Calibration of backward-in-time model using drifting buoys in the East China Sea

In the process of oil exploitation and transportation, large amounts of crude oil are often spilled, resulting in serious pollution of the marine environment. Forecasting oil spill reverse trajectories to determine the exact oil spill sources is crucial for taking proactive and effective emergency m...

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Main Authors: Fangjie Yu, Jiaojiao Li, Yang Zhao, Qiuxiang Li, Ge Chen
Format: Article
Language:English
Published: Elsevier 2017-07-01
Series:Oceanologia
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S0078323417300131
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spelling doaj-eb5627eb45a844a8b6b65650e4214bf22020-11-24T21:19:57ZengElsevierOceanologia0078-32342017-07-0159323824710.1016/j.oceano.2017.01.003Calibration of backward-in-time model using drifting buoys in the East China SeaFangjie Yu0Jiaojiao Li1Yang Zhao2Qiuxiang Li3Ge Chen4College of Information Science and Engineering, Ocean University of China, Qingdao, PR ChinaCollege of Information Science and Engineering, Ocean University of China, Qingdao, PR ChinaCollege of Liberal Arts, Journalism and Communication, Ocean University of China, Qingdao, PR ChinaCollege of Information Science and Engineering, Ocean University of China, Qingdao, PR ChinaCollege of Information Science and Engineering, Ocean University of China, Qingdao, PR ChinaIn the process of oil exploitation and transportation, large amounts of crude oil are often spilled, resulting in serious pollution of the marine environment. Forecasting oil spill reverse trajectories to determine the exact oil spill sources is crucial for taking proactive and effective emergency measures. In this study, the backward-in-time model (BTM) is proposed for identifying sources of oil spills in the East China Sea. The wind, current and random walk are three major factors in the simulation of oil spill sources. The wind drag coefficient varies along with the uncertainty of the wind field, and the random walk is sensitive to various traits of different regions, these factors are taken as constants in most of the state-of-the-art studies. In this paper, a self-adaptive modification mechanism for drift factors is proposed, which depends on a data set derived from the drifter buoys deployed over the East China Sea shelf. It can be well adapted to the regional characteristics of different sea areas. The correlation factor between predicted positions and actual locations of the drifters is used to estimate optimal coefficients of the BTM. A comparison between the BTM and the traditional method is also made in this study. The results presented in this paper indicate that our method can be used to predict the actual specific spillage locations.http://www.sciencedirect.com/science/article/pii/S0078323417300131Wind drag coefficientRandom walkDrifter buoysOil spill reverseOil spill model
collection DOAJ
language English
format Article
sources DOAJ
author Fangjie Yu
Jiaojiao Li
Yang Zhao
Qiuxiang Li
Ge Chen
spellingShingle Fangjie Yu
Jiaojiao Li
Yang Zhao
Qiuxiang Li
Ge Chen
Calibration of backward-in-time model using drifting buoys in the East China Sea
Oceanologia
Wind drag coefficient
Random walk
Drifter buoys
Oil spill reverse
Oil spill model
author_facet Fangjie Yu
Jiaojiao Li
Yang Zhao
Qiuxiang Li
Ge Chen
author_sort Fangjie Yu
title Calibration of backward-in-time model using drifting buoys in the East China Sea
title_short Calibration of backward-in-time model using drifting buoys in the East China Sea
title_full Calibration of backward-in-time model using drifting buoys in the East China Sea
title_fullStr Calibration of backward-in-time model using drifting buoys in the East China Sea
title_full_unstemmed Calibration of backward-in-time model using drifting buoys in the East China Sea
title_sort calibration of backward-in-time model using drifting buoys in the east china sea
publisher Elsevier
series Oceanologia
issn 0078-3234
publishDate 2017-07-01
description In the process of oil exploitation and transportation, large amounts of crude oil are often spilled, resulting in serious pollution of the marine environment. Forecasting oil spill reverse trajectories to determine the exact oil spill sources is crucial for taking proactive and effective emergency measures. In this study, the backward-in-time model (BTM) is proposed for identifying sources of oil spills in the East China Sea. The wind, current and random walk are three major factors in the simulation of oil spill sources. The wind drag coefficient varies along with the uncertainty of the wind field, and the random walk is sensitive to various traits of different regions, these factors are taken as constants in most of the state-of-the-art studies. In this paper, a self-adaptive modification mechanism for drift factors is proposed, which depends on a data set derived from the drifter buoys deployed over the East China Sea shelf. It can be well adapted to the regional characteristics of different sea areas. The correlation factor between predicted positions and actual locations of the drifters is used to estimate optimal coefficients of the BTM. A comparison between the BTM and the traditional method is also made in this study. The results presented in this paper indicate that our method can be used to predict the actual specific spillage locations.
topic Wind drag coefficient
Random walk
Drifter buoys
Oil spill reverse
Oil spill model
url http://www.sciencedirect.com/science/article/pii/S0078323417300131
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AT jiaojiaoli calibrationofbackwardintimemodelusingdriftingbuoysintheeastchinasea
AT yangzhao calibrationofbackwardintimemodelusingdriftingbuoysintheeastchinasea
AT qiuxiangli calibrationofbackwardintimemodelusingdriftingbuoysintheeastchinasea
AT gechen calibrationofbackwardintimemodelusingdriftingbuoysintheeastchinasea
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