Canopy temperature based system effectively schedules and controls center pivot irrigation of cotton

Cotton is a perennial plant with an indeterminate growth pattern that is typically produced like an annual, but requires proper management to effectively produce high yields and good fiber quality in a thermally limited environment like the northern Texas High Plains. In 2007 and 2008, we investigated the effect of irrigation scheduling/control method and amount on cotton (Gossypium hirsutum L.) yield and water use efficiency. Methods were automatic irrigation scheduling and control of a center pivot system, and manually scheduled irrigation to replenish soil-water to field capacity. Cotton was irrigated with LEPA (low energy, precision application) drag socks in furrow dikes; three blocks were irrigated manually and three were irrigated automatically. Six replicates of the manual and automatic irrigation treatments were included in the randomized block design. Manual irrigations were based on the weekly replenishment of soil-water to field capacity in the top 1.5m of the soil profile and included a fully irrigated treatment (I100), and treatments receiving 67% (I67) and 33% (I33) of the I100 amount, plus a non-irrigated treatment (I0). Automatic irrigations were triggered using a time temperature threshold (TTT) algorithm, which was designated as the I100 treatment, and treatments receiving 67%, 33%, and 0% of that amount (I67, I33 and I0, respectively). In 2007, overall mean lint yields (102.3 and 101.6gm-2, manual and automatic, respectively) were not significantly different. Similarly, yields were not significantly different across automatic and manual treatments in the same treatment level, with the exception of the I67 treatment where the manual treatment yields were 11% greater. In 2008, the mean yields were 70% less than those in 2007 for both methods of irrigation (30.3 and 30.9gm-2, manual and automatic, respectively) due to harsh climatic conditions at emergence and heavy rainfall and cooler temperatures in the month of August. Yields from the automatically irrigated plots in the I100 and I67 treatments, however, were significantly greater than yields from the corresponding manually irrigated plots; though there was no significant difference between yields in the drier treatments (I33 and I0) plots. These results indicate that the TTT algorithm is a promising method for auto-irrigation scheduling of short season cotton in an arid region. However, further studies are essential to demonstrate consistent positive outcomes.Automatic irrigation scheduling Cotton Time temperature threshold

A Reevaluation of Time Domain Reflectometry Propagation Time Determination in Soils

Time domain reflectometry (TDR) is an established method for the determination of apparent dielectric permittivity and water content in soils. Using current waveform interpretation procedures, signal attenuation and variation in dielectric media properties along the transmission line can significantly increase sampling error in estimating the time, t2, at which the pulse arrives at the end of the probe. Additionally, manual adjustment of waveform analysis parameters is frequently required in current software to accommodate changes in media properties when processing large time series of TDR measurements. Our objectives were to reevaluate conventional propagation time analysis and difficulties with these methods, introduce the AWIGF (adaptive waveform interpretation with Gaussian filtering) algorithm that circumvents these problems, and compare interpretation methods using waveforms obtained with different TDR instruments and under widely varying media properties. The AWIGF algorithm filters signal noise using Gaussian kernels with an adaptively estimated standard deviation based on the maximum gradient of the reflection at the termination of the probe. Two fitted parameters are required to scale the smoothing level for a given step pulse generator. Additionally, the maximum second derivative is used to evaluate t2. The AWIGF‐determined t2 was compared with TACQ, a standard waveform interpretation algorithm. The strategies of AWIGF permitted the determination of t2 without parameter adjustment when the loss characteristics of the medium changed, such as with an increase in soil water content and bulk electrical conductivity. Using the new method, the sampling error of t2 was <0.06 ns across a wide range of medium properties and less than or equal to that obtained with TACQ. In strongly attenuated waveforms, the water content sampling error determined with AWIGF was 0.005 m3 m−3 compared with 0.038 m3 m−3 obtained using TACQ

Using radiation thermography and thermometry to evaluate crop water stress in soybean and cotton

The use of digital infrared thermography and thermometry to investigate early crop water stress offers a producer improved management tools to avoid yield declines or to deal with variability in crop water status. This study used canopy temperature data to investigate whether an empirical crop water stress index could be used to monitor spatial and temporal crop water stress. Different irrigation treatment amounts (100%, 67%, 33%, and 0% of full replenishment of soil water to field capacity to a depth of 1.5 m) were applied by a center pivot system to soybean (Glycine max L.) in 2004 and 2005, and to cotton (Gossypium hirsutum L.) in 2007 and 2008. Canopy temperature data from infrared thermography were used to benchmark the relationship between an empirical crop water stress index (CWSIe) and leaf water potential ([Psi]L) across a block of eight treatment plots (of two replications). There was a significant negative linear correlation between midday [Psi]L measurements and the CWSIe after soil water differences due to irrigation treatments were well established and during the absence of heavy rainfall. Average seasonal CWSIe values calculated for each plot from temperature measurements made by infrared thermometer thermocouples mounted on a center pivot lateral were inversely related to crop water use with r2 values >0.89 and 0.55 for soybean and cotton, respectively. There was also a significant inverse relationship between the CWSIe and soybean yields in 2004 (r2 = 0.88) and 2005 (r2 = 0.83), and cotton in 2007 (r2 = 0.78). The correlations were not significant in 2008 for cotton. Contour plots of the CWSIe may be used as maps to indicate the spatial variability of within-field crop water stress. These maps may be useful for irrigation scheduling or identifying areas within a field where water stress may impact crop water use and yield.Infrared thermometry Infrared thermography Empirical crop water stress index Water use Cotton yields Soybean yields

Patch scale turbulence over dryland and irrigated surfaces in a semi-arid landscape under advective conditions during BEAREX08

Quantifying turbulent fluxes of heat and water vapor over heterogeneous surfaces presents unique challenges. For example, in many arid and semi-arid regions, parcels of irrigated cropland are juxtaposed with hot, dry surfaces. Contrasting surface conditions can result in the advection of warm dry air over an irrigated crop surface where it increases the water vapor deficit and, thereby, atmospheric demand. If sufficient water is available, this can significantly enhance evaporative water loss from the irrigated field. The scale and frequency of turbulent eddies over an irrigated surface during periods of strong advection is not fully understood. High frequency (20 Hz) data were acquired over irrigated cotton, wheat stubble, and rangeland fields during the 2008 growing season as part of the Bushland Evapotranspiration and Agricultural Remote Sensing Experiment (BEAREX08). Spectral analysis of momentum and scalar quantities including heat and water vapor revealed low frequency features in the turbulence structure due to the penetration of the surface boundary layer by large-scale eddies during periods of unusually strong advection. Wavelet analysis was applied to assess specific events contributing to the spatial and temporal structure of turbulent flux eddies. The analysis showed that low frequency contributions were linked to both local and regional scale advective processes. These results clearly point to a need to better understand surface energy balance exchange for heterogeneous surfaces in arid and semi-arid regions under conditions of strong local and regional advection