Search Results (51)

The Guangdong Hong Kong Macao Greater Bay Area is a core economic region in China with a high incidence of typhoon storm surges. Its low-lying terrain and dense river networks make it vulnerable to severe disasters when typhoons overlap with astronomical tides. This study integrates typhoon, terrain, and tide level data from 2000 to 2024 to construct an ADCIRC (Advanced Circulation Model) v54.01 numerical model, identify risk factors and high-risk areas, and design and verify the effectiveness of coordinated prevention and control countermeasures. Results show that the model has reliable simulation accuracy with MAE < 0.2 m and RMSE < 0.3 m; typhoon intensity and terrain elevation are the dominant factors, with high-risk areas concentrated on the west bank of the Pearl River Estuary and Dongguan Water Town; the comprehensive “engineering + non-engineering” measures can reduce the inundation area by 60% and the inundation rate of high-risk areas from 85% to 22%, providing technical support for regional disaster prevention and control. The novelty of this study lies in the integrated approach of combining grey relational analysis and multiple linear regression to quantify the contribution of key influencing factors, coupled with scenario-based evaluation of coordinated engineering and non-engineering measures tailored to the complex terrain and river network characteristics of the GBA. Full article

Wave overtopping is one of the most complex coastal hazards to characterize in field conditions due to its high non-linearity and the interaction between unsteady hydrodynamics and wave–structure processes. To get insights into the underlying occurrence and persistence of overtopping, this study proposes an integration of numerical and data-driven models. Multi-month field observations made at a breakwater are used to investigate the hydro-meteorological parameters causing overtopping initiation and persistence. High-frequency video-derived overtopping detections are combined with coupled ADCIRC–UnSWAN (ADvanced CIRCulation–Unstructured Simulating WAves Nearshore) hindcasts to construct near-structure hydro-meteorological conditions. The results reveal a clear dynamical asymmetry showing that overtopping initiation corresponds to exceedance of crest elevation at individual wave-scale associated with elevated wave height, water level, wave steepness, and wind characteristics, whereas overtopping persistence depends on short-term temporal effects associated with wave energy, direction, and sustained water levels. Gradient-boosted decision trees, temporal convolutional networks, and Transformer models are employed, demonstrating that persistence cannot be inferred from instantaneous sea-states alone, indicating a separation of timescales between triggering and sustained overtopping dynamics. These findings provide field-scale evidence of distinct hydrodynamic regimes governing overtopping processes, highlighting the importance of temporal characteristics for understanding overtopping dynamics and developing predictive coastal hazard frameworks. Full article

Tidal-scale wave modulation is a critical yet complex process in macro-tidal estuaries. This study investigates semidiurnal wave modulations in the Changjiang River Estuary (CRE) using unique, long-term in situ observations and high-resolution ADCIRC–SWAN coupled simulations. Pronounced semidiurnal signals are identified in significant wave height (H_s), mean wave period, and wave direction. Observational results demonstrate that the modulation intensity is highest in Hangzhou Bay and the CRE mouth, decreasing gradually offshore. A key finding is that semidiurnal H_s maxima systematically coincide with peak flood currents and precede high water by approximately three hours. Long-term records confirm that this modulation persists year-round and intensifies during energetic events such as typhoons. The expression of the tidal signal depends on wave composition: wind-sea-dominated conditions exhibit stronger period modulation, whereas swell-dominated conditions favor coherent H_s modulation as kinematic tidal effects remain more apparent in the absence of strong local wind forcing. Numerical sensitivity experiments demonstrate that tidal currents are the primary driver of the observed wave modulation, while water-level effects are largely confined to shallow shoals. The results highlight that accurately reproducing the observed frequency–directional structure requires the inclusion of current-induced Doppler shifts and refraction. Beyond the classical following-current effects, the analysis suggests that the spatial deceleration of currents along the wave path acts as a kinematic trap that focuses wave action and sustains H_s intensification. This mechanism provides a physically plausible explanation for the observed phase relationship and points to the non-local nature of estuarine wave dynamics, where the wave state appears as an integrated response to cumulative current gradients along the propagation path. These findings emphasize the necessity of incorporating wave–current coupling in future coastal modeling and hazard forecasting. Full article

The risk of wave overtopping is amplifying under sea-level rise and increased frequency of extreme coastal events. Conventional empirical and physical methods for estimating overtopping characteristics are limited by site-specific assumptions, which underscores the need for robust and efficient approaches. This study develops a multiscale numerical modeling framework that couples the regional ADCIRC–UnSWAN (Advanced CIRCulation and Unstructured Simulating WAves Near-shore) model with DualSPHysics (SPH) model to simulate overtopping responses under varying sea states. ADCIRC-UnSWAN provides regional-scale hydrodynamic and wave forcing, which is nested into localized SPH model to resolve wave-structure interactions. The proposed framework accurately reproduces overtopping responses including water thickness and velocity while leveraging GPU acceleration for computational efficiency. The model outputs are further analyzed to classify overtopping hazard levels and perform probabilistic pedestrian risk as sessments that account for uncertainties in wave characteristics and human vulnerability. The results supports the development of early warning systems and provide a foundation for dynamic hazard level updates in real or near-real time, contributing to improved coastal risk governance under uncertainties. Full article

Using Hurricane Harvey as a case study, this paper uses the hurricane track, wind velocity and pressure, bathymetry, Manning’s n coefficients, tidal forcing, and storm surge results generated by the ADCIRC+SWAN model as input to construct a uniform spatiotemporal deep learning model for storm surge forecasting. The model transforms inputs into embeddings and performs feature fusion and extraction. The regression layer of the model outputs the predicted values of storm surge water elevation, station water level time series, and hurricane tracks with attributes. To analyze the model’s adaptability and robustness as a surrogate model to ADCIRC, ablation experiments are conducted on up to 10 input variables to investigate the impact of various inputs on the results. Heat maps between 3, 6, 9, and 12 h horizon prediction and targets revealed excellent performance for the large scale of nodes and multiple inputs on the training set, validation set, and test set as the surrogate model. When the model is used to forecast water levels of 12 observation stations, the 9 h forecasting horizon is generally equal to or better than the ADCIRC simulation results. When the model is used to predict hurricane tracks and attributes, the 12 h forecast horizon is relatively close to the observed values, achieving satisfactory results. This model is developed and tested using Hurricane Harvey data and storm surge results as a case study. To develop a generalized prediction model would require a large amount of data and storm surge results from many hurricanes. Full article

Taiwan is frequently affected by typhoons, which cause storm surges and wave impacts that damage sea dikes, resulting in overflow and subsequent flooding. Therefore, it is essential to analyze the damage to sea dikes caused by storm surges and wave impacts, leading to overflow, for effective coastal protection. This study employs the ADCIRC model coupled with the SWAN model to simulate storm surges and waves around Taiwan and develops a sea dike failure model that incorporates mechanisms for impact damage, run-up damage, and overflow calculation. To ensure model accuracy, three historical typhoon events were used for calibration and validation of the ADCIRC+SWAN model. The results show that the ADCIRC coupled with SWAN model can effectively simulate storm surges and waves during typhoons. Typhoon Soulik (2013) was simulated to examine a breach in the Tamsui Youchekou sea dike in northern Taiwan, and an uncertainty analysis was conducted using the Monte Carlo method and Bayesian theorem. The results indicate that when the compressive strength of the sea dike is reduced to 5% of its original strength, impact and run-up damage occur, leading to overflow. In the case of impact damage, the overflow volume due to the breach falls within a 95% confidence interval of 0.16 × 10⁶ m³ to 130 × 10⁶ m³. For run-up damage, the 95% confidence interval for the overflow volume ranges from 0.16 × 10⁶ m³ to 639 × 10⁶ m³. The ADCIRC+SWAN model is used to simulate storm surge and waves, incorporating impact damage and run-up damage mechanisms to represent concrete sea dike failure. This approach effectively models dike failure and calculates the resulting overflow. Full article

This study aims to assess the adaptability of coastal areas in the Republic of Korea to future climate change-induced flooding. Coastal areas can be susceptible to complex external factors, including rainfall, tide levels, storm surge wave overtopping, etc. The study employs an integrated approach to address this, connecting hydrological and marine engineering technologies. The models utilized in this study encompass XP-SWMM, ADCIRC, SWAN, and FLOW-3D. This study analyzed floods in 2050 and 2100, considering expected rainfall patterns, sea level rising, and an increase in typhoon intensity based on climate change scenarios for six coastal areas in the Republic of Korea. We reviewed the adaptability of flooding to climate change in each region. Full article

The present study is devoted to the analysis of extreme sea level oscillations of the Laptev Sea using the ADCIRC model. The numerical modeling is performed on a high-resolution grid and verified for sea level observations from three tide gauges. We have revealed regional characteristics of extreme sea level oscillations for different parts of the Laptev Sea coast. The maximum total sea level range was 544 cm in Ebelyakh Bay, while the minimum was 267 cm in Khatanga Bay, where maximum tidal ranges were obtained. Some areas in Khatanga Bay and Anabar Bay had maximum tidal ranges exceeding 200 cm. The study provided an estimation of the possible magnitude of coastal flooding by calculating the extreme total and residual sea levels for different return periods: 1, 2, 5, 10, 20, 50, and 100 years. The amplitude of extreme surges calculated for the 100-year return period can exceed 300 cm for several sections of the Laptev Sea coast, with the maximum sea level range being about 680 cm for Anabar and Ebelyakh Bays. Full article

Providing storm surge risk information at multi-day lead times is critical for hurricane evacuation decisions, but predictability of storm surge inundation at these lead times is limited. This study develops a method to parameterize and adjust tropical cyclones derived from global atmospheric model data, for use in storm surge research and prediction. We implement the method to generate storm tide (surge + tide) ensemble forecasts for Hurricane Michael (2018) at five initialization times, using archived operational ECMWF ensemble forecasts and the dynamical storm surge model ADCIRC. The results elucidate the potential for extending hurricane storm surge prediction to several-day lead times, along with the challenges of predicting the details of storm surge inundation even 18 h before landfall. They also indicate that accurately predicting Hurricane Michael’s rapid intensification was not needed to predict the storm surge risk. In addition, the analysis illustrates how this approach can help identify situationally and physically realistic scenarios that pose greater storm surge risk. From a practical perspective, the study suggests potential approaches for improving real-time probabilistic storm surge prediction. The method can also be useful for other applications of atmospheric model data in storm surge research, forecasting, and risk analysis, across weather and climate time scales. Full article

The vulnerability to coastal disasters resulting from storm surges and wave overtopping (WOT) during typhoon intrusions is significantly escalating due to rising sea levels. In particular, coastal seawalls constructed along the coast through engineered assessments are experiencing an increase in the frequency of WOT and associated flooding in proportion to the reduction in freeboard due to rising sea levels. This study employed a unified modeling system that combines an empirical formula for estimating WOT volumes with a numerical model simulating tides, waves, and storm surges. The analysis was conducted across the Northwest Pacific (NWP) Ocean, encompassing coastal seawalls and terrestrial regions, using an integrated seamless grid system, which utilized ADCIRC + SWAN + EurOtop, for the present day, 2050, 2070, and 2100 to investigate how vulnerability to WOT changes with sea level rise. The maximum envelope of WOT inundation results for three historical and two 100-year return period synthetic typhoons confirms that vulnerability to WOT intensifies with rising sea levels. The single-process integrated model applied in this study can serve not only for long-term coastal seawall protection design but also for the short-term early warning system for storm surges and WOT, contributing to immediate preparedness efforts. Full article

Storm surge and concomitant waves induced by extreme weather systems can significantly modulate the marine dynamic environment. In this study, we used the Advanced Circulation-Simulating Waves Nearshore (ADCIRC-SWAN) coupled model to analyze spatiotemporal variation in dynamic processes during two types of weather systems, i.e., typhoons and extratropical storms, in the sea area near the Shandong Peninsula. The effects of waves on water level, water level change on wave height, and currents on wave height were investigated and quantified separately by performing sensitivity experiments. Our results showed that the interaction between water level change and waves occurred mainly in the nearshore zone. The wave-induced surge accounted for about 10–15% of the total storm surge. The water level change-induced significant wave height reached up to 0.9–1.3 m. Wave–current interaction occurred mainly in the offshore zone and was related to the relative angle between wave and current directions. The modulations of water level and wave height were strongly dependent on not only storm track and intensity but also topography and coastline shapes. Full article

Hurricane storm surges are influenced by wind intensity, forward speed, width and slope of the ocean bottom, central pressure, angle of approach, shape of coastal lines, local features, and storm size. A numerical experiment is conducted using the Advanced Circulation + Simulation and Simulating Waves Nearshore (ADCIRC + SWAN) coupled model for understanding the effects of wind intensity, forward speed, and wave on the storm surges caused by Hurricane Harvey. The ADCIRC + SWAN is used to simulate hurricane storm surges and waves. The wind fields of Hurricane Harvey were reconstructed from observed data, aided by a variety of methodologies and analyses conducted by Ocean Weather Inc (OWI) after the event. These reconstructed wind fields were used as the meteorological forcing in the base case in ADCIRC+SWAN to investigate the storm surges caused by the hurricane. Hurricane Harvey was the second most costly hurricane in the United States, causing severe urban flooding by dropping more than 60 inches of rainfall in Texas. The hurricane made three landfalls, with its first landfall as a Category 4 based on the Saffir–Simpson Hurricane Wind Scale (SSHWS), with wind intensities of 212.98 km/h (59 m/s). The storm surges caused by Hurricane Harvey were unique due to the slow speed, crooked tracks, triple landfalls in the USA, and excessive rain. The model’s storm surge and wave results were compared against observed data. High water marks at 21 locations and time series at 12 National Oceanic and Atmospheric Administration (NOAA) gauges were compared with the generated results. Several cases were investigated by increasing or decreasing the wind intensity or hurricane forward speed by 25% of the OWI wind and pressure data. The effects of the wave were analyzed by comparing the results obtained from ADCIRC + SWAN (with waves) and ADCIRC (without waves) models. The study found that the changes in wind intensity had the most significant effect on storm surges, followed by wave and forward speed changes. This study signifies the importance of considering these factors to enhance accuracy in predicting storm surges. Full article

The South Pacific region is characterised by steep shelves and fringing coral reef islands. The lack of wide continental shelves that can dissipate waves makes Pacific Island countries vulnerable to large waves that can enhance extreme total water levels triggered by tropical cyclones (TCs). In this study, hindcasts of the waves and storm surge induced by severe TC Harold in 2020 on Tongatapu, Tonga’s capital island, were examined using the state-of-the-art hydrodynamic and wave models ADCIRC and SWAN. The contributions of winds, atmospheric pressure, waves, and wave-radiation-stress-induced setup to extreme total water levels were analysed by running the models separately and two-way coupled. The atmospheric pressure deficit contributed uniformly to the total water levels (~25%), while the wind surge was prominent over the shallow shelf (more than 75%). Wave setup became significant at locations with narrow fringing reefs on the western side (more than 75%). Tides were dominant on the leeward coasts of the island (50–75%). Storm surge obtained from the coupled run without tide was comparable with the observation. The wave contribution to extreme total water levels and inundation was analysed using XBEACH in non-hydrostatic mode. The model (XBEACH) was able to reproduce coastal inundation when compared to the observed satellite imagery after the event on a particular coastal segment severely impacted by coastal flooding induced by TC Harold. The coupled ADCIRC+SWAN underestimated total water levels nearshore on the reef flat and consequently inundation extent as infragravity waves and swash motion are not resolved by these models. The suite of models (ADCIRC+SWAN+XBEACH) used in this study can be used to support the Tonga Meteorological Service Tropical Cyclone Early Warning System. Full article

Efficiency in storm surge modeling is crucial for forecasting coastal hazards in real-time. While computation cost may not be the main concern for organizations with ample resources, the robustness of forecasts generated by most parties are restricted by wall-clock time. The Parametric Wave Solver (PARAM) was developed by Boyd and Weaver (2021) as an alternative to computationally expensive wind–wave models when modeling restricted estuarine environments. For this study, PARAM has been tightly coupled with the ADCIRC hydrodynamic model to create ADCparam, then integrated into the Multistage mini-ensemble modeling system (MMEMS), a one-way nesting framework for modeling waves and circulation in coastal estuaries developed by Taeb and Weaver (2019). In the MMEMS framework, ADCIRC + SWAN is used to simulate the coarser ocean domain and ADCparam is applied to the nested high resolution estuarine mesh. ADCparam has greatly reduced computation time for the high resolution nested sub-model compared to the third-generation wave model originally used. While the PARAM wave solution shows dissimilarities with the SWAN solution, significant wave height and wave period results are consistent and warrant further pursuit of the parametric wave ensemble method as a substitute to SWAN within MMEMS. ADCparam models demonstrated run times up to 51% faster than ADCIRC coupled with SWAN, an established iterative wave model tightly coupled to ADCIRC and packaged with the MMEMS repository. ADCparam wall time is comparable to running ADCIRC without wave forcing, nearly eliminating the computational cost of including the wave forcing in the high-resolution estuarine domain of MMEMS. Computational efficiency is greatly increased while maintaining solution integrity. Though ADCparam, and its application to MMEMS, are still being refined and validated, the coupled model system has proven to be an efficient, viable path for implementing waves in any estuarine circulation model. Full article

The south coast of Korea is vulnerable to coastal disasters, such as storm surges, high waves, wave overtopping, and coastal flooding caused by typhoons. It is imperative to predict such disastrous events accurately in advance, which requires accurate meteorological forcing for coastal ocean modeling. In this study, to acquire accurate meteorological data as important forcing variables for the prediction of storm surges and waves, we examined the forecast performance and applicability of a next-generation global weather/climate prediction model, the Model for Prediction Across Scales (MPAS). We compared the modeled surface pressure and wind with observations on the south coast of Korea for three typhoons that damaged Korea in 2020—Bavi, Maysak, and Haishen—and investigated the accuracy of these observations with the MPAS prediction. Those meteorological forcing variables were then used in the tightly coupled tide-surge-wave model, Advanced CIRCulation (ADCIRC) and the Simulating Waves Nearshore (SWAN) for the simulation of a typhoon-induced storm surge and wave. We also performed the hindcast of the wave and storm surges using a parametric tropical cyclone model, the best-track-based Generalized Asymmetric Holland Model (GAHM) embedded in ADCIRC+SWAN, to better understand the forecast performance and applicability of MPAS. We compared the forecast results of the typhoon-induced wave and storm surges with their hindcast in terms of the time-series and statistical indices for both significant wave height and storm surge height and found that wave and storm surge prediction forced by MPAS forecast provides a comparable accuracy with the hindcast. Comparable results of MPAS forcing with that of hindcast using best track information are encouraging because ADCIRC+SWAN forced by MPAS forecast with an at most four-day lead time still provides a reasonable prediction of wave and storm surges. Full article