There have been many studies to estimate soil moisture, particularly as it relates to irrigation. However, due to the heterogeneity of soils and the variability of vegetation and, in some areas, topography, soil moisture can be variable over time and space, making it a challenge to estimate. Not surprisingly, many studies have shown that the variability in soil moisture increases with decreasing average moisture content and vice versa. Therefore, the drier the soil, the more variability, and this suggests that more sampling points are needed to characterize soil moisture under drier conditions. In addition, many studies have looked at soil moisture levels near the soil surface (~0 - 4 in), but when making an irrigation decision, it is important to estimate the soil moisture in the active rooting zone of the plant.
Soil moisture sensors have been documented to conserve water without reducing soybean yields by applying irrigation when the plant needs it and removing some of the guesswork from irrigation scheduling. In addition, in Mississippi, granular matrix sensors (GMS) are most commonly used to help schedule irrigation applications. However, questions remain on how many sets of sensors are needed for any given area. This project will help determine if the in-field variability is enough to warrant a higher density of sensors and a different irrigation schedule for different areas of a field.