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 advanced 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 the 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.

Highlights

  • Irrigated agriculture, a major contributor to the United States (U.S.) economy, plays a vital role in supplying the demand for food, feed, and fiber

  • The TDR315 (Acclima Inc., Meridian, ID, USA) is a recently commercialized sensor for agricultural applications [18]. This sensor operates on principles of Time Domain Reflectometry (TDR) that estimates the soil apparent permittivity (Ka ) at relatively higher frequencies (3.5 GHz), which are less sensitive to bulk electricity conductivity (EC) compared to lower frequency electromagnetic techniques [22]

  • Results of this study reveal that the Rosetta model is capable of accurately estimating soil moisture thresholds even with minimal input data

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Summary

Introduction

A major contributor to the United States (U.S.) economy, plays a vital role in supplying the demand for food, feed, and fiber. Sustaining high levels of food production through irrigated agriculture requires large amounts of water. Irrigation water sources, are usually limited in amount and are subject to increasing competition. More variability in precipitation patterns is expected due to climate change, which may threaten the availability of irrigation water supplies [3,4]. These challenges create the need to Sensors 2018, 18, 3786; doi:10.3390/s18113786 www.mdpi.com/journal/sensors

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