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Utilizing Space-based Technology for Cotton Irrigation Scheduling
1X. Qiao, 1A. Khalilian, 2J. O. Payero, 1J. M. Maja, 1C. V. Privette, 1Y. J. Han
1. Clemson University
2. Clemson Univesity

Accurate soil moisture content measurements are vital to precision irrigation management. Electromagnetic sensors such as capacitance and time domain reflectometry have been widely used for measuring soil moisture content for decades. However, to estimate average soil moisture content over a large area, a number of ground-based in-situ sensors would need to be installed, which would be expensive and labor intensive. 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 feasibility of using DMR to determine soil moisture content in cotton production fields; 2) evaluate the attenuation effect of vegetation (cotton) on GPS reflected 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 GPS reflected 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 GPS reflected signals to soil moisture changes needs to be further studied before this technology can be utilized for irrigation scheduling in cotton production.

Keyword: Remote sensing, GPS, Soil volumetric moisture content, Irrigation