2024 USCRP Funded Projects

Physically Informed, Equitable, and Efficient Hurricane Surge Characterization

In the artificial intelligence era, storm surge surrogate models have emerged as a promising way to overcome the computational burden associated with the robust probabilistic coastal hazard assessments (PCHA) on which communities rely for planning, risk-based design, and emergency management. Yet, little attention has been given to (a) characterizing the distribution of error associated with these models; (b) understanding how well these models perform in the context of expected natural structure of storm surge, over a range of storms and geographic settings; and (c) understanding how model error impacts social equity and resilience. The project goal is to leverage existing data to advance the science of PCHA through development of a holistic approach for equitable, physically informed, and transparent storm surge surrogate modeling. The research objectives are to: (O1) Understand how the performance of existing and novel surrogate modeling approaches depends on storm surge physics and storm training set and (O2) Understand how socioeconomic equity and resilience are impacted by geospatial variation in surrogate model error, while pursuing the training objective of (O3) Training students in coastal engineering and broadening their understanding of how scientific decisions impact social equity. Outcomes have potential to transform PCHA by enabling a quantitative focus on socioeconomic equity, redirecting attention to what matters most for community resilience—people.

Dr. Jennifer Irish, Dr. Michelle Bensi, and Dr. Yang Shao

Photo Description:  Potential inequities in surge surrogate model error in Tampa, FL region. Oval shows area of coincident high error and poverty. Preliminary sample results based on data from U.S. Census Bureau (2024) and U.S. Federal Emergency Management Agency (2016).

Climate Resilience and Adaptation of Communities to Storm-Related Flooding in the US Great Lakes Watershed 2024

The “Climate Resilience and Adaptation of Communities” project is Phase 2 of a

USCRP-funded project entitled “Identifying and Communicating Coastal Impacts of

Storm-Related Events... in the ...Great Lakes” (ICCI-Great Lakes) which developed

individual and community-level Climate Resilience and Adaptation Guidance (CRAG)

and associated decision support tools which guide people through the process of

identifying their home vulnerabilities, and then brainstorming and prioritizing potential

resilience adaptations. A Climate Resilience and adaptation Spatial Information

Database (CRASID) was also created to identify specific areas of high vulnerability in

the US Great Lakes watershed based on overlapping human and critical infrastructure risks due to flooding and socioeconomic vulnerabilities. The CRASID plays a dual role of enabling people to identify whether their homes and local personally important critical

infrastructure, like schools or local emergency shelters and hospitals, are also at risk of flooding. ICCI-Great Lakes Phase 2 will enable us to develop these tools into an

integrated set of decision support tools that both facilitate home adaptation planning and actions to increase climate (severe storm and flood) resilience and enable people to plan safe evacuation routes that can take into account needed stops like collecting people from work, school or day care on their way to a safe location. The spatial database will be revised based on user feedback and be made accessible through a web accessible, platform-flexible user interface, and the CRAG and decision support tools will be revised based on feedback and new versions will be created for apartment dwellers and small businesses.

Dr. Diane Henshel

Photo Description: Water covers a traffic light ahead sign. Photo from Unsplash.

Analyzing and Modeling Hybrid Dune Resilience to Energetic Waves

Rising sea levels and intensifying wave climatology necessitate novel coastal infrastructure. Living shorelines are nature-based features that serve as coastal protection while simultaneously enhancing habitat. Historically, living shorelines have been implemented in low to moderate wave energy environments, with only minimal implementations in exposed, high energy wave environments (i.e., Pacific). Here, over five years of quarterly and event-based observations of a novel dune-based living shoreline have been collected. This proposal seeks to process and analyze multi-substrate dune response to energetic (i.e., long period) wave events. The analysis will be extended to propose and validate a modeling methodology for hybrid dune-based living shoreline structures in high-energy wave climates. An undergraduate will pre-process sUAS data and identify erosion events. A graduate student will process, quality control, and analyze all living shoreline data. She will then use this data to develop a modeling methodology characterizing multi-substrate dune response to energetic wave events. This research specifically addresses extreme event understanding, explores a new science question characterizing hybrid dune response to energetic, long period wave events, and develops modeling methodologies for future dune response.

Dr. Timu Gallien

Photo Description: Coastal Flood Lab Post-event Surveying at Cardiff State Beach  

How colliding forces change: The influence of climate and geography on flood transition zones

  This project focuses on quantifying the variation in location and extent of flood transition zones, where compounding river and coastal conditions drive flooding, at a set of rivers in the southern United States. We will utilize data developed during the previously funded USCRP project, “When forces collide: Developing a scalable framework for compound flood risk assessment” which includes ten synthetic statistical simulations of river and coastal water level boundary conditions, each representing 10,000 years of storm events, 1000s of hydraulic model runs based on existing FEMA-provided HEC-RAS models, and surrogate models for linking the hydraulic models with statistical simulations, resulting in millions of estimates of along-river water surface elevation. With this data, we will evaluate the merits of different statistical approaches for characterizing compounding flood drivers, characterize transition zones in the floodplain in addition to the river channel, and account for shifts in the flood transition zone due to climate change. Ultimately, our research will help to quantify properties of the flood transition zone necessary to include in more detailed modeling applications, and whether they vary geographically, important details for building resilience to changing extremes.

Dr. Katy Serafin, Dr. Thomas Wahl, and Dr. Robert Jane

Photo Description: Schematic of the flood transition zone along a coastal river.

Identifying At-Risk Habitats for Walleye, Yellow Perch, and Lake Whitefish in the U.S. Great Lakes Amid Aquatic Invasive Species Impacts

Great Lakes’ coasts are crucial for native fishes as they provide spawning and nursery habitat, foraging opportunity, and serve as a haven from predation. Aquatic invasive species (AIS) have invaded the Great Lakes at the highest rate recorded for a freshwater ecosystem and are degrading native fish habitat, spreading disease, altering food webs, and acting as predators. These pervasive interactions are of great concern for Walleye Sander vitreus, Yellow Perch Perca flavescens, and Lake Whitefish, Coregonus clupeaformis as these species hold considerable cultural and economic value to surrounding communities. An understanding of suitable habitat distribution for the focal species is a management priority; however, few studies on ideal habitats for these species have accounted for AIS. We will fill this gap by (1) using a comprehensive historical and current database on AIS to identify the AIS which have potential direct and indirect impacts on the three focal native species, (2) analyzing the extent of habitat overlap in the Great Lakes between these invasives and the three focal native species, (3) identifying any existing uninvaded or minimally invaded habitats (refugia), and (4) using historical trajectories of invasion to pinpoint areas within suitable uninvaded habitats where invasive species may move. These steps will allow us to determine the level of risk to the three focal species, need for management across habitats, and ideal stocking locations in the Great Lakes.

Dr. Silvia Newell

Photo Description: (photo credit Monte Consulting/Michigan Sea Grant) 

Performance Evaluation of Nature-based Retrofits for Hardened Shorelines and Impacts on Adjacent Properties

Hardened elements such as bulkheads and seawalls are, and are likely to remain, a prominent feature of coastal shorelines. However, such infrastructure often leads to erosion locally and at adjacent areas, which ultimately diminishes the natural benefits of coastal habitats. In response, land-managers have begun to implement various softening techniques (i.e., living shorelines retrofits) in an attempt to stabilize sediments and otherwise enhance the habitat value of affected areas. While there is some evidence of the potential positive impacts of retrofits (i.e., shoreline stabilization and ecological benefits), such designs have not been critically evaluated to determine their effects on wave responses (e.g., wave energy attenuation) or sediment transport process. The proposed study seeks to address this data gap by investigating the effects of common retrofit designs, such as planter boxes, seaward marsh planting, and green riprap, on wave and geomorphic responses. This study will also explore the potential impacts of designs on sediment transport processes using numerical modeling.

Dr. Nigel Temple, Dr. Stephanie Patch, and Dr. Bret Webb

Photo Description: The wave flume at the Center for Applied Coastal Engineering and Science at the University of South Alabama will be used to investigate wave and geomorphic responses to different living shorelines retrofit designs for hardened infrastructure. Photo Credit: Bret Webb.

An investigation of morphodynamic long-term variability at Waikīkī Beach

This project addresses the data and knowledge gap of multi-decadal beach morphological datasets by first developing statistical relationships between a 3-year database of weekly beach surveys and offshore wave conditions and then extrapolating the statistical model to estimate probable multi-decadal time series of beach states at the densely populated, Waikīkī Beach. The results from this tropical, calcareous sand beach will be compared with quartz sand beaches on the East Coast (e.g. Duck, NC). The proxy time series estimated from the statistical model will be verified with the sparse geo-rectified aerial photographs starting in 1949. The multi-decadal time series of beach states will be analyzed to elucidate the inter-annual variability of coastal processes and be used to guide local beach maintenance activities related to beach nourishment or expansion plans to stabilize the shoreline with coastal infrastructure. The project educates a graduate student towards an MS degree from the Ocean and Resources Engineering (ORE) Department and collaborates with coastal geologists and a Waikīkī Beach management coordinator for broader impacts.

Dr. Justin Stopa

Photo Description: (a) shows an example orthomosaic of Waikīkī Beach collected from a drone survey and generated from photogrammetry techniques. b) shows the derived elevations generated by geo-rectifying the imagery to ground control points.

Coastal Resiliency in Salt Marshes and Marine Vegetated Environments

Coastal wetlands (such as salt marshes) are critically important to maintaining a healthy

coastal ecosystem and protecting communities from storms. However, current rates of

sedimentation in salt marshes are not high enough to keep up with sea level rise

estimates. The projected outcome is a change in the nature of the system, including

transitions from high to low marsh, and low marsh to mud flat. These transitions alter

the estuarine habitat, reduce (or eliminate) ecosystem services provided by a healthy

marsh ecosystem, and negatively impact resiliency of coastal communities including

increased flood risk and storm damage. Human communities need strategies for

maintaining and building natural infrastructure, and require an understanding of how

suspended sediment is dispersed and deposited in complex marine vegetated systems.

The goal of the project is to address these needs by utilizing previously collected field

and laboratory data at both small- and large-scales, and with numerical simulations from

publicly available hydrodynamic models. The field data to be used in this study were

obtained under previous USCRP funding in the NH Hampton/Seabrook Estuary and in

Barnegat Bay, NJ, estuarine systems that contain a range of mudflats, low and high

marshes, and artificial oyster reefs. Results will provide insight into salt marsh and

shoreline sedimentation processes with implications to long term coastal resiliency

under sea level rise.

Dr. Thomas Lippmann, Dr. Jang-Geun Choi, Dr. Tracy Mandel, Dr. Michael Palace, Dr. David Burdick, and Dr. Longhuan Zhu

Photo Description: (left) Satellite image of HSE. (middle) Aerial views of the extensive marsh under low tide (top), high spring tide (middle), and regularly occurring nuisance flooding (bottom). (right) Satellite image of Barnegat Bay and photo of floating oyster farms.

Quantifying and Understanding the Lake Michigan Shoreline Response Associated with an Extreme Water Level Increase

This project examines the Lake Michigan shoreline response to a record-breaking extreme water level event that occurred between 2013 and 2020, during which the water level rose nearly 2m. To quantify the Lake Michigan coastal response, this project leverages a newly-available USACE topobathymetric survey from 2020, combined with a previous survey in 2013, that together perfectly span the extreme event. The project aims to quantify and understand the Lake Michigan shoreline response, in order to help Great Lakes communities be more prepared for future events. A major component of the project, on equal footing with the science objectives, is the development of a Great Lakes Graduate Student Community of Practice, which leverages expertise at four Great Lakes institutions to produce an empowered next generation of Great Lakes coastal scientists and engineers.

Dr. Cary Troy, Dr. Ethan Theuerkauf, Dr. Guy Meadows, Ryan Williams, Dr. Chin Wu, and Dr. Lucas Zoet 

Photo Description: Dune erosion resulting from high water levels in Lake Michigan, in Dune Acres, IN (photo courtesy of Dr. Cary Troy)

 Assessing Compound Flood Impacts on Groundwater Levels in Coastal Urban Communities

High tidal events co-occurring with intense rainfall can produce substantial flooding in coastal urban communities, such as Tybee Island (GA). To mitigate this flooding impact on the community, engineers design flood resiliency measures that could include traditional structures (culver, pipes, pumps), as well as natural infrastructure (rain gardens, bio-swales, and bio-retention). These structures have been well studied and designed for inland communities with no risk of coastal flooding. However, tides and rising sea levels could influence the groundwater levels around coastal communities, reducing natural infrastructure capacity to soak the rainfall-runoff. Therefore, this proposal seeks to study the relationship between sea-level rise, tides, rainfall, and groundwater levels to improve natural infrastructure guidelines and implementation along GA coastal communities. To achieve this, we will use data collected from different groundwater wells around the GA coast, with a special emphasis on Tybee Island due to its data availability and relevance to the community, as well as numerical models, including hydrodynamic models and machine learning. Furthermore, community engagement activities will center around Tybee Island’s residents (and surrounding communities) to tailor the research outcomes to their needs. The outcomes of this proposal will greatly help Tybee Island’s Natural Infrastructure plan by providing specific recommendations for the design of their rain gardens for the current and future climate, as well as to the other GA coastal communities with similar threats.

Dr. Felix Santiago-Collazo, Dr. Adam Milewski, Mrs. Jessica Brown, and Dr. Carol Pride

Photo Description: Drone image of Tybee Island and its back marsh looking towards the east (Photo Credit: Daniel Buhr).

 Automated sediment characterization to understand long-term coastal change in response to human interventions

Sediment characteristics, such as sediment composition and grain size, are a fundamental property of coastal systems, exerting control on storm response and recovery, habitat availability, efficacy of restoration efforts, and long-term coastal evolution. However, availability of large spatial extents or long time series of observations of sediment characteristics have been limited by challenges in collecting and analyzing sediment samples, particularly in mixed sediment environments. We propose to integrate, improve, and apply existing machine learning models and statistical image analysis techniques for qualitative and quantitative characterization of mixed beach sediments to understand long-term evolution of a coastal system impacted by human intervention. We will leverage a 14-year database of sediment images collected monthly to annually with high spatial resolution over the Elwha River delta and adjacent, downdrift coastlines (WA) following the undamming of the Elwha River, which released 18 million tons of sediment to the coast. Analyses of these images alongside existing topobathy profiles will enable us to examine the co-evolution of sediment characteristics and beach morphology over seasonal to decadal timescales. All datasets produced within this project will be published as they are created, and methods will be developed using open-source principles.

Dr. Christie Hegermiller and Dr. Ian Miller

Photo Description: The removal of two dams along the Elwha River released 18 million tons of sediment to the coast, where fine sediments were transported away by strong tidal currents and coarser sediments accumulated in a delta, seen here by satellite in 2013. In the inset, nine images of beach sediments were segmented into cobble, gravel, sand, and “other” classes as a preliminary step in characterizing the sediment. 

A Multi-Decadal Re-Analysis of Water Quality and Health Risks In An Urban, Coastal Watershed With Changing Precipitation

This project will synthesize and re-investigate multiple decades of existing coastal monitoring and precipitation data from New York Harbor and the Hudson River Estuary. We will quantify the response of water quality to rainfall across timescales ranging from days to decades using water quality parameters representing point-source and non-point source contaminants and investigate how ongoing long-term shifts in rainfall frequency and magnitude affect water quality and human health risks in this urban, coastal environment that is home to approximately 20 million people. Statistical re-sampling of the large water quality data set generated after combining multiple existing data sources will be used to evaluate how spatial and temporal data aggregation affect projections of water quality in response to changing precipitation for different subwatersheds and along urban to suburban gradients. A secondary focus will be to assess the effects of individual extreme precipitation events (including records of several tropical cyclones hitting the region during the existing data record) on precipitation vs. water quality relationships. Students from a Hispanic-serving institution (CUNY Queens College) will take on leadership roles in organizing and analyzing large data sets and project outreach activities to help prepare the next generation of coastal environmental scientists.

Dr. Andrew Juhl and Dr. Gregory O’Mullan

Photo Description: Cloudy Manhatten skyline. 

Implementing species-specific root traits into hydrodynamic and geomorphological models of marsh evolution to understand Blue Carbon dynamics

Coastal wetlands are valuable ecosystems that provide economic, environmental, and cultural benefits. A range of salinities results in a series of marshes with different vegetation communities, representative of their salinity. These marshes are dependent on vertical accumulation of both organic and mineral material in order to survive high rates of sea level rise. However, long-term predictions of marsh morphodynamics do not account for complex distribution of organic content. In fact, marsh plants distribute organic content not only to the top layer of the sediment, but within the soil. This distribution depends on the plant species, but the details on the vertical distribution of below-ground biomass (i.e., the roots) is difficult to measure. Therefore, we propose to (1) develop species-specific below-ground biomass curves based on bulk density and (2) implement these relationships in a coupling of two existing numerical models – an ecological model of plant community composition and a geomorphic model of marsh systems. We hypothesize that the different root structures of plants will affect the elevation of marshes and result in differing morphodynamic responses along a salinity gradient. The results of this work will develop plant root relationships that can be implemented in any marsh model and demonstrate the morphodynamic impacts of plant community composition and their roots on long-term marsh evolution.

Dr. Kendall Valentine and Dr. Madeline Foster-Martinez

Photo Description: Photos of sediment cores from coastal Louisiana from both brackish and saline marshes. In the brackish marshes, the root material is finer and more distributed through the 25-cm cores, while in the saline marshes the roots are thicker. 

 Probabilistic predictions of rainfall associated with tropical cyclones over land

This proposal focuses on the development of a probabilistic rainfall generator for tropical cyclones (TCs) during and after landfall along the U.S. Territories and Caribbean Islands, and the Pacific Rim for advancing the flood hazard estimation supported by the USACE Coastal Hydraulics Laboratory (CHL), for example through the Coastal Hazards System (CHS). The proposed work will develop a data-driven multiplicative model relating observed rainfall to the rainfall obtained from a parametric TC rainfall model; the relationship between observed and modeled TC rainfall can be described through the product of a deterministic and a stochastic component. 

There are multiple hazards associated with landfalling TCs, including storm surge, heavy rainfall, and riverine flooding, leading to compound extreme events. While much of the existing emphasis is on hydrodynamic modeling and storm surge, much less effort has been dedicated to the development of a probabilistic TC rainfall generator. This proposal aims at bridging this existing gap and augmenting the capabilities of the CHS environment to include rainfall associated with these storms.

Dr. Gabriele Villarini

Photo Description: Image of Hurricane Florence on September 12, 2018 (Source: NASA)