Tidal phenomenon is a significant dynamical phenomenon in the ocean, and the accurate prediction of tide is an important task for various maritime activities. This paper proposes analysis method considering tidal periodicity and apply it to the actua...
The extreme values of high tides are generally caused by a combination of astronomical and meteorological causes, as well as by the conformation of the sea basin. One place where the extreme values of the tide have a considerable practical interest i...
Tidal prediction is essential for navigation safety, coastal risk management, and climate adaptation. This study develops and validates a hybrid harmonic analysis–artificial intelligence (HA–AI) framework to improve decadal tidal forecast...
Forecasting coastal bottom dissolved oxygen (DO) concentrations is essential for hypoxia mitigation and ecosystem protection, however it remains challenging due to the complex interplay of physical and biogeochemical drivers. This study proposes a no...
This study presents a two-dimensional hydraulic modelling framework for the simulation of flash and compound flooding in coastal urban areas with non-perennial river systems. The model employs a rain-on-grid approach within HEC-RAS v6.7 beta5 (2D sol...
A system for providing routine seven-day forecasts of sea level observable at tide gauge locations is described and evaluated. Forecast time series are aggregated from well-established operational systems of the Australian Bureau of Meteorology; alth...
Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often de...
Accurate gas consumption forecasting is critical for modern energy systems due to complex consumer behavior and regulatory requirements. Deep neural networks (DNNs), such as Seq2Seq with attention, TiDE, and Temporal Fusion Transformers, are promisin...
Sea level changes in coastal areas significantly influence port activities (e.g., the safety of navigation). Along Italian coastlines, sea level variations are mainly due to astronomical tides (well known, due to gravitational attraction between Eart...
Multistep-ahead forecasting of chlorophyll concentration is of great significance in red tide early warning systems. Existing methods often neglect the potential adverse interactions between non-predictive variables and chlorophyll while failing to f...
Chlorophyll prediction facilitates the comprehension of red tide characteristics and enables early warning. In practice, it is formulated as a multivariate time series forecasting problem aimed at forecasting future chlorophyll concentrations by cons...
One of the manifests of air-sea interactions is the change in sea level due to meteorological forcing through wind stress and atmospheric pressure. When meteorological conditions conducive to water level increase coincide with high tides during sprin...
This paper proposes a semi-automatic green tide extraction method based on the NDVI to extract Yellow Sea green tides from 2008 to 2022 using remote sensing (RS) images from multiple satellites: GF-1, Landsat 5 TM, Landsat 8 OLI_TIRS, HJ-1A/B, HY-1C,...
15 February 2023
Venice and its lagoon represent an extraordinary architectural, artistic and cultural heritage. However, due to the combination of astronomical and meteorological causes, as well as by the conformation of the sea basin, the city and its lagoon are fr...
Accurate and timely water level predictions are essential for effective shoreline and coastal ecosystem management. As sea levels rise, the frequency and severity of coastal inundation events are increasing, causing significant societal and economic...
F_TIDE has been proven to be effective in obtaining the time-varying harmonic parameters of nonstationary tidal signals, and the results near the two endpoints of the analyzed time series are more accurate than those obtained by S_TIDE, which provide...
Deep learning has become a widely used approach in photovoltaic (PV) power generation forecasting due to its strong self-learning and parameter optimization capabilities. In this study, we apply a deep learning algorithm, known as the time-series den...
Forecasting estuarine circulation is a hot topic, especially in densely populated regions, like Santos (Brazil). This paper aims to improve a water-level forecasting system for the Santos estuary, particularly the physical forcing determining the res...
To improve the overall accuracy of tidal forecasting and ameliorate the low accuracy of single harmonic analysis, this paper proposes a combined tidal forecasting model based on harmonic analysis and autoregressive integrated moving average–sup...
Accurate and timely information of surface currents is crucial for various operations such as search and rescue, marine renewable energy extraction and oil spill treatment. Conventional approaches to study coastal surface currents are numerical model...
In the Venice Lagoon some of the highest tides in the Mediterranean occur, which have influenced the evolution of the city of Venice and the surrounding lagoon for centuries. The forecast of “high waters” in the lagoon has always been a matter of con...
In this study, monsoon-induced surge during high tides at the Southeast coast of Vietnam was analyzed based on the observed tide data at the Vung Tau station in the period between 1997—2016. Specifically, the surge was determined by removing th...
This paper describes storm surge simulations made for Sandy (2012) for the Metropolitan New York (NYC) area using the Advanced Circulation (ADCIRC) model forced by the Weather Research and Forecasting (WRF) model. The atmospheric forecast uncertainty...
The water level forecasting system represented by the hydrodynamic model relies too much on the input data and the forecast value of the boundary, therefore introducing uncertainty in the prediction results. Tide tables ignore the effect of the resid...
Since 2008, annual outbreaks of green tides in the Yellow Sea have had severe impacts on tourism, fisheries, water sports, and marine ecology, necessitating effective interception and removal measures. Satellite remote sensing has emerged as a promis...
Numerical simulations of the storm tide that flooded the US Atlantic coastline during Hurricane Sandy (2012) are carried out using the National Weather Service (NWS) Sea Lakes and Overland Surges from Hurricanes (SLOSH) storm surge prediction model t...
The water-level time series of a tidal river is influenced by various factors and has a complex structure, which limits its use as hydrological forecast data. This study proposes a methodology for decomposing the water-level time series of a tidal ri...
Urban rail transit networks in developing countries are rapidly expanding, entering a networked operational phase where accurate passenger flow forecasting is crucial for optimizing vehicle scheduling, resource allocation, and transportation efficien...
The highly urbanized estuary of San Francisco Bay is an excellent example of a location susceptible to flooding from both coastal and fluvial influences. As part of developing a forecast model that integrates fluvial and oceanic drivers, a case study...
Qinhuangdao, a famous coastal resort city in northeastern China, has been affected by the rapid growth of harmful algae. The brown tide induced by Aureococcus anophagefferens (A. anophagefferens) first occurred along Qinhuangdao’s coastline in...
The Four-Dimensional Data Assimilation module (FDDA) is used in combination with the WRF model for the analysis of two case studies of high tide (on 4 April 2019 and on 12 November 2019) that affected the Venice Lagoon in the recent past. The system...
Sea level rise due to climate change poses an increasing threat to coastal ecosystems, infrastructure, and human settlements. However, accurately estimating sea level changes in regions without tide gauge observations remains a major challenge. While...
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 tropic...
Harmful algal blooms (HABs) often cause great harm to fishery production and the safety of human lives. Therefore, the detection and prediction of HABs has become an important issue. Machine learning has been increasingly used to predict HABs at home...
The fluctuation of the tide is closely related to the production and life of people in coastal areas, and the change in the tide level will have a significant impact on the safety of infrastructure, ship travel, ecological environment, and other issu...
Typhoons can often cause inundation in lower coastal cities by inducing strong surges and waves. Being affected by typhoon annually, the coastal cities in South Korea are very vulnerable to typhoons. In 2016, a typhoon ‘CHABA’, with a maximum 10 min...
Coastal flooding is a global phenomenon that results in severe economic losses, threatens lives, and impacts coastal communities worldwide. While recent developments in real-time flood forecasting systems provide crucial information to support coasta...
The North Sea is a shallow sea that forms a complex physical system. The nonlinear interaction of the astronomical tides, varying wind fields and varying pressure systems requires appropriate approaches to be described accurately. An application base...
The study used the SCHISM ocean model combined with the WWM III wind wave model to quantify the interaction between wind waves and tides in the coastal zone of the Changjiang River Estuary and its adjacent areas. The wave and storm surge during Typho...
In this study, a novel model that performs ensemble empirical mode decomposition (EEMD) and stepwise regression was developed to forecast the water level of a tidal river. Unlike more complex hydrological models, the main advantage of the proposed mo...
To understand the Arctic environment, which is closely related to sea ice and to reduce potential risks, reliable sea ice forecasts are indispensable. A practical, lightweight yet effective assimilation scheme of sea ice concentration based on Optima...
Climate change and rising sea levels pose significant threats to coastal regions, necessitating accurate and timely forecasts. Current methods face limitations due to their inability to fully capture nonlinear complexities, high computational costs,...
Gated storm surge barriers are being studied by the United States Army Corps of Engineers (USACE) for coastal storm risk management for the New York City metropolitan area. Surge barrier gates are only closed when storm tides exceeding a specific &ld...
Accurate predictions of beach user numbers are important for coastal management, resource allocation, and minimising safety risks, especially when considering surf-zone hazards. The present work applies an XGBoost model to predict beach attendance fr...
Super Typhoon Saola (2309) skirted past south-southeast of Hong Kong within 40 km on the night of 1 September 2023, posing a significant storm surge threat to Hong Kong. Given the close proximity of Saola with a peak intensity of about 210 km/h withi...
This study constructs a time-dependent model to predict the nighttime suspended sediment concentration near Wenzhou based on the convolutional neural network U-Net, which integrates the high-resolution Delft3D (version 4.03.01) hydrodynamic model and...
The ocean tide loading (OTL) can result in displacements of centimeters or even decimeters at nearshore stations. Global ocean tide models exhibit errors in nearshore regions, which limit the accuracy of maintaining the coordinates of these stations....
The present study extends the applicability of a statistical model for prediction of storm surge originally developed for The Battery, NY in two ways: I. the statistical model is used as a biascorrection for operationally produced dynamical surge for...
The primary contribution of this study lies in analyzing the dynamic drivers during two anomalous sea level rise events in the Bohai Sea through coupled numeric modeling using the Weather Research and Forecasting (WRF) model and the Finite-Volume Com...
For nearly two decades, the Yellow Sea has experienced recurrent green tides, which are now considered the largest of their kind globally; the mechanism behind these outbreaks remains highly complex and not fully understood. This study investigates t...
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