Improving optimization efficiency for the total pollutant load allocation in large two-dimensional water areas: Bohai...

Area of Science:

• Environmental Science
• Water Quality Management
• Computational Oceanography

Background:

• Total pollutant load allocation (TPLA) is crucial for water quality management but can be computationally intensive.
• Existing optimization methods face challenges with numerous water quality constraints, leading to lengthy calculation times.

Purpose of the Study:

• To develop and evaluate an efficient method for solving TPLA optimization problems under water quality constraints.
• To reduce the computational burden associated with TPLA in complex marine environments.

Main Methods:

• Introduced a Trial and Error Method (TEM) to iteratively remove redundant points in optimization calculations.
• Applied TEM to TPLA for the Bohai Sea, utilizing both structured and non-structured model grids.
• Validated the method's efficiency against standard optimization approaches.

Main Results:

• TEM reduced calculation time to approximately 2 minutes for over 100,000 model grids meeting water quality standards.
• Achieved up to a 98.9% improvement in optimization efficiency.
• Identified that ~90% of total nitrogen (TN) load reduction in the Bohai Sea should originate from 56 pollution sources, with 85% of this reduction achievable from just 10 sources.

Conclusions:

• The TEM offers a highly efficient solution for TPLA optimization problems, significantly outperforming traditional methods.
• This method provides a practical tool for effective water quality management and pollutant reduction strategies in large marine ecosystems like the Bohai Sea.