Inverse identification of pollution source release information for surface river chemical spills using a hybrid...

Area of Science:

• Environmental Science
• Water Resource Management
• Computational Modeling

Background:

• Estimating contaminant source characteristics is crucial for effective emergency response to surface river pollution.
• Identifying the location, time, and quantity of contaminant injection is essential for liability assessment and response scheme design.

Purpose of the Study:

• To develop an effective pollution source inverse method for reconstructing contaminant release history.
• To provide appropriate emergency response schemes for surface river environmental pollution.
• To verify the accuracy and efficiency of the developed method.

Main Methods:

• Developed an integrated pollution source inverse method (IGSAA) combining a genetic algorithm (GA) and simulated annealing algorithm (SAA).
• Applied IGSAA to a hypothetical study and a trace study of the Truckee River.
• Compared IGSAA with traditional GA-based and SAA-based methods.

Main Results:

• The IGSAA method demonstrated superior accuracy and efficiency in contaminant source inversion compared to traditional methods.
• Successfully reconstructed contaminant source release history and characteristics in both hypothetical and real-world river scenarios.
• Validated the effectiveness of IGSAA for identifying chemical spill sources.

Conclusions:

• The developed IGSAA method is effective for identifying contaminant source characteristics and informing emergency response.
• The method aids decision-makers in quick response, emergency rescue, and enhancing river system management.
• This approach enhances supervision and management capabilities for real surface river systems facing pollution events.