Environmental Restoration: GPR for Cranberry Bog Reclamation
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Environmental Restoration: GPR for Cranberry Bog Reclamation

A Sensors & Software customer describes using a NOGGIN® 250 GPR for a unique application – helping to restore a former cranberry bog to its natural state as part of a local environmental restoration program.

By Doria Kutrubes
Radar Solutions International

 

Introduction

Cranberries have been produced in the USA for almost two centuries. They are an unusual crop in that they grow best in bogs, which consist of fresh water underlain by layers of sand, peat, gravel, and clay. Over the decades, many bogs were artificially created by flooding areas for the purpose of cultivating cranberries. Now, for environmental purposes, some jurisdictions are working to restore former cranberry bogs to their natural, pristine conditions.

Radar Solutions International (RSI), Inc. conducted a series of ground penetrating radar (GPR) surveys to map stratigraphic layering at four different former cranberry bogs, totaling over 60 acres. The subsurface information derived from the GPR survey is being used as part of a local environmental restoration program.
 

Survey Methodology

RSI used Sensors & Software’s NOGGIN® 250 MHz GPR system, and synchronized it with a sub-centimeter GPS, which provided real-time geo-referencing of our GPR traverses (Figures 1 and 2).

Figure 1
A NOGGIN® 250 with high accuracy GPS was pulled around former cranberry bogs to map subsurface layering.

The seamless integration of the NOGGIN® 250 and our GPS, enabled our field crew to be extremely productive, allowing RSI personnel to focus exclusively on data collection, rather than spending time setting up a survey grid. We found that, compared to previous GPR service providers tasked with surveying the bog with older GPR equipment from another manufacturer, we could collect five times the data in a single day. Using GPR-GPS synchronization, the maximum line spacing throughout each cell in these bogs, was no greater than 10 to 15 feet apart (Figure 2). The high data density provided confidence in the conditions between GPR lines.

Synchronizing the GPS with the GPR also saved post-processing time, as GPR lines did not have to be assembled into a grid file using the GFP_Edit utility software, as their positions were already georeferenced.

Figure 2
GPS paths of the GPR lines shown on Google Earth, showing the typical GPR data density collected in the 60 acres of the bog surveys.

The other advantage of the NOGGIN®, is that it allows the real-time “stacking” of GPR signal, increasing the overall investigative depth of the GPR compared to older GPR systems.
 

Interpretation

At this site, the highest-amplitude reflections occurred where there was a lithologic change, such as between the sand fill, added by the cranberry farms, and native peat layers beneath. Low to high amplitude internal reflections were also observed within the primary peat layer, which occurred where there is a sudden change in silt/sand content, possibly caused by a flooding event (Figure 3).

Figure 3
Example GPR profile from the Bog. The bottom of sand reflector is shown in red. Below the sand is a reflection corresponding to the primary peat layer, the bottom of which is shown in cyan. In places, there are weak to strong internal reflections within the primary peat layer; the pattern of the weaker reflections suggesting that the peat layer becomes more homogeneous towards the center of the bog. The multiple, strong reflections at the bottom of the primary peat bottom (cyan) suggests the deeper layer is a sandy peat. The greater the sand or silt content within the peat, the stronger and more numerous the reflections. This contact between the two peat layers is suggestive of a more active depositional environment, such as may occur after a flood event.

To map the depth of the lithologic layers, it was necessary to obtain an accurate velocity of the GPR signal through the saturated layers. GPR velocity varies with mineralogy and water content and is often extracted by fitting a curve to a hyperbola in the GPR data. However, in this case, there were no hyperbolic responses in the GPR data to work with.

Another method to determine the GPR velocity is to correlate a lithologic layer of known depth to a reflector in the GPR data. To do this, cores were drilled using a hand-auger at 7 locations throughout each bog (Figures 4 & 5). By correlating the lithologic layers observed in the cores with reflectors seen in the GPR data, the velocity of the GPR signal through the mostly saturated sand/fill and native peat was determined to be about 0.235 ft/ns.

GPR cross-sections were interpreted using the EKKO_Project™ (V5 R3) GPR data analysis software, created by Sensors & Software. Using the Interpretation module, we were able to identify, and “pick” layers attributed to the sand-peat interface, as well as the interface between the bottom of the peat and deeper glacial/depositional material.

RSI extracted the depths of each picked layer as a GPR Project Report spreadsheet (CSV) file and created contour maps of thicknesses and depths using the SURFER© program, created by Golden Software, Inc. (Figures 4 & 5).
 

Results

Interpreted GPR results from multiple bog sites show that the longer the cranberry bog was in operation, the thicker the sand topping the peat. Typically, the sand ranged between 1.5 and 3 feet in thickness, but in some areas, the sand was more than 5 feet (Figure 4) .

Figure 4
Contour map of sand thickness and core locations. Thicker areas are red.

We also observed that typically the peat was more than 16 feet in thickness in the center of the bog and tapered to only a few feet in thickness at the edges (Figure 5).

Figure 5
Contour map of peat thickness and core locations. Thicker areas a purple.

 

Summary

The GPR survey of the former cranberry bogs was very successful. The fresh water in the bogs had low TDS (total dissolved solids) and the sediments, low electrical conductivity. This allowed the NOGGIN® 250 GPR signals to penetrate to depths greater than 20 feet – GPR depths that are not typical in many materials. The detailed information that RSI discovered about the current state of the bogs proved invaluable to begin the planning process of returning them to their natural state.

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