Examining Multiple Techniques to Interpolate Discrete Soil Moisture Measurements using a Large-Scale Lysimeter Facility

Soil moisture is a crucial component for understanding the agricultural soil water budget. In situ, soil moisture measurements are generally taken using soil moisture probes inserted at discrete depths within the profile. The characterization of the total moisture content found within the soil water profile for the agricultural water budget is generally determined through linear interpolations. This research used a large-scale lysimeter facility to evaluate the accuracy to which a linear interpolation can characterize a soil water profile. Results identified that a linear interpolation can describe the profile with normalized root mean square errors of 4.38% and 4.5% for silt loam and sandy loam soils, respectively, between actual and predicted daily soil water storage. Other interpolation methods (e.g., soil weighted average, inverse distance weighting, geophysical techniques, and cubic splines) were then employed to determine if the estimations of water budget estimates could be improved. A geophysical weighting technique showed the most promising improvement for estimation of the soil water profile for the sandy loam soils, while a linear interpolation remained the best method for the silt loam soils. Findings suggest that soil texture analysis is beneficial in determining the type of interpolation required.