Toward closed-loop remediation: A dynamic optimization approach for hydraulic conductivity estimation and...

Area of Science:

• Environmental Science
• Hydrogeology
• Geostatistics

Background:

• Accurate characterization of the hydraulic conductivity field (K-field) is crucial for effective contaminated site remediation.
• Traditional methods struggle with K-field heterogeneity due to limited data, leading to inefficient and costly remediation designs.

Purpose of the Study:

• To develop and evaluate a dynamic iterative optimization framework for improved K-field characterization and adaptive remediation planning.
• To integrate parameter inversion and remediation design into a closed-loop simulation-observation-update-optimization system.

Main Methods:

• Utilized pilot point parameterization and simulation-optimization techniques for iterative K-field updating.
• Dynamically adjusted remediation strategies based on real-time monitoring data within a closed-loop framework.

Main Results:

• Demonstrated significant improvements in K-field accuracy, indicated by reduced LRMSE and increased SCC over iterations.
• The dynamic framework achieved higher contaminant removal rates and lower total pumping volumes compared to static remediation plans.

Conclusions:

• The proposed dynamic framework offers a practical and adaptive solution for managing complex contaminated sites in heterogeneous aquifers.
• This approach enhances remediation effectiveness and reduces operational costs by improving K-field characterization and optimizing remediation strategies.