Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/8/2005
Publication Date: 9/2/2005
Citation: Kaleita, A.L., Heitman, J.L., Logsdon, S.D. 2005. Field Calibration of the Theta Probe for Des Moines Lobe Soils. Applied Engineering in Agriculture. 21(5):865-870. Interpretive Summary: Knowing soil water content is important for undertanding the water cycle (rain, infiltration, runoff, evaporation, and crop water use). Remote sensing is used as a nondestructive way to examine soil water over large areas. The ThetaProbe is a device used to measure soil water content near the soil surface to compare with remotely sensed data. This study showed that temperature influenced the water content readings of ThetaProbe in the laboratory, but many other factors affected field water content measurements in the field. This study also showed that 20 ThetaProbe measurements were enough to calibrate for water content in the field. This information is useful for scientists who need to verify remote sensing measurements, and for regulators who need to know the accuracy of remotely sensed soil water data.
Technical Abstract: Knowledge of soil moisture is needed to understand crop water use, hydrology, and microclimate. A reliable, rapid technique is needed, and recently an impedance soil moisture probe (ThetaProbe) has gained interest by the research community. The purpose of this study is to calibrate the probe for soils of Central Iowa through field sampling, determine the number of samples needed for calibration, and determine the effect of temperature on calibration. Field calibration was based on ThetaProbe measurements on Des Moines lobe soils combined with gravimetric sampling and soil temperature determination. A laboratory calibration study was conducted on similar soils across a range of water contents and temperatures. Although there was some scatter, the field calibration was adequate for Iowa soils, with R2=0.79. Inclusion of temperature improved calibration slightly to R2=0.80. Including a temperature term was slightly more helpful for the controlled laboratory calibration, where the R2 increased from 0.85 to 0.87. To determine the appropriate number of samples needed for the field calibration, regression equations were determined from sample numbers ranging from 2 to 87, and the standard error was determined for each. Based on the standard error analysis, 20 samples was an adequate number, with no further improvement for larger data sets.