Advancements in dielectric soil moisture sensor Calibration: A comprehensive review of methods and techniques

Authors: MANE, SIDDHESH - Michigan State University; DAS, NARENDRS - Michigan State University; SINGH, GURJEET - Michigan State University; Cosh, Michael; DONG, YOUNSUK - Michigan State University

Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/1/2024
Publication Date: 3/1/2024
Citation: Mane, S., Das, N., Singh, G., Cosh, M.H., Dong, Y. 2024. Advancements in dielectric soil moisture sensor Calibration: A comprehensive review of methods and techniques. Computers and Electronics in Agriculture. 218. Article e 108686. https://doi.org/10.1016/j.compag.2024.108686.
DOI: https://doi.org/10.1016/j.compag.2024.108686

Interpretive Summary: Soil moisture sensing via in situ sensors is an important aspect of the land surface, because of the role that soil moisture plays in the water, energy, and carbon cycles. There are many different manufacturers of these sensors which leads to complications for interpretation and harmonization. A review of the different sensor technologies is necessary to understand the breadth and depth of the technology and how the sensor designs can influence the interpretation of their outputs. This work will impact the ability of modelers, action agencies, and scientists to interpret soil moisture data from in situ networks for a variety of applications.

Technical Abstract: Soil moisture (also referred as soil water content) is a vital geophysical state variable in various fields, such as agriculture, hydrology, meteorology, and remote sensing calibration/validation. Thus, accurate measurement of soil moisture is essential to ensure better modeling and decision-making. There are many ways to measure soil moisture, though the gravimetric method of soil moisture measurement is the most accurate, however, it is not suitable for real-time or large-scale field studies due to labor- and time-intensive procedures. In other words, the gravimetric method-based soil moisture measurements are not very feasible for hydrological or agricultural applications where a large number of in-situ observations are needed frequently as well as for validation of the remote sensing-based products that require sampling in a narrow time window during satellite passes. Hence, alternative modern methods like electronic sensors that measure soil moisture instantly are necessary for such applications. Since soil moisture sensors usually operate on the principle of dielectric characterization of the soil and water and use conversion relationships to provide soil moisture, these sensors require appropriate calibration for precise measurements. Although various procedures for calibrating dielectric soil moisture sensors are available in the scientific literature, factors affecting calibration, the technical complexity of calibration, and lack of confidence in their effectiveness limits their use in field studies. In this context, a review of soil moisture sensor calibration protocols has been conducted with the aim of examining the effectiveness and limitations of various calibration methods and approaches for dielectric constant-based soil moisture sensors. The importance of selecting an appropriate calibration method based on the sensor type, soil type, and environmental conditions is highlighted in this review. We also examine various calibration methods, including traditional equations based on linear or polynomial regression and advanced methods such as the nonlinear approach (i.e., artificial neural network). The need for regular calibration and maintenance of soil moisture sensors to ensure accurate and reliable data is also emphasized. The review concludes by providing recommendations for selecting the appropriate calibration method/approach for dielectric soil moisture sensors to achieve the required accuracy and future directions. Overall, this review provides valuable insights for researchers and practitioners in the field of dielectric sensor-based soil moisture monitoring and management.