A Comprehensive Review of Oil Spill Fate Models and Operational Tools: Capabilities and Applicability to the Caspian Sea

The Caspian Sea’s unique environment and intense hydrocarbon extraction make it a high-risk, understudied region for oil spill modelling. This review assesses the physical, chemical, and biological processes governing oil spill transport and fate, and evaluates the principal numerical tools available for the Caspian Sea context. The weathering processes are reviewed from foundational formulations to operational implementations. Key research challenges identified include the absence of photo-oxidation from operational models, limited laboratory data for Caspian crude oil types, and simplified biodegradation parameterizations. Hydrodynamic forcing uncertainty, arising from the lack of a dedicated operational ocean model, remains the dominant source of trajectory forecast error. Seven operational oil spill modelling tools and the ROMS hydrodynamic platform are reviewed. Only OSCAR and MIKE 21 have documented applications to the Caspian Sea, representing a significant regional gap. ROMS is identified as the most suitable hydrodynamic platform for future operational forecasting. Finally, the integration of machine learning and deep learning methods, including neural network trajectory prediction and SAR detection, is discussed as a promising frontier for improving forecast accuracy in this data-sparse environment.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2026-08-18
DOI
https://doi.org/10.3390/jmse14161531
Primary Topic
Oil Spill Detection and Mitigation
Type
article
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article

A Comprehensive Review of Oil Spill Fate Models and Operational Tools: Capabilities and Applicability to the Caspian Sea

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A Comprehensive Review of Oil Spill Fate Models and Operational Tools: Capabilities and Applicability to the Caspian Sea

Abdurashid Aliuly, Abzal Seitov, Tangnur Amanzholov, Aziz Kudaikulov, А. Kаltayev, D. Baimbetov, Alibek Kuljabekov, Bakytzhan Assilbekov, Spartak Shabilov, Samal Syrlybekkyzy
article en

Abstract

The Caspian Sea’s unique environment and intense hydrocarbon extraction make it a high-risk, understudied region for oil spill modelling. This review assesses the physical, chemical, and biological processes governing oil spill transport and fate, and evaluates the principal numerical tools available for the Caspian Sea context. The weathering processes are reviewed from foundational formulations to operational implementations. Key research challenges identified include the absence of photo-oxidation from operational models, limited laboratory data for Caspian crude oil types, and simplified biodegradation parameterizations. Hydrodynamic forcing uncertainty, arising from the lack of a dedicated operational ocean model, remains the dominant source of trajectory forecast error. Seven operational oil spill modelling tools and the ROMS hydrodynamic platform are reviewed. Only OSCAR and MIKE 21 have documented applications to the Caspian Sea, representing a significant regional gap. ROMS is identified as the most suitable hydrodynamic platform for future operational forecasting. Finally, the integration of machine learning and deep learning methods, including neural network trajectory prediction and SAR detection, is discussed as a promising frontier for improving forecast accuracy in this data-sparse environment.

Journal of Marine Science and EngineeringVol. 14(16)
Al-Farabi Kazakh National University (KZ), Satbayev University (KZ), Caspian University (KZ), Ionosphere Institute (KZ)
Life below water
Openalex Percentile: Top 19%
Oil Spill Detection and Mitigation
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