Synergistic use of an oil drift model and remote sensing observations for oil spill monitoring

Padova, Diana De; Mossa, Michele; Adamo, Maria; Carolis, Giacomo De; Pasquariello, G.

doi:10.1007/s11356-016-8214-8

Cited by 30 publications

(19 citation statements)

References 37 publications

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“…Especially in this case of shallow basins subjected to strong anthropization and urban discharges, it is fundamental to monitor their hydrodynamics and water quality (De Carolis et al, 2013;De Serio and Mossa, 2014;De Serio and Mossa, 2015;De Serio and Mossa, 2016a;De Padova et al, 2017a;De Padova et al, 2017b;Armenio et al, 2018;De Serio and Mossa, 2018;Armenio et al, 2019;De Serio et al, 2020).…”

Section: Background and Summarymentioning

confidence: 99%

Meteo and hydrodynamic data in the Mar Grande and Mar Piccolo by the LIC Survey, winter and summer 2015

Mossa¹,

Armenio²,

Meftah³

et al. 2020

Preprint

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Abstract. The Coastal Engineering Laboratory (LIC) of the DICATECh of the Polytechnic University of Bari (Italy) maintains a place-based research program in the Mar Grande and Mar Piccolo of Taranto (a coastal system in southern Italy), providing records of hydrodynamic and water-quality measurements. This site is one of the most complex marine ecosystem models in terms of ecological, social, and economic activities. It is considered highly vulnerable for the presence of the naval base, of the biggest refinery of Europe and of the oil refinery. Two fixed stations have been installed, one in the Mar Grande (MG station) and another in Mar Piccolo (MP station). In the MG station constituents include wind speed and direction, air temperature and humidity, barometric pressure, net solar radiation, water salinity, water temperature, water pressure, dissolved oxygen, fluorescence, turbidity, CDOM, crude oil and refined fuels, sea currents and waves. In the MP station constituents include water temperature, sea currents and waves. We provide a summary of how these data have been collected by the research group and how they can be used to deepen understanding of the hydrodynamic structures and characteristics of the basin. These data are available at https://doi.org/10.5281/zenodo.4044121 (Mossa et al., 2020).

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Section: Background and Summarymentioning

confidence: 99%

Meteo and hydrodynamic data in the Mar Grande and Mar Piccolo by the LIC Survey, winter and summer 2015

Mossa¹,

Armenio²,

Meftah³

et al. 2020

Preprint

Self Cite

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“…Several researchers have employed oil slick spreading equations and the resulting area to calculate the average thickness of slicks [82][83][84]. These are, at best, estimates since the spreading equations are not good predictors and since both thin and thick slicks are counted in the area calculations.…”

Section: Modeling and Calculationsmentioning

confidence: 99%

The Challenges of Remotely Measuring Oil Slick Thickness

Fingas¹

2018

Remote Sensing

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The thickness of oil spills on the sea is an important but poorly studied topic. Means to measure slick thickness are reviewed. More than 30 concepts are summarized. Many of these are judged not to be viable for a variety of scientific reasons. Two means are currently available to remotely measure oil thickness, namely, passive microwave radiometry and time of acoustic travel. Microwave radiometry is commercially developed at this time. Visual means to ascertain oil thickness are restricted by physics to thicknesses smaller than those of rainbow sheens, which rarely occur on large spills, and thin sheen. One can observe that some slicks are not sheen and are probably thicker. These three thickness regimes are not useful to oil spill countermeasures, as most of the oil is contained in the thick portion of a slick, the thickness of which is unknown and ranges over several orders of magnitude. There is a continuing need to measure the thickness of oil spills. This need continues to increase with time, and further research effort is needed. Several viable concepts have been developed but require further work and verification. One of the difficulties is that ground truthing and verification methods are generally not available for most thickness measurement methods.

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“…The MODIS satellite visual-spectrum broadband data 32 , and synergic use of optical remote-sensing and numerical modelling can both detect and characterize marine oil slicks 33 . And the later method has also been proved correct in Literature 34 .…”

mentioning

confidence: 91%

The Influence of Oil leaking rate and Ocean Current Velocity on the Migration and Diffusion of Underwater Oil Spill

Huang

et al. 2020

Sci Rep

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Severe environmental pollution and huge economic losses would be caused by submarine oil spill with the increasing development of petroleum energy in sea. In order to predict the law of migration of oil spill from submarine pipelines accurately, the volume of fluid (VOF) model and realizable k-ε turbulence model were employed to establish numerical simulation of submarine oil spill, and the experiments were used to verify the feasibility of the numerical models. Different oil leaking rate and ocean velocity were simulated in the study. The simulation results indicated that comparing with oil leaking rate (set vertical migration velocity, Uo), current velocity (set horizontal migration velocity, Uw) has a greater influence on the migration of the oil spilling; the actual vertical migration velocity (Uo1), actual horizontal migration velocity (Uw1) and R1 (the ratio of Uo1 and Uw1) are positively correlated with R (the ratio of Uo and Uw), and they both fluctuate within a small range no matter how large R is; when 20 ≤ R ≤ 150, R1 fits a linear fit curve with curve as R1 = 0.66932 + 0.00215 R, which can provide a theoretical reference to the recovery system of underwater pipeline oil spilling emergency.

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Synergistic use of an oil drift model and remote sensing observations for oil spill monitoring

Cited by 30 publications

References 37 publications

Meteo and hydrodynamic data in the Mar Grande and Mar Piccolo by the LIC Survey, winter and summer 2015

Meteo and hydrodynamic data in the Mar Grande and Mar Piccolo by the LIC Survey, winter and summer 2015

The Challenges of Remotely Measuring Oil Slick Thickness

The Influence of Oil leaking rate and Ocean Current Velocity on the Migration and Diffusion of Underwater Oil Spill

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