Scientists used a mathematical approach to uncover path-defining “structures” beneath Gulf waters that governed the movement of oil following the Deepwater Horizon oil spill. This method could give decision makers quick and reliable information to support evacuations, interventions for marine life, and use of dispersants.

They published their findings in the March 2012 edition of the Proceedings of the National Academy of Sciences: Forecasting sudden changes in environmental pollution patterns.

Researchers analysed Lagrangian coherent structures (LCSs) to identify below-surface pushes and pulls – in place of traditional weather forecasting models – that created “major short-term changes” to the flow of water and influenced the movement of dispersed oil. Analysis of LCS, “the recently discovered hidden skeleton behind complex mixing patterns in unsteady flows,” uses immediate information about velocity of water flow or air circulation rather than the computer-generated models of weather used by scientists and responders in 2010. In the summer following the spill, researchers observed that “uncertainties in the spread of the pollutant plume had severe financial implications,” and reduced the effectiveness of response efforts.

With LCS analysis, scientists were able to “obtain remarkably accurate predictions of instabilities in the shape of the spill.” The scientists envision broad applications of LCS-core analysis in making predictions for other environmental pollutants in the air (such as ash clouds) or water (such as red tides), potentially reducing ecologic and economic impacts. Increased accuracy in forecasts of the paths of contaminants in water or air can help in decision making, resource allocation, model validation, and scenario analysis.

The study authors are María J. Olascoaga and George Haller (Proceedings of the National Academy of Sciences 2012

(spill-international.com, Edited by Topco)