Predicting Storm Surges Chaos Computational Intelligence Data Assimilation And Ensembles
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Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles
Accurate predictions of storm surge are of importance in many coastal areas in the world to avoid and mitigate its destructive impacts. For this purpose the physically-based (process) numerical models are typically utilized. However, in data-rich cases, one may use data-driven methods aiming at reconstructing the internal patterns of the modelled processes and relationships between the observed descriptive variables. This book focuses on data-driven modelling using methods of nonlinear dynamics and chaos theory. First, some fundamentals of physical oceanography, nonlinear dynamics and chaos, computational intelligence and European operational storm surge models are covered. After that a number of improvements in building chaotic models are presented: nonlinear time series analysis, multi-step prediction, phase space dimensionality reduction, techniques dealing with incomplete time series, phase error correction, finding true neighbours, optimization of chaotic model, data assimilation and multi-model ensemble prediction. The major case study is surge prediction in the North Sea, with some tests on a Caribbean Sea case. The modelling results showed that the enhanced predictive chaotic models can serve as an efficient tool for accurate and reliable short and mid-term predictions of storm surges in order to support decision-makers for flood prediction and ship navigation.
Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles
Accurate predictions of storm surge are of importance in many coastal areas in the world to avoid and mitigate its destructive impacts. For this purpose the physically-based (process) numerical models are typically utilized. However, in data-rich cases, one may use data-driven methods aiming at reconstructing the internal patterns of the modelled p
Smart Wastewater Systems and Climate Change
Author: Moharana Choudhury
language: en
Publisher: Royal Society of Chemistry
Release Date: 2025-07-09
The changes in temperature and rainfall that will come with climate change combined with populations that are growing but also becoming more condensed will put a great deal of stress on our wastewater systems. Smart systems use sensors, data analytics, and automation to enable real-time monitoring, data-driven decision-making, and enhanced control. Smart Wastewater Systems and Climate Change presents the ways smart technology can be used to improve wastewater management and increase the climate resilience of wastewater systems. This is a great resource for anyone interested in water or wastewater management, climate resilience, or smart systems applications. Topics covered include: Use of spatial intelligence and geospatial analysis Approaches to risk assessment and disaster resilience Incorporation of machine learning and AI into decision making