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We recently developed a dynamically coupled hydrological‐ocean modeling system that provides seamless coverage across the land‐ocean continuum during hurricane‐induced compound flooding. This study introduced a local inertial equation and a diagonal flow algorithm to the overland routing of the coupled system’s hydrology model (WRF‐Hydro). Using Hurricane Florence (2018) as a test case, the performance of the coupled model was significantly improved, evidenced by its enhanced capability of capturing backwater and increased water level simulation accuracy and stability. With four model experiments, we present a framework to detangle, define, and quantify compound and nonlinear effects. The results revealed that the flood peaks in the lower Cape Fear River Basin and the coastal waters were contributed by inland flooding and storm surge, respectively. These two processes had comparable contributions to the flooding in the Cape Fear River Estuary. The compound effect was identified when the flood levels resulting from the combination of land and ocean processes surpassed those caused by an individual process alone. The compound effect during Hurricane Florence exhibited limited impact on flood peaks, primarily due to the time lag between the peaks of the storm surge and the inland flooding. In the period between the two peaks, the compound effect was salient and significantly impacted the magnitude and variation of the flood level. The nonlinear effect, defined as the difference between the compound flood level and the superposition of storm surge and inland flooding water levels, reduced flood levels in the river channels while increasing flood levels on the floodplain. Plain Language Summary This study addresses the phenomenon of hurricane‐induced compound flooding, which arises when inland waters and storm surges coincide at the land‐ocean boundary. We’ve devised a hydrological‐ocean model that effectively covers such events. This model, enhanced with new algorithms, was tested using Hurricane Florence (2018) data, showing marked improvements in predicting water levels and tide effects. Our research delineates and quantifies the complex interplay between different flooding sources during such events. Key findings include the determination that both inland flooding and storm surges contributed equally to the flooding in the Cape Fear River Estuary. However, the overlapping impact of these processes, termed the “compound effect,” was limited in its influence on peak flood levels, mainly due to the time gap between storm surge and inland flooding peaks. Another crucial discovery was the “nonlinear effect,” which accounts for discrepancies in predicted flood levels. This effect tended to decrease flood levels in river channels but increased them on floodplains. Key Points A local inertial equation and a diagonal flow algorithm were introduced to a newly developed dynamically coupled hydrological‐ocean model Strong compound effect between hydrological and ocean processes occurred between their peaks The nonlinear effect reduced the flood peaks in the river channels while amplifying them on the floodplains

Tropical cyclones are one of the most destructive natural hazards and much of the damage and casualties they cause are flood-related. Accurate characterization and prediction of total water levels during extreme storms is necessary to minimize coastal impacts. While meteotsunamis are known to influence water levels and to produce severe consequences, their impacts during tropical cyclones are underappreciated. This study demonstrates that meteotsunami waves commonly occur during tropical cyclones, and that they can contribute significantly to total water levels. We use an idealized coupled ocean–atmosphere–wave numerical model to analyze tropical cyclone-induced meteotsunami generation and propagation mechanisms. We show that the most extreme meteotsunami events are triggered by inherent features of the structure of tropical cyclones: inner and outer spiral rainbands. While outer distant spiral rainbands produce single-peak meteotsunami waves, inner spiral rainbands trigger longer lasting wave trains on the front side of the tropical cyclones. Tropical cyclones can cause severe damage, in particular through flooding of coastal areas. Here, the authors show that in addition to known impacts, tropical cyclone rainbands can cause meteotsunami waves that can contribute significantly to the total water levels and hence flooding risks.

Hurricane‐induced compound flooding is a combined result of multiple processes, including overland runoff, precipitation, and storm surge. This study presents a dynamical coupling method applied at the boundary of a processes‐based hydrological model (the hydrological modeling extension package of the Weather Research and Forecasting model) and the two‐dimensional Regional Ocean Modeling System on the platform of the Coupled‐Ocean‐Atmosphere‐Wave‐Sediment Transport Modeling System. The coupled model was adapted to the Cape Fear River Basin and adjacent coastal ocean in North Carolina, United States, which suffered severe losses due to the compound flood induced by Hurricane Florence in 2018. The model's robustness was evaluated via comparison against observed water levels in the watershed, estuary, and along the coast. With a series of sensitivity experiments, the contributions from different processes to the water level variations in the estuary were untangled and quantified. Based on the temporal evolution of wind, water flux, water level, and water‐level gradient, compound flooding in the estuary was categorized into four stages: (I) swelling, (II) local‐wind‐dominated, (III) transition, and (IV) overland‐runoff‐dominated. A nonlinear effect was identified between overland runoff and water level in the estuary, which indicated the estuary could serve as a buffer for surges from the ocean side by reducing the maximum surge height. Water budget analysis indicated that water in the estuary was flushed 10 times by overland runoff within 23 days after Florence's landfall. Plain Language Summary Compound flooding refers to a phenomenon in which two or more flooding sources occur simultaneously or subsequently within a short period of time. In this study, we present a new numerical model that combines hydrological and ocean models to represent the exchange of water levels at the land‐ocean interaction zone. To test the model's robustness, we use this model to simulate the water level changes in Cape Fear River Basin and adjacent coastal ocean in North Carolina, United States, for Hurricane Florence in 2018. The comparison between observed and simulated water level prove that the new model can better resolve the changes in water elevation during a hurricane event than the traditional method where the ocean model utilized the river model's outputs as its boundary condition. We further quantify the contributions from different processes to the water level variations in the estuary. The compound flooding in the estuary was categorized into four stages: (I) swelling, (II) local‐wind‐dominated, (III) transition and (IV) overland‐runoff‐dominated. The estuary could serve as a buffer for surges from the ocean side by reducing the maximum surge height. The water in the estuary was flushed 10 times by overland runoff within 23 days after Florence's landfall. Key Points A coupled hydrological‐ocean model was developed using hydrological modeling extension package of the Weather Research and Forecasting model (WRF‐Hydro) and two‐dimensional Regional Ocean Modeling System (ROMS 2D) through the Coupled‐Ocean‐Atmosphere‐Wave‐Sediment Transport modeling system The dynamical coupling method was applied to the interface boundary of WRF‐Hydro and ROMS 2D to realize a seamless model coupling Hurricane Florence‐induced compound flooding event was investigated by analyzing the modeled water level evolution, water budget, and nonlinear effects in the Cape Fear Estuary

Infragravity waves are key components of the hydro‐sedimentary processes in coastal areas, especially during extreme storms. Accurate modeling of coastal erosion and breaching requires consideration of the effects of infragravity waves. Here, we present InWave, a new infragravity wave driver of the Coupled Ocean‐Atmopshere‐Waves‐Sediment Transport (COAWST) modeling system. InWave computes the spatial and temporal variation of wave energy at the wave group scale and the associated incoming bound infragravity wave. Wave group‐varying forces drive free infragravity wave growth and propagation within the hydrodynamic model of the coupled modeling system, which is the Regional Ocean Modeling System (ROMS) in this work. Since ROMS is a three‐dimensional model, this coupling allows for the combined formation of undertow currents and infragravity waves. We verified the coupled InWave‐ROMS with one idealized test case, one laboratory experiment, and one field experiment. The coupled modeling system correctly reproduced the propagation of gravity wave energy with acceptable numerical dissipation. It also captured the transfer of energy from the gravity band to the infragravity band, and within the different infragravity bands in the surf zone, the measured three‐dimensional flow structure, and dune morphological evolution satisfactorily. The idealized case demonstrated that the infragravity wave variance depends on the directional resolution and horizontal grid resolution, which are known challenges with the approach taken here. The addition of InWave to COAWST enables novel investigation of nearshore hydro‐sedimentary dynamics driven by infragravity waves using the strengths of the other modeling components, namely the three‐dimensional nature of ROMS and the sediment transport routines. Plain Language Summary Infragravity waves have periods between 25 and 250 s and are the result of wind‐wave groups, or “sets.” When wind‐waves of similar periods travel together, they group, resulting in varying wave heights within the groups. This wave height variation at the group scale forces ocean surface infragravity waves. Coastal circulation, flooding, sand transport, and erosion are strongly influenced by these infragravity waves, especially during extreme storms. Therefore, it is important that we are able to model infragravity waves. We present a novel infragravity wave component of the Coupled‐Ocean‐Atmosphere‐Wave‐Sediment Transport (COAWST) modeling system: InWave. By coupling InWave and a circulation model, COAWST is now able to account for the main processes needed to predict coastal hazards due to extreme storms. This new coupled system is verified by reproducing observations from idealized numerical cases, a laboratory experiment on dune erosion, and a field experiment. Results show a good agreement with observations. Key Points InWave is a new infragravity wave driver of the Coupled Ocean‐Atmosphere‐Wave Sediment Transport (COAWST) modeling system Coupling InWave with the Regional Ocean Modeling System within COAWST enables the modeling of infragravity waves and three‐dimensional flows The coupled system is verified by reproducing laboratory and field observations, with good hydrodynamic and morphodynamic performance

Despite recent advancements in ocean–wave observations, how a tropical cyclone’s (TC’s) track, intensity, and translation speed affect the directional wave spectra evolution is poorly understood. Given the scarcity of available wave spectral observations during TCs, there are few studies about the performance of spectral wave models, such as Simulating Waves Nearshore (SWAN), under various TC scenarios. We combined the National Data Buoy Center observations and numerical model hindcasts to determine the linkages between wave spectrum evolution and TC characteristics during hurricanes Matthew 2016, Dorian 2019, and Isaias 2020. Five phases were identified in the wave spectrogram based on the normalized distance to the TC, the sea–swell separation frequency, and the peak wave frequency, indicating how the wave evolution relates to TC characteristics. The wave spectral structure and SWAN model’s performance for wave energy distribution within different phases were identified. The TC intensity and its normalized distance to a buoy were the dominant factors in the energy levels and peak wave frequencies. The TC heading direction and translation speed were more likely to impact the durations of the phases. TC translation speeds also influenced the model’s performance on swell energy. The knowledge gained in this work paves the way for improving model’s performance during severe weather events.

Improving nitrogen use efficiency from nitrogen-based fertilizers is key in managing nutrient supply to agricultural crops. This work explores the potential of noncovalent derivatives (NCDs) as components of sustainable slow release nitrogen fertilizers. Six distinct crystalline forms were prepared through the slow evaporation of urea with the co-formers; adipic acid, pimelic acid, suberic acid, azelaic acid and sebacic acid. Each form was characterized using a suite of analytical techniques with three novel crystalline structures identified. Formation of NCDs with urea and dicarboxylic acids effectively slowed the release of urea in water. Moreover, increasing the carbon chain length of the dicarboxylic acid co-former correlated with reduction in the urea release rate by up to 4-fold compared with regular granular urea. These results provide a proof of concept that noncovalent derivatization technology holds promise as a viable approach for slowing urea release from nitrogen-based fertilizers, thereby enhancing soil and plant nitrogen retention.

This paper describes the importance of wave‐current interaction in an inlet‐estuary system. The three‐dimensional, fully coupled, Coupled Ocean‐Atmosphere‐Wave‐Sediment Transport (COAWST) modeling system was applied in Willapa Bay (Washington State) from 22 to 29 October 1998 that included a large storm event. To represent the interaction between waves and currents, the vortex‐force method was used. Model results were compared with water elevations, currents, and wave measurements obtained by the U.S. Army Corp of Engineers. In general, a good agreement between field data and computed results was achieved, although some discrepancies were also observed in regard to wave peak directions in the most upstream station. Several numerical experiments that considered different forcing terms were run in order to identify the effects of each wind, tide, and wave‐current interaction process. Comparison of the horizontal momentum balances results identified that wave‐breaking‐induced acceleration is one of the leading terms in the inlet area. The enhancement of the apparent bed roughness caused by waves also affected the values and distribution of the bottom shear stress. The pressure gradient showed significant changes with respect to the pure tidal case. During storm conditions the momentum balance in the inlet shares the characteristics of tidal‐dominated and wave‐dominated surf zone environments. The changes in the momentum balance caused by waves were manifested both in water level and current variations. The most relevant effect on hydrodynamics was a wave‐induced setup in the inner part of the estuary. Key Points The three‐dimensional, wave‐current, COAWST modeling system was applied in Willapa Bay Interaction between waves and currents represented by the vortex‐force method The inlet shares the characteristics of tidal and surf zone environments

In response to environmental concerns and restrictions on isocyanate-based materials, researchers and the coatings industry are focused on developing eco-friendly isocyanate-free polyurethanes. This article introduces a novel class of environmentally-friendly, initiator/catalyst-free, UV-curable, self-healing non-isocyanate polyurethanes (NIPUs) synthesized from bio-based carbonated soybean oil (CSO) and non-toxic coumarin. The synthesis of these polymers is based on using a photo-reactive coumarin that undergoes a reversible [2 + 2] cycloaddition upon exposure to the wavelength of UV light. UV-curable three coumarin-terminated isocyanate-free polyurethane prepolymers were synthesized using CSO and three different amines and epoxy coumarin. Subsequently, a set of cross-linked NIPU polymers were obtained with exposure of 365 nm UV irradiation. The photo-reversible nature of these polymers was investigated in response to various wavelengths of UV radiation. Additionally, their self-healing ability and the thermal and mechanical properties of NIPU coatings were studied using optical microscopy, thermogravimetric analysis, differential scanning calorimetry, and a universal testing machine. The outcomes demonstrate that this polyurethane has the potential to provide a sustainable alternative to isocyanate-based materials. Two examples of stimulated healing are given, that of healing a scratch and the other being the healing of a sample that has been mechanically stressed to failure in a tensile mode.

We demonstrate the increased ability to forecast hurricane impacts with a coupled numerical modeling system by simulating ocean waves, water levels, currents, sediment transport, and structural damage to predict inundation, coastal morphological change, and residential building impacts. The Coupled‐Ocean‐Atmosphere‐Waves‐Sediment‐Transport (COAWST) modeling system is applied to simulate Hurricane Michael (category 5, 2018) that made landfall near Tyndall Air Force Base, FL, in the northern Gulf of America, causing severe devastation and flooding. Atmospheric forcings from the Coupled Ocean/Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS‐TC) are used to drive the ocean and wave models on a series of nested grids. Results identify that coastal inundation at Mexico Beach is due to surge from winds and waves, supplemented by pulses of infragravity wave motions that propagate landward into the inundation region. Seed lines observed on interior building walls also demonstrate variable changes in water level. In addition, a machine learning model was applied to hindcast structure damages, caused mostly by waves and winds, with a 72% accuracy estimate of substantial damage in proximity of landfall. The storm also created a breach across Cape San Blas, the adjacent barrier spit, due to large surge and low dune elevations. Dune locations with vegetated land cover are shown to reduce wave‐energy dissipation and reduce erosion, whereas locations without land cover had increased breaching potential. The breach occurred during the maximum ocean‐side water level, and the delayed high water on the bay side allowed a pressure gradient to drive flow seaward and promote breach development. Plain Language Summary Hurricane Michael impacted the areas near Mexico Beach and Cape San Blas along the Florida panhandle in October 2018. The hurricane was the strongest storm on record to impact that region at that time, devastated the infrastructure, and created erosion and breaching along the coastline. Numerical modeling of the storm identified that the surge was enhanced due to the occurrence of lower frequency waves that pulsed water into the region. Damage to structures in the landfall area was accurately predicted with a machine‐learning model. The area of the breach occurred at a low dune elevation, and coastal vegetation on the dune reduced the storm impacts. Key Points Modeled infragravity wave water levels have stronger agreement to high‐water marks than using phase averaged models Barrier island breaching was constrained by land cover and sustained due to ocean versus back‐bay water‐level phase differences Machine learning model was 72% accurate to hindcast structures impacts near Mexico Beach

Hurricanes interact with the Gulf Stream in the South Atlantic Bight (SAB) through a wide variety of processes, which are crucial to understand for prediction of open-ocean and coastal hazards during storms. However, it remains unclear how waves are modified by large-scale ocean currents under storm conditions, when waves are aligned with the storm-driven circulation and tightly coupled to the overlying wind field. Hurricane Matthew (2016) impacted the U.S. Southeast coast, causing extensive coastal change due to large waves and elevated water levels. The hurricane traveled on the continental shelf parallel to the SAB coastline, with the right side of the hurricane directly over the Gulf Stream. Using the Coupled Ocean–Atmosphere–Wave–Sediment Transport modeling system, we investigate wave–current interaction between Hurricane Matthew and the Gulf Stream. The model simulates ocean currents and waves over a grid encompassing the U.S. East Coast, with varied coupling of the hydrodynamic and wave components to isolate the effect of the currents on the waves, and the effect of the Gulf Stream relative to storm-driven circulation. The Gulf Stream modifies the direction of the storm-driven currents beneath the right side of the hurricane. Waves transitioned from following currents that result in wave lengthening, through negative current gradients that result in wave steepening and dissipation. Wave–current interaction over the Gulf Stream modified maximum coastal total water levels and changed incident wave directions at the coast by up to 20°, with strong implications for the morphodynamic response and stability of the coast to the hurricane.