Removal of river-stage fluctuations from well response using multiple regression

Area of Science:

• Hydrogeology
• Environmental Science
• Geoscience

Background:

• Unconfined aquifers near rivers experience hydrologic responses due to river stage fluctuations.
• River-induced well responses can hinder aquifer characterization and remediation monitoring.
• Understanding these interactions is crucial for managing groundwater resources and contaminant transport.

Purpose of the Study:

• To develop a method for quantifying and removing river stage influences on groundwater levels.
• To enhance the accuracy of aquifer characterization and remedial action assessments.
• To improve the estimation of groundwater flow and contaminant flux to rivers.

Main Methods:

• Utilized a time-domain, multiple-regression, convolution (superposition) method to establish river response function (RRF) relationships between river stage and well/aquifer responses.
• Applied a multiple-regression deconvolution correction approach to isolate true aquifer responses by removing river-induced effects.
• Analyzed corrected well responses for improved aquifer characterization and remediation evaluation.

Main Results:

• Successfully developed RRFs to model the impact of river stage on adjacent unconfined aquifers.
• Demonstrated the effectiveness of the deconvolution approach in removing river-induced noise from well water-level data.
• Showcased the potential for improved aquifer characterization and remediation assessment using corrected data.

Conclusions:

• The developed RRF and deconvolution methods provide a robust tool for analyzing groundwater systems influenced by rivers.
• Removing river stage effects significantly enhances the reliability of groundwater data for environmental management.
• This technique supports better decision-making for remediation strategies and contaminant transport assessments in river-connected aquifers.