Geoscience Reference
In-Depth Information
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High-resolution mapping of soil and rock stratigraphy (Davis and Annan, 1989)
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Interpretations of a fragipan in Idaho (Doolittle et al., 2000a)
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Improvement of interpretation of water table depths and groundwater flow patterns using
predictive equations (Doolittle et al., 2000b)
Determination of forest productivity on a loamy substrata glacial drift soil in Michigan
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(Farrish et al., 1990)
Assessment of Bt horizons in sandy soils (Mokma et al., 1990a) and ortstein continuity in
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selected Michigan soils (Mokma et al., 1990b)
All of the above used GPR to determine a soil feature that would have a direct affect on agricul-
tural production. But there are also what may be called “indirect” applications of GPR. An example
would be the determination of volumetric water contents in soil with GPR (van Overmeeren et al.,
1997). This is an increasing area of radar application, and this is what I mean by indirect applica-
tions of GPR to agricultural investigations.
3.4 IndIReCt GpR ApplICAtIonS to AGRICUltURAl InveStIGAtIonS
Agricultural utilization of remote sensing to detect, identify, locate, map, predict, or estimate a bur-
ied feature or object that may affect production or management is an increasing application for GPR.
This section will discuss the various ways that radar has been used for these indirect purposes. Let
us begin by looking at studies involving GPR to detect and monitor groundwater.
GPR investigations to detect and monitor groundwater have several components. It has been
used to estimate soil water content (Serbin and Or, 2004) during irrigation and drainage (Galage-
dara et al., 2005); to identify subsurface flow pathways (Collins, et al., 1994; Gish et al., 2002; Kow-
alsky et al., 2004; Gish et al., 2005) and nitrogen loss (Walthall et al., 2001); to estimate moisture
contents in the vadose zone (Alumbaugh et al., 2002); to survey perched water on anthropogenic
soils (Freeland et al., 2001); to estimate volumetric water on a field scale (Grote et al., 2003); and
to map spatial variation in surface water content to compare GPR to time domain reflectometry
(Huisman et al., 2002).
Serbin and Or (2004) reported using a GPR with a suspended horn antenna to obtain continu-
ous measurements of near surface water content dynamics. These measurements were made in sand
over silt loam textures. They concluded that radar enabled them to verify radar measurements at
well-defined spatial scales and detailed temporal resolutions not available by other remote sensing
techniques. Galagedara et al. (2005) went one step further to estimate water contents with GPR
under irrigation and drainage conditions. Specifically, they were interested in determining the opti-
mal ground wave sampling depth under irrigation and drainage situations.
Identifying subsurface flow pathways is a very important application of GPR because of what
(e.g., fertilizers, pesticides) may move with the soil water. Several investigations (Collins et al.,
1994; Gish et al., 2002, 2005; Kowalsky et al., 2004) documented potential subsurface water move-
ment. Collins et al. (1994) was one of the first to do so and will be discussed as an example.
A large portion of north-central Florida is located in a “bare-karst” region. The limestone can
be exposed at the surface or within a depth of a few meters. This area is known for sinkholes open-
ing “overnight!”. A series of sinkholes (mother with two daughter dolines) did open up in a matter
of a few days in a field and Collins et al. (1994) used this area for their investigation.
The study site was in a pasture in which horse riding and jumping took place (Collins et al.,
1994). GPR was used to identify the size of the caverns and determine subsurface flow patterns
in order to locate other potential sinkholes in the immediate area. Three grids (macro, medi, and
micro) were created, and GPR transects were made. Collins et al. (1994) were able to determine the
size of the dolines and create three-dimensional diagrams of subsurface flow. They reported that
the surface topography had preferential flow toward the dolines, and the subsurface flow patterns
were more complex. There are subsurface “depressions,” and the flow patterns were toward these
