Skip to main content
ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Agroclimate and Natural Resources Research » Research » Publications at this Location » Publication #358544

Research Project: Towards Resilient Agricultural Systems to Enhance Water Availability, Quality, and Other Ecosystem Services under Changing Climate and Land Use

Location: Agroclimate and Natural Resources Research

Title: Performance assessment of five different soil moisture sensors under irrigated field conditions in Oklahoma

Author
item Datta, Sumon - Oklahoma State University
item Taghvaeian, Saleh - Oklahoma State University
item Ochsner, Tyson - Oklahoma State University
item Moriasi, Daniel
item Gowda, Prasanna
item Steiner, Jean

Submitted to: Sensors
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/2/2018
Publication Date: 11/5/2018
Citation: Datta, S., Taghvaeian, S., Ochsner, T.E., Moriasi, D.N., Gowda, P.H., Steiner, J.L. 2018. Performance assessment of five different soil moisture sensors under irrigated field conditions in Oklahoma. Sensors. 18(11): 1-17. https://doi:10.3390/s18113786.
DOI: https://doi.org/10.3390/s18113786

Interpretive Summary: Producers are increasingly using soil moisture sensors to manage irrigation scheduling. There are different types of commercially available soil moisture sensors, but electromagnetic sensors have been more widely used for irrigation scheduling due to their low cost, ease of installation, operation, and maintenance. However, performance of these sensors in soils with different levels of salinity and clay content is limited. Therefore, the performance of five different soil moisture sensors was evaluated for their accuracy in two irrigated cropping systems, one each in central and southwest Oklahoma with variable levels of soil salinity and clay content. Sensors evaluated included TDR315, CS655, GS1, SM100, and CropX. With factory settings, only the CS655, TDR315, and GS1 sensors measured soil moisture sufficiently accurate at the site with lower levels of salinity and clay, while none of them performed satisfactorily at the site with higher levels of salinity and clay. In addition, a wide range of accuracies was noted among soil moisture sensors and methods for determining soil moisture thresholds, thus making it difficult to utilize soil moisture sensors for irrigation scheduling applications. Therefore, we recommend that more studies be conducted under variable field conditions to evaluate the performance of the new sensors and to provide guidelines.

Technical Abstract: Meeting the ever-increasing global food, feed, and fiber demands while conserving the quantity and quality of limited agricultural water resources and maintaining the sustainability of irrigated agriculture requires optimizing irrigation management using smart technologies such as soil moisture sensors. In this study, the performance of five different soil moisture sensors was evaluated for their accuracy in two irrigated cropping systems one each in central and southwest Oklahoma with variable levels of soil salinity and clay content. With factory calibrations, three of the sensors had sufficient accuracies at the site with lower levels of salinity and clay, while none of them performed satisfactorily at the site with higher levels of salinity and clay. The study also investigated the performance of different approaches (laboratory, sensor-based, and the Rosetta model) to determine soil moisture thresholds required for irrigation scheduling, i.e. field capacity (FC) and wilting point (WP). The estimated FC and WP by Rosetta model were closest to the laboratory-measured data using undisturbed soil cores, regardless of the type and number of input parameters used in the Rosetta model. The sensor-based method of ranking the readings resulted in overestimation of FC and WP. Finally, soil moisture depletion, a critical parameter in effective irrigation scheduling, was calculated by combining sensor readings and FC estimates. Ranking-based FC resulted in overestimation of soil moisture depletion, even for accurate sensors at the site with lower levels of salinity and clay.