The version 2.1 of PETROMAR-3D model,
created in the Center for Marine Meteorology of the Meteorology Institute of
Cuba, is presented. This Lagrangian model has been designed to describe the
physical processes of marine oil spills in the face of multiple scenarios of
the marine environment. Although it is applicable to any part of the world, it
is mainly designed for inter-American seas. The novelty has been to integrate
the processes of drift and weathering into a model, with updated methods that
incorporate 3D phenomena, a very favorable situation to achieve an operating
system in Cuba and the region for the immediate and medium term. Python was
chosen as the programming language because it has advanced libraries for
numerical modeling, automation work and other useful tools for pre-and
post-processing. By means of adapters, an important number of atmospheric,
hydrodynamic and wave models have been considered to create the scenarios
efficiently. The modular distribution in which the code has been created
facilitates its use for other dispersion analysis and biophysical applications.
Finally, a set of simple images are presented, aimed at informing
decision-makers in order to mitigate the effects of the spill on the
environment.
References
[1]
Liu, Y., MacFadyen, A., Ji, Z.G. and Weisberg, R.H. (2013) Monitoring and Modeling the Deepwater Horizon Oil Spill: A Record Breaking Enterprise. John Wiley & Sons, Hoboken, 195.
[2]
Calzada, A.E., Acuna, F.E.P., Perdomo, D.R. and Taylor, R.C. (2015) Modelación de los derrames de petróleo mediante el empleo de PETROMAR. Revista Cubana de Meteorología, 21, 57-69. http://rcm.insmet.cu/index.php/rcm/article/view/413/473
[3]
Spaulding, M.L. (2017) State of the Art Review and Future Directions in Oil Spill Modeling. Marine Pollution Bulletin, 115, 7-19. https://doi.org/10.1016/j.marpolbul.2017.01.001
[4]
Arkhipov, B.V. and Shapochkin, D.A. (2019) Modeling Oil Spills in the Sea. Mathematical Models and Computer Simulations, 11, 107-120. https://doi.org/10.1134/S2070048219010046
[5]
Fay, J.A. (1971) Physical Processes in the Spread of Oil on a Water Surface. International Oil Spill Conference, 1, 463-467. https://doi.org/10.7901/2169-3358-1971-1-463
[6]
Zheng, L., Yapa, P.D. and Chen, F. (2003) A Model for Simulating Deepwater Oil and Gas Blowouts Part I: Theory and Model Formulation. Journal of Hydraulic Research, 41, 339-351. https://doi.org/10.1080/00221680309499980
[7]
De Dominicis, M., Pinardi, N., Zodiatis, G. and Lardner, R. (2013) MEDSLIK-II, a Lagrangian Marine Surface Oil Spill Model for Short-Term Forecasting. Part 1: Theory. Geoscientific Model Development, 6, 1851-1869. https://doi.org/10.5194/gmd-6-1851-2013
[8]
Ribotti, A., Antognarelli, F., Cucco, A., Falcieri, M.F., Fazioli, L., Ferrarin, C., Olita, A., Oliva, G., Pes, A. and Quattrocchi, G. (2019) An Operational Marine Oil Spill Forecasting Tool for the Management of Emergencies in the Italian Seas. Journal of Marine Science and Engineering, 7, 1. https://doi.org/10.3390/jmse7010001
[9]
Golshan, R., Boufadel, M.C., Rodriguez, V.A., Geng, X., Gao, F., King, Th., Robinson, B. and Tejada-Martínez, A.E. (2018) Oil Droplet Transport under Non-Breaking Waves: An Eulerian RANS Approach Combined with a Lagrangian Particle Dispersion Model. Journal of Marine Sciences and Engineering, 6, 1-16. https://doi.org/10.3390/jmse6010007
[10]
Lee, J.H. and Cheung, V. (1990) Generalized Lagrangian Model for Buoyant Jets in Current. Journal of Environmental Engineering, 116, 1085-1106. https://doi.org/10.1061/(ASCE)0733-9372(1990)116:6(1085)
[11]
Fernandez, F. (2018) Seawater: Seawater Library for Python. https://github.com/pyoceans/python-seawater
[12]
Fofonoff, N.P. and Millard, R.C. (1983) Algorithms for the Computation of Fundamental Properties of Seawater, Ocean Best Practices. https://www.oceanbestpractices.net/handle/11329/109
Betancourt, F.O. (2005) Modelado de la evolución de derrames de petróleo en zonas litorales. PhD Dissertation, Universidad Nacional Autónoma de México, México.
[15]
Gutiérrez, A.R. (2012) Dispersión y caoticidad de partículas pasivas en las aguas oceánicas de la región occidental de Cuba. PhD Dissertation, Instituto de Oceanología, Cuba. https://www.oceandocs.org/handle/1834/4847
[16]
Gros, J., Dissanayake, A.L., Daniels, M.M., Barker, C.H., Lehr, W. and Socolofsky, S.A. (2018) Oil Spill Modeling in Deep Waters: Estimation of Pseudo-Component Properties for Cubic Equations of State from Distillation Data. Marine Pollution Bulletin, 137, 627-637. https://doi.org/10.1016/j.marpolbul.2018.10.047
[17]
Kotzakoulakis, K. and George, S.C. (2018) Predicting the Weathering of Fuel and Oil Spills: A Diffusion-Limited Evaporation Model. Chemosphere, 190, 442-453. https://doi.org/10.1016/j.chemosphere.2017.09.142
[18]
Spanoudaki, K., Kampanis, N., Kalogerakis, N., Zodiatis, G. and Kozyrakis, G. (2018) Modelling of Oil Spills from Deep Sea Releases. EGU General Assembly Conference Abstracts, Vienna, 8-13 April 2018, 16401.
[19]
Mackay, D. and Matsugu, R.S. (1973) Evaporation Rates of Liquid Hydrocarbon Spills on Land and Water. The Canadian Journal of Chemical Engineering, 51, 434-439. https://doi.org/10.1002/cjce.5450510407
[20]
Mackay, D., Shiu, W.Y., Hossain, K., Stiver, W., and McCurdy, D. (1982) Development and Calibration of an Oil Spill Behavior Model. Toronto Univ. (Ontario) Dept. of Chemical Engineering and Applied Chemistry, Toronto. https://www.osti.gov/biblio/5464992
[21]
Bi, Y.C., et al. (2015) A Vapor-Liquid Equilibrium Model for Petroleum Based on Two-Parameter Antoine Equation. Computers and Applied Chemistry, 32, 324-328. http://en.cnki.com.cn/Article_en/CJFDTotal-JSYH201503014.htm
[22]
Delvigne, G.A.L. and Sweeney, C. (1988) Natural Dispersion of Oil. Oil and Chemical Pollution, 4, 281-310. https://doi.org/10.1016/S0269-8579(88)80003-0
[23]
Li, Z., Spaulding, M.L. and French-McCay, D. (2017) An Algorithm for Modeling Entrainment and Naturally and Chemically Dispersed Oil Droplet Size Distribution under Surface Breaking Wave Conditions. Marine Pollution Bulletin, 119, 145-152. https://doi.org/10.1016/j.marpolbul.2017.03.048
[24]
Eley, D., Hey, M. and Symonds, J. (1988) Emulsions of Water in Asphaltene-Containing Oils 1. Droplet Size Distribution and Emulsification Rates. Colloids and Surfaces, 32, 87-101. https://doi.org/10.1016/0166-6622(88)80006-4
[25]
Qiao, P., Harbottle, D., Tchoukov, P., Wang, X. and Xu, Z. (2017) Asphaltene Subfractions Responsible for Stabilizing Water-in-Crude Oil Emulsions. Part 3. Effect of Solvent Aromaticity. Energy Fuels, 31, 9179-9187. https://doi.org/10.1021/acs.energyfuels.7b01387
[26]
Green, D.W. and Perry, R.H. (2008) Perry’s Chemical Engineers’ Handbook. Eighth Edition, McGraw-Hill, New York.
[27]
Perry, R.L., Leung , P.T., Zwissler, C., Bouchard, R., Hervey, R., Fiorentino, L., Sharma, N., Martin, K., Howden, S., Kirkpatrick, B. and Kim, H.S. (2016) Collaborative Observational and Operational Oceanography to Improve 2015 and 2016 Loop Current Forecasting in the Gulf of Mexico. OCEANS 2016 MTS/IEEE Monterey, Monterey, 19-23 September 2016, 1-8. https://doi.org/10.1109/OCEANS.2016.7761275 https://ieeexplore.ieee.org/document/7761275
[28]
Mooney, M. (1951) The Viscosity of a Concentrated Suspension of Spherical Particles. Journal of Colloid Science, 6, 162-170. https://doi.org/10.1016/0095-8522(51)90036-0
[29]
Nguyen, T. (2017) Research and Development for Oil Spill Simulation Backward in Time at East Vietnam Sea. Journal of Petroleum & Environmental Biotechnology, 8, 344. https://doi.org/10.4172/2157-7463.1000344
[30]
Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M., Wang, W. and Powers, J.G. (2008) A Description of the Advanced Research WRF Version 3. NCAR Technical Note-475+ STR.
[31]
Zou, X., Huan, W. and Xiao, Q. (1998) A User’s Guide to the MM5 Adjoint Modeling System. Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research, Boulder. https://opensky.ucar.edu/islandora/object/technotes%3A343/datastream/PDF/view
[32]
Nam (2017) North America Mesoescale Forecasting System. National Center for Environmental Information (NCEI) Formerly Known as National Climatic Data Center (NCDC). https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/north-american-mesoscale-forecast-system-nam
[33]
Moore, A.M., Arango, H.G., Broquet, G., Powell, B.S., Weaver, A.T. and Zavala-Garay, J. (2011) The Regional Ocean Modeling System (ROMS) 4-Dimensional Variational Data Assimilation Systems: Part I System Overview and Formulation. Progress in Oceanography, 91, 34-49. https://doi.org/10.1016/j.pocean.2011.05.004
[34]
Chassignet, E.P., Hurlburt, H.E., Smedstad, O.M., Halliwell, G.R., Hogan, P.J., Wallcraft, A.J., Baraille, R. and Bleck, R. (2007) The HYCOM (HYbrid Coordinate Ocean Model) Data Assimilative System. Journal of Marine Systems, 65, 60-83. https://doi.org/10.1016/j.jmarsys.2005.09.016
[35]
Martin, P.J., Barron, Ch.N., Smedstad, L.F., Campbell, T.J., Wallcraft, A.J., Rhodes, R.C., Rowley, C., Townsend, T.L. and Carroll, S.N. (2009) Navy Coastal Ocean Model (NCOM) Version 4.0 (User’s Manual). Naval Research Lab Stennis Space Center Ms Oceanography Div. https://doi.org/10.21236/ADA494652 https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/navoceano-ncom-reg
[36]
Lumkin, R., Grodsky, S.A., Centurioni, L., Rio, M.-H., Carton, J.A. and Lee, D. (2013) Removing Spurios Low-Frecquency Variability in Drifter Velocities. Journal of Atmospheric and Oceanic Technology, 30, 353-360. https://doi.org/10.1175/JTECH-D-12-00139.1
[37]
Tolman, H.L. (2002) User Manual and System Documentation of WAVEWATCH III Version 2.22. National Oceanic and Atmospheric Administration, Technical Note 222. https://polar.ncep.noaa.gov/mmab/papers/tn276/MMAB_276.pdf
[38]
The SWAN Team (2020) SWAN User Manual. SWAN Cycle III Version 41.31A. Delft University of Technology, Delft, 143 p. http://swanmodel.sourceforge.net/online_doc/swanuse/swanuse.html
[39]
GEBCO (2017) Gridded Bathymetry Data (General Bathymetric Chart of the Oceans). British Oceanographic Data Centre, Liverpool. https://www.bodc.ac.uk/data/hosted_data_systems/gebco_gridded_bathymetry_data
[40]
Pérez, F. (2013) Simulación del ascenso del petróleo derramado en el lecho marino. VII Congreso de Meteorología SOMETCUBA, La Habana.
[41]
Robert, L. and Wettre, C. (2012) Comparison of Operational Oil Spill Trajectory Forecast with Surface Drifter Trajectories in the Barens Sea. Journal Geology and Geosciences, 1, 1-8.
