An impact-oriented Early Warning and Bayesian-based Decision Support System for flood risks in Zeebrugge harbour

Bolle, Annelies; Neves, Luciana das; Smets, Steven; Mollaert, Justine; Buitrago, Saul

doi:10.1016/j.coastaleng.2017.10.006

Cited by 24 publications

(11 citation statements)

References 25 publications

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“…Analysis of the behaviour of specific management interventions (or DRR measures) against the observed impacts of single storms are not yet commonly found in literature, being limited to few recent studies, mostly within the frame of EU funded projects (e.g. Barquet et al, 2018;Bolle et al, 2018;Ferreira et al, 2018;Jäger et al, 2018;Plomaritis et al, 2018;Villatoro et al, 2014). There is not currently in place a policy of ex-ante evaluation of the effectiveness of DRR measures against specific, high potential impact, storm events.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness assessment of risk reduction measures at coastal areas using a decision support system: Findings from Emma storm

Ferreira

Plomaritis

Costas

2019

Science of The Total Environment

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Storms impact coastal areas often causing damages and losses at occupied areas. On a scenario of increasing human occupation at coastal zones and under climate change conditions (including sea level rise and increasing frequency of extreme sea levels), the consequences of storms are expected to be amplified if no adaptation or further management actions are implemented. The selection of the best possible coastal management measures, considering both costs and effectiveness, will be mandatory in the future, in order to optimise resources. This work analyses the performance of risk reduction measures (beach nourishment and receptors -house and infrastructures -removal), using a decision support system comprised by a morphodynamic numerical model (XBeach) and a Bayesian network based on the source-pathway-receptor concept. The effectiveness of the risk reduction measures is then assessed by a simple index expressing the consequences to the receptors. The approach was tested at Faro Beach by evaluating its performance for a particular storm, Emma (Feb/March 2018), which fiercely impacted the southern coast of Portugal. The output results from the modelling were compared to field observations of the actual damages caused by the storm. The combined use of both measures or the solely use of the nourishment would avoid almost all observed impacts from this storm. The work is pioneer on demonstrating the use of a decision support system 2 for coastal regions validated against observed impacts for a high-energy storm event. The methodology and the proposed index are adaptable to any sandy coastal region and can be used to test (and improve) management options at a broad number of coastal areas worldwide, minimising implementation costs and reducing the risk to the occupation and to the people.

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Section: Introductionmentioning

confidence: 99%

Effectiveness assessment of risk reduction measures at coastal areas using a decision support system: Findings from Emma storm

Ferreira

Plomaritis

Costas

2019

Science of The Total Environment

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“…Many Bayesian network based studies for coastal applications have been published but nearly all of them use discrete Bayesian networks [47][48][49][50][51][52][53][54] except the very few recent ones which use NPBNs [86][87][88][89]. In discrete BNs, variables have to be discretized into bins where the number and sizes of the bins need to be correctly fine-tuned to ensure that each bin represents homogeneous information and has nearly similar impact on the child node.…”

Section: Methodological Valuementioning

confidence: 99%

“…Used C d = 1.5 from [45] Modeling complex systems requires the (probabilistic) dependence among constituting system components to be taken into account. As a possibility, Bayesian networks (BNs) are being used in different coastal engineering studies [47][48][49][50][51][52][53][54]. A Bayesian network is a directed acyclic graph (DAG) whose nodes represent random variables and whose arcs represent probabilistic dependence.…”

Section: Spartina Anglicamentioning

confidence: 99%

Probabilistic Characterization of the Vegetated Hydrodynamic System Using Non-Parametric Bayesian Networks

Niazi

Morales-Nápoles

Wesenbeeck

2021

Water

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The increasing risk of flooding requires obtaining generalized knowledge for the implementation of distinct and innovative intervention strategies, such as nature-based solutions. Inclusion of ecosystems in flood risk management has proven to be an adaptive strategy that achieves multiple benefits. However, obtaining generalizable quantitative information to increase the reliability of such interventions through experiments or numerical models can be expensive, laborious, or computationally demanding. This paper presents a probabilistic model that represents interconnected elements of vegetated hydrodynamic systems using a nonparametric Bayesian network (NPBN) for seagrasses, salt marshes, and mangroves. NPBNs allow for a system-level probabilistic description of vegetated hydrodynamic systems, generate physically realistic varied boundary conditions for physical or numerical modeling, provide missing information in data-scarce environments, and reduce the amount of numerical simulations required to obtain generalized results—all of which are critically useful to pave the way for successful implementation of nature-based solutions.

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“…The diversity in research topics and methods is evident. Concepts such as decision-making, policy, resilience, and planning are added into the investigation (See Peirson et al, 2015;Ng et al, 2018;Bolle et al, 2018;, as ports being a critical element of transportation networks and coastal cities. Similarly, the challenges from uncertainties inside the problem, governance model, or stakeholders also lead to a rise of study (Walker et al, 2015).…”

Section: General Review Of the Previous Study Of Port Climate Change mentioning

confidence: 99%

“…The diversity in research topics and methods is evident in the past decade. Such sustainability, uncertainty, and risks, decision-making, perceptions, and attitudes of stakeholders, policy, resilience, and planning are added into the investigation (See Pierson et al, 2015;Ng et al, 2018;Bolle et al, 2018;. There is a rise in concepts of institutions, stakeholders, and perceptions in recent years, which are mostly treated as barriers in the study.…”

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confidence: 99%

Climate change adaptation in the port industry: A complex of lingering research gaps and uncertainties

Panahi

Pang

2020

Transport Policy

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Despite a rise of global concerns on climate change and adaptation in recent years, a review of articles published over the past two decades shows that research on port climate adaptation is still in its infancy (Panahi et al., 2020). Seaports play a pivotal role in the global supply chain and transportation networks and profoundly influence the regional economy and are highly exposed to marine natural disasters and climate change threats. The adaptation strategy is regarded as a practical approach to reducing vulnerabilities of the seaport to climate change. A significant research community covering various subjects on the study of port climate adaptation is emerging and forming (Panahi et al., 2020). However, the existing scholarships on port climate adaptation remain to focus on developed countries' ports and lack of diversification background. There is still a limited contribution of researchers from developing countries in port climate research. The growing leadership role of Chinese ports in global transportation and supply chain network makes researchers need to pay more attention to adaptation's status quo. In the complex context of port reform and development, in what way and to what extent do the institutions and stakeholders in the decision-making environment to China's port system affect the process of establishing and implementing adaptation mechanisms in ports, requires further research. This literature is partly formed by the work of Panahi et al. (2020). It explores the roles of and interaction between institutions and stakeholders in climate change adaptation of the Chinese port system, based on the decision-making theory. This paper undertakes an in-depth case study on Ningbo-Zhoushan port, one of China's most representative regional ports. We identify that the inadequate supply of institutions and the absence and misbehaviors of main port stakeholders cause institutional imperfection of port adaptation system to varying degrees. This paper is one of the first attempts to fill the gap in research on climate change and adaptation in Chinese ports. In addition, by bringing together concepts from social science fields into interdisciplinary research, we further prove and develop decision-making theory through case studies within the Chinese social and institutional system framework.

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An impact-oriented Early Warning and Bayesian-based Decision Support System for flood risks in Zeebrugge harbour

Cited by 24 publications

References 25 publications

Effectiveness assessment of risk reduction measures at coastal areas using a decision support system: Findings from Emma storm

Effectiveness assessment of risk reduction measures at coastal areas using a decision support system: Findings from Emma storm

Probabilistic Characterization of the Vegetated Hydrodynamic System Using Non-Parametric Bayesian Networks

Climate change adaptation in the port industry: A complex of lingering research gaps and uncertainties

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