Different readings in soil moisture sensors are caused by spatial variation in water content (see part 1). These readings provide researchers valuable information about soil texture, watering patterns, and water use. This week, learn two more strategies to keep in mind when trying to understand the varying patterns of soil moisture at your research or irrigation site.
In some crop studies, it may be important to account for horizontal variation.
Strategy #2: Crop Studies—Representing Variation in a Homogeneous Environment
In some research projects, it will be important to account for horizontal variation. How variable is the water content across a field? We did an experiment in which we set out a transect across a field of bare, tilled soil. Using a METER EC-5 soil moisture probe connected to a Procheck meter, we sampled water content at one-meter intervals over a 58-meter distance. The individual readings are shown in Figure 1.
Figure 1. You can determine how many samples are necessary to characterize a homogeneous area in about an hour using and EC-5 soil moisture sensor and a ProCheck.
In this data set the samples are not spatially correlated. The variation is apparent. The mean water content of the data set is 0.198 m3m-3. The standard deviation is 0.023 m3m-3 . The coefficient of variation is 12%. Using some simple geostatistics, we determined that three carefully placed sites would adequately represent the variation present in this very homogeneous environment. Of course, in some environments, samples will not be independent. If a semivariogram indicates that some underlying spatial factor influences soil moisture variability, you will have to consider that in your experimental design.
By taking into account the major relevant sources of soil moisture variation, you can plan enough sampling locations to draw conclusions from your data.
Strategy #3: Ecology Studies—Heterogeneous Environments
On a forested hillside, horizontal variation in soil moisture will obviously be significant. Determining how many sensors to use and where to place them is not at all trivial. Stratified sampling—systematically sampling from more uniform subgroups of a heterogeneous population—may be a better way to deal with this kind of variety. The researcher classifies the site into strata (eg., forested canopy, brush, hillside, valley) and evaluates the number of samples needed to statistically represent the variation present within each stratum.
Many people allow for the variation in soil moisture values that come from slope, orientation, vegetation, and canopy cover. Some fail to consider the important soil-level variations that come from soil type and density. By taking into account the major relevant sources of soil moisture variation, you can plan enough sampling locations to draw reasonable conclusions from your data. Choose too few locations, and you run the risk of missing the patterns that will lead to higher level understanding. Choose too many, and not only will you be unable to afford your experiment, you may miss the patterns altogether as your experiment overflows with random abundance.
Sometimes researchers want to compare dissimilar sites.
Comparing Data from Different Sites or Strata
Comparing absolute water content numbers can give confusing results. Both measurements are volumetric water content, but 35% here vs. 15% there actually tells us very little. Was the site in sand or clay, or something in between? If conditions at the two sites are virtually identical, the comparison may make some sense. But often, researchers want to compare dissimilar sites.
Figure 2. Changes in VWC with depth (convention: negative values indicate depths below soil surface) for the same time period at Site 1.
Water potential measurements determined by converting absolute volumetric water content to soil water potential using a moisture characteristic curve specific to each soil type can be used to compare results across sites. Comparing relative values—quantities of water used in centimeters for example—can also be both useful and valid.
Figure 3 below illustrates an experiment we performed in a dryland field where water content measurements were made over a growing season at 30, 60, 90, 120, and 150 cm below a wheat crop. The graph of soil moisture data shows how water is taken up from successively deeper layers. By subtracting one profile from another and summing over the layers where change occurs (for instance, in Figure 2 above, subtract the far left line from the far right line to see how much water was used from May 10th to August 21st), you can determine the amount of water used by the plants over a particular period. If similar data were taken at different sites or in different strata, these relative values, in terms of quantified water use, could form the basis of solid comparison studies.
Figure 3. Soil water content in winter wheat measured at 30 cm increments
Read more about accurate soil moisture: Can you sample the profile without a profile probe? Find out.