agricultural field, monitoring the temporal changes in soil conditions can be
as important as understanding spatial heterogeneity when it comes to determining
the locally-optimized application rates of key agricultural inputs. For
example, the monitoring of soil water content is needed to decide on the amount
and timing of irrigation. On-the-go soil sensing technology provides a way to
rapidly obtain high-resolution, multiple data layers to reveal soil spatial
variability, at a relatively low cost. To take advantage of this information,
it is important to define the locations, which represent diversified field
conditions, in terms of their potential to store and release soil water.
Choosing the proper locations and the number of soil monitoring sites is not
straightforward. In this project, sensor-based maps of soil apparent electrical
conductivity and field elevation were produced for seven agricultural fields in
Nebraska, USA. In one of these fields, an eight-node wireless sensor network
was used to establish real-time relationships between these maps and the Water
Stress Potential (WSP) estimated using soil matric potential measurements. The
results were used to model hypothetical WSP maps in the remaining fields.
Different placement schemes for temporal soil monitoring sites were evaluated
in terms of their ability to predict the hypothetical WSP maps with a different
range and magnitude of spatial variability. When a large number of monitoring
sites were used, it was shown that the probability for uncertain model
predictions was relatively low regardless of the site selection strategy.
However, a small number of monitoring sites may be used to reveal the
underlying relationship only if these locations are chosen carefully.
Cite this paper
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