An iterative strategy for contaminant source localisation using GLMA optimization and Data Worth on two synthetic 2D...

Area of Science:

• Environmental science
• Hydrogeology
• Geochemistry

Background:

• Accurate contaminant source localization is crucial for effective environmental remediation.
• Heterogeneous subsurface properties and unknown source characteristics pose significant challenges.

Purpose of the Study:

• To develop and evaluate a contaminant source localization strategy for continuous sources in heterogeneous fields.
• To integrate parameter estimation with data worth analysis for optimal measurement placement.

Main Methods:

• Utilized the Gauss-Levenberg-Marquardt algorithm combined with data worth analysis for iterative parameter estimation.
• Employed a data collection strategy focused on reducing uncertainty in source location.
• Validated the approach using two-dimensional synthetic models with varying complexity.

Main Results:

• Achieved good estimates for contaminant source location and dispersivity with acceptable normalized root-mean-square error (NRMSE).
• Iterative data acquisition demonstrably decreased the standard deviation of the source location and improved NRMSE.
• The estimated hydraulic conductivity fields retained key features of the original fields.

Conclusions:

• The developed strategy is parsimonious, applicable to real-world scenarios, and effective in contaminant source localization.
• Iterative data collection significantly enhances the accuracy and reliability of source identification.
• The method successfully estimates key hydrogeological parameters alongside source location.