Enhancing the management response to oil spills in the Tuscany Archipelago through operational modelling

Janeiro, João; Zacharioudaki, Anna; Sarhadi, E.; Neves, A. A. O.; Martins, Flávio

doi:10.1016/j.marpolbul.2014.03.021

Cited by 26 publications

(23 citation statements)

References 37 publications

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“…At the same time, other proactive decision support services can be easily configured. As an example of further improvement in the system, a unit for modeling the forecast of oil-spillage spread due to weather and sea conditions, as described for example in [14], could be included and added as a layer to the dynamic risk map. Obviously, this should come along with a service unit deputed to acquiring meteorological data, but, as explained in the paper due to the modular nature of the connected units, this will not be a structural problem.…”

Section: Discussionmentioning

confidence: 99%

“…A particular interface is the one devoted to the acquisition of mathematical simulation of the oil-spillage spread. In principle, this could be based on the results obtained in [14], or, if coupled with an interface for meteorological and sea surface (currents, waves...), data could be computed as part of a dedicated internal mathematical simulation module.…”

Section: Service Unitmentioning

confidence: 99%

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A Marine Information System for Environmental Monitoring: ARGO-MIS

Pieri

Cocco²,

Salvetti

2018

JMSE

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Sea shipping routes have become very crowded and this, coupled with an always increasing demand of oil based products, contributes to the increase in maritime traffic density, as a consequence pollution risks have increased. Therefore, it is important to have information systems capable of detecting and monitoring environmental endangering situations like oil spills at sea. In this paper, a Marine Information System, acting as an integrated and inter-operable monitoring tool is proposed and discussed. The discussion focuses on a system that is able to integrate different data acquired from various electronic sensors, and that is inter-operable among marine operators and ship traffic authorities. The available data on the system are all geo-referenced, and flows seamlessly through the system, where they are integrated in a consistent and usable manner. An important result of this integration is the capability to produce a collection of proactive services such as Decision Support ones, which can be used to improve the functionalities and facilities concerned in an intervention operation. Through the implementation of these services, we aim to demonstrate how an efficient environmental management system could benefit from being supported by a Marine Information System that can provide the dynamic links between different data, models and actors.

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Section: Discussionmentioning

confidence: 99%

Section: Service Unitmentioning

confidence: 99%

A Marine Information System for Environmental Monitoring: ARGO-MIS

Pieri

Cocco²,

Salvetti

2018

JMSE

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“…The MOHID oil spill modelling component was initially developed in MOHID in 2001 (Fernandes, 2001), and over the years the model has been operationally applied in different incidents (Carracedo et al, 2006;Janeiro et al, 2014), field exercises and studies worldwide, allowing the simulation of all major oil transport and weathering processes at sea. The source code of the oil spill modelling system was recently updated to include full 3-D movement of oil particles, wave-induced currents and oil-shoreline interaction (Fernandes et al, 2013), as well as blowout emissions .…”

Section: Oil Spill Modelmentioning

confidence: 99%

Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

Fernandes¹,

Braunschweig²,

Lourenço³

et al. 2016

Ocean Sci.

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Abstract. The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events.A combined methodology to dynamically estimate time and space variable individual vessel accident risk levels and shoreline contamination risk from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area -the Portuguese continental shelf -with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time, or as an alternative, a correction factor based on vessel distance from coast. Shoreline risks can be computed in real time or from previously obtained data.Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns ("hot spots") or developing sensitivity analysis to specific conditions, whereas real-time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.

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“…This paper addresses these issues by proposing an integrated and inter-operable information system based on acquired data from a variety of electronic sensors. In particular, the proposed Marine Information System (MIS) integrates classical SAR satellite processed data [3], with multi-spectral aerial data, as well as environmental data from in situ monitoring stations (e.g., placed on static and floating buoys) [4], and dynamic data acquired from in situ mobile sources (e.g., Autonomous Underwater Vehicles (AUVs) equipped with sensing modules). The designed MIS provides a collection of environmental Decision Support Services (EDSS), for (i) automatically monitoring the overall environmental situation, (ii) quantitatively representing environmental risk factors and (iii) proactively notifying events that deserve the consideration of end users.…”

Section: Introductionmentioning

confidence: 99%

Environmental Monitoring Integrated with a Proactive Marine Information System

Moroni

Pieri

Tampucci

et al. 2018

International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM)

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Abstract:In the framework of environmental monitoring, the remote detection and monitoring of oil spills at sea is an important ability due to the high demand of oil based products. This situation causes, that shipping routes are very crowded and the likelihood of oil slicks occurring is also increasing. In this paper we propose a fully integrated and inter-operable information system which can act as a valuable monitoring tool. Such a marine information system is able to monitor ship traffic and marine operators by integrating heterogeneous signals and data through sensing capabilities from a variety of electronic sensors, along with geo-positioning tools, and through a communication infrastructure. This system is able to transfer the integrated data, freely and seamlessly, between different elements of the system itself (and their users). The system also provides a set of decision support services capable of performing functionalities which can act as a support for decision makers.

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Enhancing the management response to oil spills in the Tuscany Archipelago through operational modelling

Cited by 26 publications

References 37 publications

A Marine Information System for Environmental Monitoring: ARGO-MIS

A Marine Information System for Environmental Monitoring: ARGO-MIS

Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

Environmental Monitoring Integrated with a Proactive Marine Information System

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