A field-portable acoustic sensing device to measure soil moisture

Srikanth Gorthi, Somsubhra Chakraborty, Bin Li, David C. Weindorf

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

For the last couple of decades, the idea of soil water measurement has gained widespread importance due to the spiraling crisis of global water resources. While several methods are being commonly used for soil water measurement, most of them do not satisfy all the essential requirements for water monitoring under field conditions including rapid on-site measurement and cost-effectiveness. This study was conducted to evaluate the efficacy of a novel field-portable acoustic sensing device on soil moisture measurements. The conventional Brutsaert's model was followed involving the continuous wave zero-crossing method to measure the acoustic velocity and considering the phase shift due to the amplifier and ambient temperature. The gravimetric moisture content (GMC) was calibrated using the acoustic velocity for 70 samples representing seven textural classes and variable soil organic carbon (OC). Results indicated the monotonous reduction of the acoustic velocities of p-wave with increasing GMC. In general, soils with higher clay content reflected higher acoustic velocities. However, sandy soils with high OC content were less prone to compaction and produced comparatively higher acoustic velocities than soils with higher clay content. A linear mixed effect (LME) model indicated that one unit increase in the acoustic velocity resulted in a 0.086% decrease in GMC. Moreover, LME parameters-based K-means clustering further highlighted the influence of soil texture for controlling the acoustic velocity. The use of LME justified the use of GMC as the target instead of the degree of saturation. Linear and quadratic models fitted for individual LME-based clusters produced R2 values ranging from 0.80 to 0.88 and 0.82–0.88, respectively. Moreover, combined linear (R2 = 0.61; RMSE = 52.12 m/s) and quadratic (R2 = 0.64; RMSE = 50.48 m/s) models incorporating all 70 samples via bootstrapping produced comparable accuracies for GMC prediction, but yielded inferior results than the individual cluster-based models. In conclusion, the acoustic sensing device showed its potential for soil water content monitoring, leading to efficient irrigation planning. More research is warranted for texture-wise calibration development incorporating a wide assortment of soil types and on-site evaluation.

Original languageEnglish
Article number105517
JournalComputers and Electronics in Agriculture
Volume174
DOIs
StatePublished - Jul 2020

Keywords

  • Acoustic velocity
  • Gravimetric moisture content
  • Linear mixed effect model
  • Soil texture

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