Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions
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 res...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-02-01
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| Series: | Ocean Science |
| Online Access: | http://www.ocean-sci.net/12/285/2016/os-12-285-2016.pdf |
| _version_ | 1818303504411787264 |
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| author | R. Fernandes F. Braunschweig F. Lourenço R. Neves |
| author_facet | R. Fernandes F. Braunschweig F. Lourenço R. Neves |
| author_sort | R. Fernandes |
| collection | DOAJ |
| description | 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.
<br><br>
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.
<br><br>
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. |
| first_indexed | 2024-12-13T05:55:51Z |
| format | Article |
| id | doaj.art-b5f98f71fa994f66bf58cbc70911f899 |
| institution | Directory Open Access Journal |
| issn | 1812-0784 1812-0792 |
| language | English |
| last_indexed | 2024-12-13T05:55:51Z |
| publishDate | 2016-02-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Ocean Science |
| spelling | doaj.art-b5f98f71fa994f66bf58cbc70911f8992022-12-21T23:57:26ZengCopernicus PublicationsOcean Science1812-07841812-07922016-02-0112128531710.5194/os-12-285-2016Combining operational models and data into a dynamic vessel risk assessment tool for coastal regionsR. Fernandes0F. Braunschweig1F. Lourenço2R. Neves3MARETEC – Marine Environment and Technology Centre, Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco Pais, 1049-001, Lisbon, PortugalAction Modulers, Estrada Principal, 29, 2640-583, Mafra, PortugalAction Modulers, Estrada Principal, 29, 2640-583, Mafra, PortugalMARETEC – Marine Environment and Technology Centre, Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco Pais, 1049-001, Lisbon, PortugalThe 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. <br><br> 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. <br><br> 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.http://www.ocean-sci.net/12/285/2016/os-12-285-2016.pdf |
| spellingShingle | R. Fernandes F. Braunschweig F. Lourenço R. Neves Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions Ocean Science |
| title | Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions |
| title_full | Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions |
| title_fullStr | Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions |
| title_full_unstemmed | Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions |
| title_short | Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions |
| title_sort | combining operational models and data into a dynamic vessel risk assessment tool for coastal regions |
| url | http://www.ocean-sci.net/12/285/2016/os-12-285-2016.pdf |
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