Towards optimal sampling schedules for integral pumping tests

Area of Science:

• Environmental Science
• Hydrogeology
• Geochemistry

Background:

• Conventional groundwater sampling may miss contaminant plumes due to sparse sampling points.
• The integral pumping test (IPT) method enhances sampled volume for better plume characterization.
• Existing IPT methodology lacks established guidelines for optimal sampling schedule design.

Purpose of the Study:

• To investigate the impact of sampling schedules on the accuracy of IPT-derived parameters.
• To provide initial insights for developing optimal sampling strategies for IPT.
• To evaluate the influence of sample number and timing on concentration estimations.

Main Methods:

• Analysis of 30 high-frequency concentration-time series from IPT.
• Simulation of various sampling schedules by modifying original data.
• Assessment of relative errors in average aquifer concentration (C(av)) estimation.

Main Results:

• Reduced sample numbers and higher data variability increase C(av) estimation errors.
• Sampling schedules with only three samples showed maximum errors up to 22%.
• Constant time intervals between samples resulted in the lowest estimation errors.

Conclusions:

• The number and timing of samples significantly affect IPT accuracy.
• Constant time interval sampling is a reliable strategy for IPT data acquisition.
• Further research is needed to establish comprehensive IPT sampling guidelines.