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Monitoring Systems and Numerical Models to Study Coastal Sites †
The present work aims at illustrating how the joint use of monitoring data and numerical models can be beneficial in understanding coastal processes. In the first part, we show and discuss an annual dataset provided by a monitoring system installed in a vulnerable coastal basin located in Southern I...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479855/ https://www.ncbi.nlm.nih.gov/pubmed/30935083 http://dx.doi.org/10.3390/s19071552 |
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author | Armenio, Elvira Ben Meftah, Mouldi De Padova, Diana De Serio, Francesca Mossa, Michele |
author_facet | Armenio, Elvira Ben Meftah, Mouldi De Padova, Diana De Serio, Francesca Mossa, Michele |
author_sort | Armenio, Elvira |
collection | PubMed |
description | The present work aims at illustrating how the joint use of monitoring data and numerical models can be beneficial in understanding coastal processes. In the first part, we show and discuss an annual dataset provided by a monitoring system installed in a vulnerable coastal basin located in Southern Italy, subjected to human and industrial pressures. The collected data have been processed and analysed to detect the temporal evolution of the most representative parameters of the inspected site and have been compared with recordings from previous years to investigate recursive trends. In the second part, to demonstrate to what extent such type of monitoring actions is necessary and useful, the same data have been used to calibrate and run a 3D hydrodynamic model. After this, a reliable circulation pattern in the basin has been reproduced. Successively, an oil pollution transport model has been added to the hydrodynamic model, with the aim to present the response of the basin to some hypothetical cases of oil spills, caused by a ship failure. It is evident that the profitable prediction of the hydrodynamic processes and the transport and dispersion of contaminants strictly depends on the quality and reliability of the input data as well as on the calibration made. |
format | Online Article Text |
id | pubmed-6479855 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64798552019-04-29 Monitoring Systems and Numerical Models to Study Coastal Sites † Armenio, Elvira Ben Meftah, Mouldi De Padova, Diana De Serio, Francesca Mossa, Michele Sensors (Basel) Article The present work aims at illustrating how the joint use of monitoring data and numerical models can be beneficial in understanding coastal processes. In the first part, we show and discuss an annual dataset provided by a monitoring system installed in a vulnerable coastal basin located in Southern Italy, subjected to human and industrial pressures. The collected data have been processed and analysed to detect the temporal evolution of the most representative parameters of the inspected site and have been compared with recordings from previous years to investigate recursive trends. In the second part, to demonstrate to what extent such type of monitoring actions is necessary and useful, the same data have been used to calibrate and run a 3D hydrodynamic model. After this, a reliable circulation pattern in the basin has been reproduced. Successively, an oil pollution transport model has been added to the hydrodynamic model, with the aim to present the response of the basin to some hypothetical cases of oil spills, caused by a ship failure. It is evident that the profitable prediction of the hydrodynamic processes and the transport and dispersion of contaminants strictly depends on the quality and reliability of the input data as well as on the calibration made. MDPI 2019-03-30 /pmc/articles/PMC6479855/ /pubmed/30935083 http://dx.doi.org/10.3390/s19071552 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Armenio, Elvira Ben Meftah, Mouldi De Padova, Diana De Serio, Francesca Mossa, Michele Monitoring Systems and Numerical Models to Study Coastal Sites † |
title | Monitoring Systems and Numerical Models to Study Coastal Sites † |
title_full | Monitoring Systems and Numerical Models to Study Coastal Sites † |
title_fullStr | Monitoring Systems and Numerical Models to Study Coastal Sites † |
title_full_unstemmed | Monitoring Systems and Numerical Models to Study Coastal Sites † |
title_short | Monitoring Systems and Numerical Models to Study Coastal Sites † |
title_sort | monitoring systems and numerical models to study coastal sites † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479855/ https://www.ncbi.nlm.nih.gov/pubmed/30935083 http://dx.doi.org/10.3390/s19071552 |
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