Increasing the Accuracy in Forecasting the Surface Drifter Trajectory by Using Data Assimilation

Document Type : Original Research Paper


Faculty of Basic Sciences, Imam Khamenei University of Marine Sciences, P.O.Box 43491-63439, Zibakonar, Gilan, Iran


Predicting the path of pollution in the marine area is one of the most important concerns for those involved in environmental studies. In this paper, we have discussed the capabilities of using the data assimilation method in the FVCOM numerical model in forecasting the movement path of a surface drifter in the Strait of Hormuz. Initially, the FVCOM model was implemented for particle tracking by using environmental data in the Strait of Hormuz. Then tidal gages data of the Strait of Hormuz were assimilated in the numerical model using the nudging method. The results of the two runs were compared with field measurements data using statistical parameters such as bias and correlation coefficient. Statistical analysis and visual comparisons depicted the ability of data assimilation in optimizing the model water level outputs and reducing the differences between drifter location and model results and also the rate of the distance between them. 


Main Subjects

Abbasi, R., Chegini, V., Sadrinasab, M.,  & Siadatmousavi, S. M. (2018). Correcting the Sea Surface Temperature by Data Assimilation over the Persian Gulf. Iranian Journal of Science & Technology, Transactions A: Science. 43:143-149. 10.1007/s40995-017-0357-z.
Abbasi, R., Chegini, V., Sadrinasab, M., & Siadatmousavi, S. M. (2017). Capabilities of data assimilation in correcting sea surface temperature in the Persian Gulf. Pollution. 3(2): 273-283. 
Abbasi,R., Chegini,V., Sadrinasab, M., & Siadatmousavi, S. M. (2018). Optimization of the modeled surface temperature by assimilation of SST data over the Persian Gulf. Indian Journal of Geo-Marine Sciences. 47: 1803-1808.
Agamuthu, P., Mehran, S., Norkhairah A., & Norkhairiyah, A. (2019). Marine debris: A review of impacts & global initiatives. Waste Management & Research. 37(10):987-1002. 
Antil, H., Lohner, R., & Price, R. (2021). Data Assimilation with Deep Neural Nets Informed by Nudging.
Chen, C., Liu, H. & Beardsley, R.C. (2003). An unstructured grid, finite-volume, three-dimensional, primitive equations ocean model: application to coastal ocean & estuaries. Journal of Atmospheric & Oceanic Technology, 20(1): 159-186.
Darvishi, M., & Ahmadi, G. (2014). Data assimilation techniques & modelling uncertainty in geosciences. The International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences. XL-2/W3: 85-90. 
Galgani, F., Brien, A. S., Weis, J., Ioakeimidis, C., Schuyler, Q., & Makarenko, I. (2021). Are litter, plastic & microplastic quantities increasing in the ocean? Micropl. Nanopl. 1. doi: 10.1186/s43591-020-00002-8.
Chassignet, E. P., Xu, X., & Zavala-Romero, O. (2021). Tracking Marine Litter with a Global Ocean Model: Where Does It Go? Where Does It Come From?. Frontiers in Marine Science. 8: 2296-7745.
Gorman, D., Gutiérrez, A., Turra, A., Manzano, A., Balthazar-Silva, D., Oliveira, N., & Harari, J. (2020). Predicting the Dispersal & Accumulation of Microplastic Pellets Within the Estuarine & Coastal Waters of South-Eastern Brazil Using Integrated Rainfall Data & Lagrangian Particle Tracking Models. Frontiers in Environmental Science. 8.
Handyman, D ., Purba, N. P., Pranowo, W ., Harahap, S ., Dante, I ., Yuliadi, L .,  & Faizal, I. (2019). Microplastics Patch Based on Hydrodynamic Modeling in The North Indramayu, Java Sea. Polish Journal of Environmental Studies. 28:  1-8. 
Moazzami, H ., Siadatmousavi, S.M., & Mazaheri, S. (2016). Data Assimilation for Wave Data in Persian Gulf Using WAVEWATCH- III Spectral Model. International Journal of Maritime Technology. 12: 115-125.
Nearing, G., Yatheendradas, S., Crow, W., Zhan, X., Liu, J., & Chen, F. (2018). The Efficiency of Data Assimilation. Water Resources Research. 54. 10.1029/2017WR020991.
Ondara, K., Wisha, U., & Panjaitan, S. (2021). Particle Tracking Model Approach for Analyzing Crude Oil Spill (Palm Fatty Acid Distillate) in Bayur Bay Based on Navier Stokes Discrete. Buletin Oseanografi Marina. 10: 67-74. 
Reynolds, R. M. (1993). Physical Oceanography of the Persian Gulf, Strait of Hormuz, & the Gulf of Oman—Results from the Mt Mitchell expedition, Marine Pollution Bulletin. 27: 35– 59.
Serpoushan, N., Zeinoddini, M., & Golestani, M. (2013). An Ensemble Kalman Filter Data Assimilation Scheme for Modeling the Wave Climate in Persian Gulf. Proceedings of the International Conference on Offshore Mechanics & Arctic Engineering - OMAE. 5. 10.1115/OMAE2013-10399.
Swiatek, D. (2010). Application of the Newtonian nudging data assimilation method for the Biebrza River flow model.
Van Sebille, E., Aliani, S., Law, K. L., Maximenko, N., Alsina, J. M., Bagaev, A., ... & Wichmann, D. (2020). The physical oceanography of the transport of floating marine debris. Environmental Research Letters, 15(2), 023003. Wang, B., Zou, X., & Zhu, J. (2000). Data assimilation & its application. Proceedings of the National Academy of Sciences. 97: 11143-11144.
Zhao, E., Mu, L., Qu, K., Shi, B., & Yu, Y. (2018). Numerical investigation of pollution transport & environmental improvement measures in a tidal bay based on a Lagrangian particle-tracking model. Water Science & Engineering. 11: 23-38.