Summary

A lab-scale infiltration experiment was conducted in a sand filled tank to observe patterns in transient multi-offset ground-penetrating radar (GPR) data. During the infiltration event, multi-offset GPR data was collected using an automated data acquisition system. The automated system used a computer controlled DC motor to position the receiving antenna along a uniaxial track across the tank, thereby allowing for continuous collection of multi-offset GPR data over the course of the experiment. Water was applied to the surface of the tank by drip irrigation where the flux was controlled with a peristaltic pump. Shifts in the radar arrivals are evident early in the experiment and progress as water content increases. Changes in velocities can be seen on both position vs. time (multi-offset) and travel time vs. experiment time (single offset) plots. By tracking the ground wave arrival, we show that it is possible to quantify the change in soil moisture and the change in wave velocities.

Introduction

The use of GPR to quantify soil moisture has become increasingly popular as it is a non-invasive method that can cover a large area to produce moisture readings with comparable accuracy to conventional methods for measuring soil water content (Huisman et al., 2001). A key reason that GPR can be used for mapping shallow moisture distributions and for monitoring soil moisture dynamics is because the velocity of an EM wave is greatly influenced by subsurface moisture content (Lunt et al. 2005). Recent work by S. Moysey (personal communication, 2010) has shown that the travel times in GPR data shift in predictable ways in response to hydrologic forcing events, such as irrigation and precipitation. That work focused, however, on data collected using single offset GPR. In contrast, multi-offset GPR data is often used to estimate subsurface wave velocities by taking advantage of the fact that travel times increase with antenna offset. Multi-offset data collection with single channel GPR systems traditionally requires antennas to be manually moved to each measurement position. This mode of data collection is inefficient, too slow for monitoring dynamic processes, and prone to positioning errors. The objective of this project is to characterize the effect of soil moisture variability on GPR data by collecting multi-offset profiles using automation technologies to limit positioning errors and collect large amounts of data in little time. In this abstract, we follow up on the work of S. Moysey (personalcommunication, 2010) by reporting the hydrologic response of multi-offset data. We expect that this work will improve field-scale characterization of soil moisture dynamics, which are of importance for applications ranging from precision agriculture to landmine detection.

Methods

Our measurements are collected using a sand-filled tank. A 0.2m thick gravel pack was installed at the base of the tank to allow for free drainage conditions. Flow rates are controlled using a peristaltic pump and measured with a flow meter. For this experiment, water was infiltrated at a rate of 5cm3/sec for 17 minutes, then stepped up to 22cm3/sec for 12 minutes (Figure 2).

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