Optimal pollution mitigation in Monterey Bay based on coastal radar data and nonlinear dynamics

Area of Science:

• Oceanography
• Environmental Science
• Remote Sensing

Background:

• High-frequency (HF) radar provides detailed surface velocity data in coastal areas.
• The application of HF radar velocity data for environmental prediction is largely unexplored.
• Monterey Bay experiences pollution from sources like agricultural runoff.

Purpose of the Study:

• To uncover and analyze a significant flow structure in Monterey Bay using HF radar data.
• To investigate the role of this flow structure in the dispersal of organic contaminants.
• To develop and demonstrate a pollution release strategy based on the identified flow structure.

Main Methods:

• Utilizing coastal HF radar observations to map surface velocities.
• Identifying and analyzing complex flow structures within the velocity data.
• Employing finite-time Lyapunov exponents to predict the motion of Lagrangian flow structures.
• Developing an HF radar-based pollution release scheme.

Main Results:

• A striking and complex flow structure was identified in Monterey Bay's coastal radar observations.
• This flow structure significantly influences the spread of organic contaminants, including agricultural runoff.
• The developed HF radar-based pollution release scheme effectively reduces pollution impact.
• Optimal pollution release times were determined based on predicted flow structure motion.

Conclusions:

• HF radar is a valuable tool for understanding coastal dynamics and predicting contaminant transport.
• The identified flow structure is key to managing pollution in estuarine and bay environments.
• Optimized pollution release strategies can significantly mitigate environmental impacts in coastal zones.