DEVELOPING EFFECTIVE GROUND AND SPACE-BASED SOIL MOISTURE SENSING TECHNIQUES FOR IRRIGATING COTTON IN COASTAL PLAIN SOILS

Irrigation scheduling based on soil moisture sensor readings has gained popularity in the past few decades since it can enhance crop yield while saving water. Such method is limited since the representativeness of an individual soil moisture sensor measurement is questionable in a large field with variable soil type and texture. The optimum location of soil moisture sensors needs to be determined within such a production field for effective sensor-based irrigation scheduling. Therefore, the first object of this study was to investigate the optimum sensor location and the number of moisture sensors required for irrigating cotton in coastal plain soils. Replicated tests were conducted during 2012, 2013, and 2014 growing seasons in a cotton field located at the Edisto Research and Education Center of Clemson University, on a typical coastal plain soil. The test field was divided into different management zones based on soil electrical conductivity (EC) measurements. Soil moisture sensors including AquaSpy, Sentek EasyAg-50, Decagon EC-5, Watermark 200SS, and 503 DR Hydroprobe neutron probe access tubes were installed side by side in plots of each management zone. Irrigation treatments were based on sensor readings from various management zones. Results showed that irrigation based on sensor readings from higher electrical conductivity zones, can stabilize or even enhance yield while increasing water use efficiency (WUE) significantly. The second objective of this study was to evaluate the performance of soil moisture sensors mentioned above to determine the most accurate and affordable sensor technology for irrigation scheduling. Season long soil moisture readings of AquaSpy, Sentek EasyAg-50, Decagon EC-5, and Watermark 200SS sensors were collected and compared to neutron probe readings. The results showed that Sentek EasyAg-50 sensor performed the best among tested sensors compared to neutron probe readings with coefficient of determination, R2 = 0.847 and root mean square error, RMSE= 4.2% for soil profiles up to 50 cm. The performance of Decagon EC-5 sensor was acceptable with R2 of 0.6 to 0.7 and RMSE ranged from 4.9% to 6.7% during the three growing seasons. Further field and lab calibration of Decagon EC-5, reduced RMSE from 4.4% to 3.3% at topsoil (10-30 cm). Compared to Sentek EasyAg and Decagon EC-5 sensors, AquaSpy and Watermark 200SS sensors performances in measuring soil moisture contents, were not satisfactory, as indicated by low R2 of less than 0.45 and high RMSE of 9.5% to 14%. The results of this study suggested that in a field with variable soil type, it would be beneficial to install moisture sensors in management zones with higher EC readings (heavier soil textures) to obtain maximum yield and WUE. The results also indicated that, although the Sentek EasyAg-50 sensor had the highest accuracy among the sensor types tested, Decagon sensor offered more promise for irrigation scheduling than the rest of the sensors tested, since it offered good accuracy and is affordable

PARAMETERIZATION OF FAO AQUACROP MODEL FOR IRRIGATED COTTON IN THE HUMID SOUTHEAST U.S.A

Cotton (Gossypium hirsutum L) is cultivated in many countries under both rainfed and irrigated conditions. In the U.S.A., cotton is grown in 17 states across a vast region known as the Cotton Belt. In the Cotton Belt as with many parts of the world, irrigated cotton is a considerable water user, but for good reasons. Irrigation can boost yield as well as stabilize yield and quality by ensuring adequate soil water during the entire growing season or at least during critical growth stages in areas where water resources are limited. From 2002 to 2007, irrigated acreage in the western states declined significantly, while in the southeastern states, irrigated acreage increased by 70%. Recent drought periods (1998-2002, 2007, & 2011) in the southeastern U.S.A. and trans-boundary water conflicts between neighboring states have elevated the importance of water resources conservation. Competition for limited water resources has become a critical issue in some parts of the southeastern states. For example, in some parts of Georgia, limits are already being placed on agricultural irrigation. In this environment, the challenge for the coming decades will be increasing food and fiber production with less water. This can be partially achieved by increasing crop water use efficiency (WUE) - the amount of yield produced per unit water used. Increasing crop water use efficiency (WUE) and use of more drought tolerance cotton varieties would help to conserve water. Water productivity (WP) provides another way to evaluate efficiency of crop water use. It is defined in this study as \u27the aboveground dry matter (kg) produced per unit land area (ha) per unit of water transpired (m)\u27. However, there are no published values for WP for cotton in the humid southeast. The first objective of this study was to determine WUE and WP of cotton in this area. Irrigation experiments were conducted in 2009 and 2010 under field environments and in 2011 under a controlled environment utilizing a rainout shelter at the Edisto Research and Education Center, near Blackville, SC. WUE ranged from 0.39 kg seed cotton/m3 water applied to 0.87 seed cotton/m3 water applied (ie., irrigation plus rainfall). WP values were 12.9, 12, and 12.7 g/m2 in year 2009, 2010, and 2011, respectively. Field experiments could be lengthy and expensive. Crop models have been used extensively to provide an alternative way of pre-evaluating field experiments. Recently, the Food and Agriculture Organization (FAO) of the United Nations developed the AquaCrop, a yield response to water stress model. AquaCrop has been recently tested for various crops under various climates, except in the humid regions. The second objective of this study was to parameterize and validate the AquaCrop model for cotton under humid climate of the southeast U.S.A. The model was parameterized and validated using quality local datasets as collected under Objective 1 above. Few parameters in Aquacrop were adjusted, such as canopy growth coefficient (CGC), canopy decline coefficient (CDC), water depletion thresholds (p factors), water productivity (WP), and reference harvest index (HIo) to produce field results from the detailed open-field and shelter studies in 2009 and 2011. Model validation involved using the parameterized model to simulate other field experiments in 2010 and comparing results. Results correlated well with simulated values with high correlation coefficients. For example, simulated values for 100% irrigation treatment in 2010 at E5 field in terms of canopy cover (measured by digital camera), soil water content, and cumulative ET were correlated with measured values with R2 of 0.8394, 0.7877, and 0.9918, respectively. A tested AquaCrop provides the necessary tool to study irrigation optimization under varying timing and intensity of drought stress as it may occur during the growing season and due to climate change and variability

Electric Character of Strange Stars

Using the Thomas-Fermi model, we investigated the electric characteristics of a static non-magnetized strange star without crust in this paper. The exact solutions of electron number density and electric field above the quark surface are obtained. These results are useful if we are concerned about physical processes near the quark matter surfaces of strange stars.Comment: 4 pages, 2 figures, LaTeX, Published in Chinese Physics Letters, Vol.16, p.77