A Coastal Flood Early-Warning System Based on Offshore Sea State Forecasts and Artificial Neural Networks
An integrated methodological approach to the development of a coastal flood early-warning system is presented in this paper to improve societal preparedness for coastal flood events. The approach consists of two frameworks, namely the Hindcast Framework and the Forecast Framework. The aim of the for...
Saved in:
Main Authors: | Michalis Chondros, Anastasios Metallinos, Andreas Papadimitriou, Constantine Memos, Vasiliki Tsoukala |
---|---|
Format: | article |
Language: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/86f66d3a871d47b49d2e857a93e17c89 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A User-Oriented Local Coastal Flooding Early Warning System Using Metamodelling Techniques
by: Déborah Idier, et al.
Published: (2021) -
Geological Oceanography of the Pliocene Warm Period: A Review with Predictions on the Future of Global Warming
by: Markes E. Johnson
Published: (2021) -
Unsteady Linearisation of Bed Shear Stress for Idealised Storm Surge Modelling
by: Pieter C. Roos, et al.
Published: (2021) -
Assessment of Extreme Storm Surges over the Changjiang River Estuary from a Wave-Current Coupled Model
by: Yutao Chi, et al.
Published: (2021) -
Offshore and Onshore Wave Energy Converters: Engineering and Environmental Features
by: Luca Cavallaro, et al.
Published: (2021)