Geoscience Reference
In-Depth Information
20.0
26.8
22.9
15.0
19.2
15.2
10.0
11.6
7.6
5.0
4.0
N
0.0
N
0.0
0.0
4.0
7.6
15.2
Distance (m)
11.6
19.2
22.9
26.8
0.0
5.0
10.0
15.0
20.0
Distance (m)
(b)
(a)
fIGURe 1.1
Ground-penetrating radar drainage pipe detection examples: (a) agricultural test plot in north-
west Ohio and (b) golf course green in central Ohio.
fertilizer, soil amendments, pesticides, and even tillage effort (Morgan and Ess, 1997; National
Research Council, 1997). The benefits of precision agriculture to farmers are maximized crop
yields and reduced input costs. There is an important environmental benefit as well. Overapplica-
tion of agrochemicals and soil tillage is fairly common. Because precision agriculture operations
result in optimal amounts of fertilizer, soil amendments, pesticides, and tillage applied on different
parts of the field, there are potentially less agrochemicals and sediment released offsite via subsur-
face drainage and surface runoff. With reduced offsite discharge of agrochemicals and sediment,
adverse environmental impacts on local waterways are diminished. In essence, precision agricul-
ture techniques allow a farm field to be divided into different management zones for the overall
purpose of optimizing economic benefits and environmental protection.
Geophysical surveys can have an important role in precision agriculture. The apparent soil elec-
trical conductivity (EC
a
) map of a farm field, obtained from resistivity or electromagnetic induction
measurements, is often significantly correlated with the crop yield map for the same field. Presented
in Figure 1.2 is an example comparing EC
a
and soybean yield for a 3 ha field in northwest Ohio.
The spatial correlation coefficient (r) between EC
a
and soybean yield is −0.51 for the field shown
in Figure 1.2. Over a two-year period for three different fields, Jaynes et al. (1995b) found r values
between EC
a
and corn/soybean yield of −0.73, −0.63, −0.55, −0.50, −0.09, and 0.45, so in five out of
six cases for this study, there was substantial correlation.
Furthermore, the mapped horizontal EC
a
patterns for a farm field often tend to remain consis-
tent over time, which implies that the horizontal EC
a
pattern is governed by lateral variations in
soil properties (Allred et al., 2005b, 2006; Lund et al., 1999). The EC
a
can be affected in a complex
manner by a number of different soil properties; therefore, a limited soil sampling and analysis
program is typically required to determine which soil property or properties have the greatest influ-
ence on the horizontal EC
a
field pattern. Again, discussions regarding the effect of soil conditions
and soil properties on soil electrical conductivity can be found in Chapters 2, 4, and 5. Soil property
information based on EC
a
measurement is useful for formulating management practices (strategies
for fertilizer, soil amendment, and pesticide application along with tillage effort) that will improve
crop yields while limiting the offsite release of agrochemicals and sediment. Consequently, because
the spatial pattern for crop yield commonly exhibits a strong correlation with the horizontal EC
a
pattern, which is in turn governed by lateral changes in soil properties, it becomes apparent that EC
a
maps generated from resistivity and electromagnetic induction surveys can be a valuable precision
agriculture tool providing insight on how to best divide a field into zones based on soil property
