Developing Internet-of-Things soil moisture sensor networks for improving irrigation management in turfgrass - Aksland, Ian Brazil, author; Ham, Jay, advisor; Khosla, Raj, committee member; Qian, Yaling, committee member (Colorado State University. Libraries, 2025)
The importance of efficient irrigation in turfgrass management is underscored by substantial water usage in urban landscapes. In many western U.S. cities, over 50% of the total annual residential water use is allocated to turfgrass and landscape irrigation. Unfortunately, 30 to 60% of this urban irrigation water is wasted due to improper irrigation scheduling. This research focuses on the development and testing of innovative Internet-of-Things (IoT)-based soil moisture sensor networks designed to help optimize irrigation management in turfgrass. Golf course fairways served as a test bed for the research. A second phase of the research focused on how spatial variability in soil type and other landscape properties might impact soil sensor sampling plans, including the number of sensors and their installation locations. The overarching goal was to explore technologies that could promote more widespread use of soil sensors in irrigation decision-making to control golf courses and other turf areas like parks, green spaces, and residential lawns. The first phase of the project involved the design and calibration of custom-made capacitive soil moisture sensors, termed DP7T, which measure both soil moisture and temperature. A custom IoT cellular datalogger and innovative below-ground housing were also developed to read the sensors and transmit the information to the cloud via a cellular modem. Detailed laboratory calibrations were performed in various soil types using temperature-controlled chambers. After calibration, the systems were field-tested on three golf courses. Calibration results highlighted the importance of including temperature corrections, and necessity to include a built-in temperature transducer in each soil sensor. After temperature correction, excellent soil-specific linear calibrations were obtained on the log transform of volumetric water content vs sensor millivolt output, but soil specific calibrations were required. Extensive field tests validated the reliability of both the sensors and IoT dataloggers under field conditions. Cellular IoT connectivity facilitated real-time data transmission and analysis to online user dashboards, providing real-time information for improved irrigation management. However, results indicated significant micro and macro-scale spatial variation in sensor output when three measurement stations were deployed along fairways at each course. The large variation in soil moisture on a fairway suggests that this degree of spatial variation will confound the use of proximal soil sensors as a tool for irrigation management in these systems. To better understand how spatial variability in soils and landscape features affected sensor readings, spatial soil variation along the fairways was mapped using electromagnetic induction (EM38). The electromagnetic EM38 data showed a positive relationship with soil moisture content across all three golf courses, and literature has pointed to a strong correlation between topography and soil variability. More research is needed to fully understand how to successfully merge EM38 mapping layers and live soil moisture data to precisely recommend which sprinklers need adjustment for optimal irrigation, but this project suggests a model for further studies. The integration of low-cost sensors with IoT systems in this study demonstrated the potential of this technology. However, more research is needed on how proximal soil sensors should be deployed to characterize spatial variability in soil moisture across the landscape effectively. This will likely involve optimizing the number and deployment locations of soil sensors to capture the most information with the fewest sensors and at the lowest cost, while still meeting the day-to-day needs of turfgrass water managers.
Keywords: IoT; soil moisture; turfgrass; irrigation management; golf; soil sensors