier system in Nauset Beach, MA. Drone-derived imagery and digital elevation models (DEMs) of the study area collected throughout the 2023–2024 winter revealed significant alongshore variability in the geomorphic response to storms. Severe, highly localized erosion (i.e., an erosional “hotspot”) occurred immediately south of the Nauset Bay spit as the result of a group of storms in December and January. Modeling results demonstrated that the location of the hotspot was largely controlled by the location of a break in a nearshore sandbar system, which induced larger waves and stronger currents that affected the foreshore, backshore and dune. Additionally, model simulations of the December and January storms assuming 0.3 m (1 ft) of SLR showed the system to be relatively resistant to major geomorphic changes in response to an isolated storm event, but more susceptible to significant overwash and breaching in response to consecutive storms. This research suggests that both very strong isolated storm events and sequential moderate storms pose an enhanced risk of major overwash, breaching, and possibly inlet formation today and into the future, raising concern for adjacent communities and resource managers.

Predicting the consequences of a major coastal storm is increasingly difficult as the result of global climate change and growing societal dependence on critical infrastructure (CI). Past storms are no longer a reliable predictor of future weather events, and the traditional approach to vulnerability assessment presents accumulated loss in largely quantitative terms that lack the specificity local emergency managers need to develop effective plans and mitigation strategies. The Rhode Island Coastal Hazards Modeling and Prediction (RI-CHAMP) system is a geographic information system (GIS)-based modeling tool that combines high-resolution storm simulations with geolocated vulnerability data to predict specific consequences based on local concerns about impacts to CI. This case study discusses implementing RI-CHAMP for the State of Rhode Island to predict impacts of wind and inundation on its CI during a hurricane, tropical storm, or nor’easter. This paper addresses the collection and field verification of vulnerability data, along with RI-CHAMP’s process for integrating those data with storm models. The project deeply engaged end-users (emergency managers, facility managers, and other stakeholders) in developing RI-CHAMP’s ArcGIS Online dashboard to ensure it provides specific, actionable data. The results of real and synthetic storm models are presented along with discussion of how the data in these simulations are being used by state and local emergency managers, facility owners, and others.  

Beach barrier systems (BBS) act as “ecosystem engi-neers” (EE), protecting the mainland and back bays from direct wave impact and reducing storm surge and flow passing through their inlets. BBS naturally adapt to slowly evolving wave climates by regressing or transgressing. However, observations show that BBS have been destabilized during past periods of fast changes in sea level or wave climate, potentially leading to drowning of the barrier. In this respect, current predictions of large changes in future Sea Level Rise (SLR) and wave climate, combined with anthropogenic effects, are concerning as these could challenge the natural adaptability of BBS. This raises the following questions: (1) can the future protective ability of local EE be predicted? (2) can the added benefits of implementing selected Nature Based Solutions (NbS) to enhance this natural protective ability be quantified, as well as their potentially negative feedback effects? In this study, these questions are considered for the south shore of Rhode Island (RI) through numerical modeling, in part based on earlier regional storm hazard assessment (Grilli et al., 2020). Specifically, here, as part of a NOAA project (“Effects of Sea-Level Rise 2021, Coastal Resilience” program), we assess the efficiency of NbS in changing climate conditions, while integrating local concerns, observed trends, and supporting local ecosystem and people’s way of life.