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Evaluating Reflected GPS Signal as a Potential Tool for Cotton Irrigation Scheduling

Xin Qiao, Ahmad Khalilian, Jose O. Payero, Joe Mari Maja, Charles V. Privette, Young J. Han
2016 Advances in Remote Sensing  
Accurate soil moisture content measurements are vital to precision irrigation management. Remote sensing using the microwave spectrum (such as GPS signals) has been used for measuring large area soil moisture contents. In our previous work, we estimated surface soil moisture contents for bare soil using a GPS Delay Mapping Receiver (DMR) developed by NASA. However, the effect of vegetation was not considered in these studies. Hence the objectives of this study were to: 1) investigate the
more » ... estigate the feasibility of using DMR to determine soil moisture content in cotton production fields; 2) evaluate the attenuation effect of vegetation (cotton) on reflected GPS signal. Field experiments were conducted during the 2013 and 2014 growing seasons in South Carolina. GPS antennas were mounted at three heights (1.6, 2.7, and 4.2 m) over cotton fields to measure reflected GPS signals (DMR readings). DMR readings, soil core samples, and plant measurements were collected about once a week and attenuation effect of plant canopy was calculated. Results showed that DMR was able to detect soil moisture changes within one week after precipitation events that were larger than 25 mm per day. However, the DMR readings were poorly correlated with soil volumetric water content during dry periods. Attenuation effect of plant canopy was not significant. For irrigation purpose, the results suggested that the sensitivity of reflected GPS signals to soil moisture changes needed to be further studied before this technology could be utilized for irrigation scheduling in cotton production. Refinement of this technology will expand the use of advanced remote sensing technology for site-specific and timely irrigation scheduling. This would eliminate the need to install moisture sensors in production fields, which can interfere with farming operations and increase production costs.
doi:10.4236/ars.2016.53013 fatcat:jvqvkmfvrfbbznsqfzf2wap3jm