A review of application of machine learning in storm surge problems
Y Qin, C Su, D Chu, J Zhang, J Song - Journal of Marine Science and …, 2023 - mdpi.com
The rise of machine learning (ML) has significantly advanced the field of coastal
oceanography. This review aims to examine the existing deficiencies in numerical …
oceanography. This review aims to examine the existing deficiencies in numerical …
Surge-NF: Neural Fields inspired peak storm surge surrogate modeling with multi-task learning and positional encoding
Storm surges pose a significant threat to coastal communities, necessitating rapid and
precise storm surge prediction methods for long-time risk assessment and emergency …
precise storm surge prediction methods for long-time risk assessment and emergency …
An advanced spatio-temporal convolutional recurrent neural network for storm surge predictions
In this research paper, we study the capability of artificial neural network models to emulate
storm surge based on the storm track/size/intensity history, leveraging a database of …
storm surge based on the storm track/size/intensity history, leveraging a database of …
Operator learning for urban water clarification hydrodynamics and particulate matter transport with physics-informed neural networks
H Li, M Shatarah - Water Research, 2024 - Elsevier
Computational fluid dynamics (CFD) can be a powerful tool for higher-fidelity water
infrastructure planning and design. Despite decades of development and demonstration …
infrastructure planning and design. Despite decades of development and demonstration …
Adaptive multi-fidelity Monte Carlo for real-time probabilistic storm surge predictions
Real-time, probabilistic predictions of the expected storm surge represent an important
information source for guiding emergency response decisions during landfalling tropical …
information source for guiding emergency response decisions during landfalling tropical …
A deep-learning model for rapid spatiotemporal prediction of coastal water levels
A Shahabi, N Tahvildari - Coastal Engineering, 2024 - Elsevier
With the increasing impact of climate change and relative sea level rise, low-lying coastal
communities face growing risks from recurrent nuisance flooding and storm tides. Thus …
communities face growing risks from recurrent nuisance flooding and storm tides. Thus …
Advancing Spatio-temporal Storm Surge Prediction with Hierarchical Deep Neural Networks
Coastal regions in North America face major threats from storm surges caused by hurricanes
and nor'easters. Traditional numerical models, while accurate, are computationally …
and nor'easters. Traditional numerical models, while accurate, are computationally …
Advancing storm surge forecasting from scarce observation data: A causal-inference based Spatio-Temporal Graph Neural Network approach
Rapid and precise forecasting of storm surge in coastal regions is crucial for ensuring safety
of coastal communities' life and property. Yet, learning a data-driven forecasting model from …
of coastal communities' life and property. Yet, learning a data-driven forecasting model from …
Data assimilation of hyper-local water level sensors for real-time monitoring of coastal inundation
As flood events become increasingly prevalent in coastal regions with sea level rise,
multiple communities have deployed water level monitoring networks across estuaries in …
multiple communities have deployed water level monitoring networks across estuaries in …
Assessing and predicting nearshore seawater quality with spatio-temporal semivariograms: the case of coastal waters in Fujian province, China
W Wang, W Cheng, J Chen - ISPRS International Journal of …, 2024 - search.proquest.com
The scientific assessment and prediction of nearshore water quality are crucial for marine
environment protection efforts. This study is based on a comprehensive analysis of existing …
environment protection efforts. This study is based on a comprehensive analysis of existing …