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Development of an adaptive irrigation system to optimize turfgrass irrigation using reclaimed water
Weiss, James Max
Weiss, James Max
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2020
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Residential lawns, parks, and golf courses all have one thing in common: turfgrass. In the United States alone, turfgrass covers an estimated 200,000 km2 of land. Water requirements are measured as evapotranspiration (ET) and crop coefficient (Kc), which vary depending on local climate and turfgrass species. Typically, measured ET is used as a minimum value for irrigation, thus excess water beyond plant uptake is applied. Using excess water for turfgrass irrigation depletes potable water sources that are also needed for human consumption. To limit water consumption, in-ground sensors that measure real time volume water content (VWC) of a bulk soil matrix have been used. Along with limiting water use with in-ground sensors, turfgrass can be irrigated with non-potable water sources with elevated levels of salinity hereafter termed ‘saline water’. Reclaimed water, or treated wastewater effluent, is one non-potable source that may be used for irrigation yet may have elevated salinity. Irrigation uses a process called leaching to prevent buildup of salts in the turfgrass rootzone, but also requires more water to flush salts out. To optimize turfgrass irrigation with brackish water, we developed and tested a wireless sensor network (WSN), in this case as part of a smart sensor irrigation system (SSIS), that utilized a control algorithm for irrigation based on both VWC and electrical conductivity (EC) measurements from in-ground sensors during the growing seasons in 2019 and 2020. The SSIS included three key components: turfgrass sensor nodes (powered via solar battery), a computer base station, and a valve controller. The WSN for the SSIS was developed at Colorado School of Mines in Golden, CO by first testing communication amongst the three components, followed by bucket testing where sensors were submerged in sand and known quantities of water were applied to verify proper readings. After the SSIS worked in bucket tests, it was deployed at the field site located at New Mexico State University’s Turfgrass Research Center in Las Cruces, NM, on plots with perennial ryegrass (Lolium perenne L.). Preliminary data showed 57.4% savings in potable water, with many caveats. Setbacks occurred when the software in SSIS was found to not be robust for any extended period of time, along with the turfgrass plots hardware drawing more energy than could be supplied each day. Additional software development was also needed before retesting. While new software was being developed, another study was implemented to mimic SSIS using manually controlled irrigation. When comparing smart saline irrigation to historic ET-based potable irrigation, results indicated a reduction in water use by 31% despite temperatures averaging 34 °C during the study. Turfgrass quality remained comparable and healthy across all plots. These findings show potential of sensor-based turfgrass irrigation to reuse and conserve water resources while maintaining comparable turfgrass health when compared to ET-based irrigation with potable water.
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