Comparison of spray, LEPA, and SDI for cotton and grain sorghum in the Texas Panhandle

Presented at the Central Plains irrigation conference on February 16-17, 2005 in Sterling, Colorado.Includes bibliographical references.Crop responses to MESA (mid-elevation spray application), LESA (low-elevation spray applicator), LEPA, (low energy precision application), and SDI (subsurface drip irrigation) were compared for full and deficit irrigation rates in the Texas Panhandle. Crops included three seasons of grain sorghum and one season of cotton; crop responses consisted of economic yield, seasonal water use, and water use efficiency (WUE). Irrigation rates were I0, I25, I50, I75, and I100 (where the subscript denotes the percentage of full irrigation, and I0 is dryland). Yield and WUE was greatest for SDI and least for spray at the I25 and I50 rates, and greatest for spray at the I100 rate. Yield and WUE trends were not consistent at the I75 rate. Seasonal water use was not significantly different in most cases between irrigation methods within a given irrigation rate. For cotton, the irrigation method did not influence boll maturity rates, but SDI resulted in higher fiber quality at the I25, I50, and I100 rates

Drip and evaporation

Presented at the Central Plains irrigation conference on February 16-17, 2005 in Sterling, Colorado.Includes bibliographical references.Loss of water from the soil profile through evaporation from the soil surface is an important contributor to inefficiency in irrigated crop production. Residue management systems may reduce this evaporative loss, but cannot be used in all cropping systems. Choice of the irrigation system and its management also can reduce evaporative loss. In particular, subsurface drip irrigation limits soil surface wetting and can lead to an overall reduction in evapotranspiration (crop water use) of as much as 10%. The example presented shows that most of the water savings occur early in the season when crop cover is not yet complete. Because evaporation from the soil surface has a cooling effect on the soil in the root zone, irrigation methods that limit evaporation will result in smaller fluctuations in soil temperature and warmer soil temperatures overall. For some crops such as cotton, this has beneficial effects that include earlier root growth, better plant development and larger yields

Cotton production with SDI, LEPA, and spray irrigation in a thermally-limited climate

Producers in the Northern Texas Panhandle and Southwestern Kansas are considering cotton as an alternative crop to corn because cotton has a similar profit potential for about one half the irrigation requirement. However, limited growing degree days pose some risk for cotton production. We hypothesized that cotton under subsurface drip irrigation (SDI) would undergo less evaporative cooling following an irrigation event compared with low energy precision applicators (LEPA) or spray irrigation and, therefore, would increase growing degree day accumulation and lead to earlier maturation. Cotton maturity was more related to irrigation rate than irrigation method, with dryland and minimal irrigation rates reaching maturity earliest. However, fiber quality, as indicated by total discount, was usually better with SDI. Lint yield and water use efficiency were greatest with SDI at low irrigation rates in 2003, and lint yield and gross returns were greatest with SDI regardless of irrigation rate in 2004

COMPARISON OF SDI, LEPA, AND SPRAY IRRIGATION PERFORMANCE FOR GRAIN SORGHUM

Subsurface drip irrigation (SDI), low−energy precision application (LEPA), and spray irrigation can be very efficient by minimizing water losses, but relative performance may vary for different irrigation system capacities, soils, crops, and climates. A three−year study was conducted at Bushland, Texas, in the Southern High Plains to compare SDI, LEPA, and spray irrigation for grain sorghum on a slowly permeable Pullman clay loam soil. Performance measures were grain yield, seed mass, soil water depletion, seasonal water use, water use efficiency (WUE), and irrigation water use efficiency (IWUE). Each irrigation method was compared at five irrigation levels: 0%, 25%, 50%, 75%, and 100% of crop evapotranspiration. The irrigation levels simulated varying well capacities typically found in the region and dryland conditions. In all three years, SDI had greater yield, WUE, and IWUE than other irrigation methods at the 50% irrigation level and especially at the 25% level, whereas spray outperformed SDI and LEPA at the 75% and 100% levels. Differences in seed mass, soil water depletion, and seasonal water use were usually insignificant at the 25% and 50% levels and inconsistent at the 75% and 100% levels. Performance was most sensitive to irrigation level, then year, and then irrigation method, although relative rankings of performance for each irrigation method within an irrigation level were consistent across years. For this climate and soil, SDI offers the greatest potential yield, WUE, and IWUE for grain sorghum when irrigation capacities are very low

Proceedings of the 21st annual Central Plains irrigation conference, Colby Kansas, February 24-25, 2009

Presented at the 21st annual Central Plains irrigation conference on February 24-25, 2009 in Colby, Kansas.Includes bibliographical references.Crop production was compared under subsurface drip irrigation (SDI), low energy precision applicators (LEPA), low elevation spray applicators (LESA), and mid elevation spray applicators (MESA) at the USDA-Agricultural Research Service Conservation and Production Research Laboratory, Bushland, Tex., USA. Each irrigation method was compared at irrigation rates meeting 25, 50, 75, and 100% of full crop evapotranspiration (ETc). Crops included three seasons of grain sorghum, one season of soybean (planted following a cotton crop that was destroyed by hail), and four seasons of upland cotton. For grain sorghum, SDI followed by LEPA, MESA, and LESA resulted in greater grain yield, water use efficiency, and irrigation water use efficiency at the 25- and 50% irrigation rates, whereas MESA followed by LESA outperformed LEPA and SDI at the 75- and 100% irrigation rates. For soybean, the same trend was observed at the 25- and 50% irrigation rates, whereas SDI followed by MESA, LEPA, and LESA resulted in the best crop response at the 75% irrigation rate, and MESA followed by SDI, LESA, and LEPA resulted in the best crop response at the 100% irrigation rate. Cotton response was consistently best for SDI, followed by LEPA, and either MESA or LESA at all irrigation rates. Within each irrigation rate, few significant differences were observed among irrigation methods in total seasonal water use for all crops

WIRELESS SENSOR NETWORK EFFECTIVELY CONTROLS CENTER PIVOT IRRIGATION OF SORGHUM

Automatic irrigation scheduling has been demonstrated using wired sensors and sensor network systems with subsurface drip and moving irrigation systems. However, there are limited studies that report on crop yield and water use efficiency resulting from the use of wireless networks to automatically schedule and control irrigations. In this 2011 study, a multinode wireless sensor network (WSN) system was mounted onto a six-span center pivot equipped with a commercial variable rate irrigation (VRI) system. Data from the WSN was used to calculate an integrated crop water stress index (iCWSI) threshold for automatic irrigation scheduling of grain sorghum. Crop response to the automatic method was compared with manual irrigation scheduling using weekly direct soil water measurements. The WSN system was operational throughout 98% of the growing season, and the delivery rates for data packets from the different nodes ranged between 90% and 98%. Dry grain yields and WUE in the automatic and manual treatment plots were not significantly different from each other at any of the irrigation levels. Crop water use and WUE were highest in the I80% irrigation treatment level. Average seasonal integrated crop water stress indices were negatively correlated to irrigation treatment amounts in both the manual and automatic plots and correlated well to crop water use. These results demonstrate that it is feasible to use WSN systems for irrigation management on a field-scale level

Utility of thermal sharpening over Texas high plains irrigated agricultural fields

Irrigated crop production in the Texas high plains (THP) is dependent on water extracted from the Ogallala Aquifer, an area suffering from sever water shortage. Water management in this area is therefore highly important. Thermal satellite imagery at high temporal (~daily) and high spatial (~100 m) resolutions could provide important surface boundary conditions for vegetation stress and water use monitoring, mainly through energy balance models such as DisALEXI. At present, however, no satellite platform collects such high spatiotemporal resolution data. The objective of this study is to examine the utility of an image sharpening technique (TsHARP) for retrieving land surface temperature at high spatial resolution (down to 60 m) from moderate spatial resolution (1 km) imagery, which is typically available at higher (~daily) temporal frequency. A simulated sharpening experiment was applied to Landsat 7 imagery collected over the THP in September 2002 to examine its utility over both agricultural and natural vegetation cover. The Landsat thermal image was aggregated to 960 m resolution and then sharpened to its native resolution of 60 m and to various intermediate resolutions. The algorithm did not provide any measurable improvement in estimating high-resolution temperature distributions over natural land cover. In contrast, TsHARP was shown to retrieve high-resolution temperature information with good accuracy over much of the agricultural area within the scene. However, in recently irrigated fields, TsHARP could not reproduce the temperature patterns. Therefore we conclude that TsHARP is not an adequate substitute for 100-m-scale observations afforded by the current Landsat platforms. Should the thermal imager be removed from follow-on Landsat platforms, we will lose valuable capacity to monitor water use at the field scale, particularly in many agricultural regions where the typical field size is ~100 X 100 m. In this scenario, sharpened thermal imagery from instruments like MODIS or VIIRS would be the suboptimal alternative

Evaluation of a wireless infrared thermometer with a narrow field of view

Many agricultural studies rely on infrared sensors for remote measurement of surface temperatures for crop status monitoring and estimating sensible and latent heat fluxes. Historically, applications for these non-contact thermometers employed the use of hand-held or stationary industrial infrared thermometers (IRTs) wired to data loggers. Wireless sensors in agricultural applications are a practical alternative, but the availability of low cost wireless IRTs is limited. In this study, we designed prototype narrow (10◦) field of view wireless infrared sensor modules and evaluated the performance of the IRT sensor by comparing temperature readings of an object (Tobj) against a blackbody calibrator in a controlled temperature room at ambient temperatures of 15 ◦C, 25 ◦C, 35 ◦C, and 45 ◦C. Additional comparative readings were taken over plant and soil samples alongside a hand-held IRT and over an isothermal target in the outdoors next to a wired IRT. The average root mean square error (RMSE) and mean absolute error (MAE) between the collected IRT object temperature readings and the blackbody target ranged between 0.10 and 0.79 ◦C. The wireless IRT readings also compared well with the hand-held IRT and wired industrial IRT. Additional tests performed to investigate the influence of direct radiation on IRT measurements indicated that housing the sensor in white polyvinyl chloride provided ample shielding for the self-compensating circuitry of the IR detector. The relatively low cost of the wireless IRT modules and repeatable measurements against a blackbody calibrator and commercial IR thermometers demonstrated that these wireless prototypes have the potential to provide accurate surface radiometric temperature readings in outdoor applications. Further studies are needed to thoroughly test radio frequency communication and power consumption characteristics in an outdoor setting

Utility of thermal image sharpening for monitoring field-scale evapotranspiration over rainfed and irrigated agricultural regions

The utility of a thermal image sharpening algorithm (TsHARP) in providing fine resolution land surface temperature data to a Two-Source-Model for mapping evapotranspiration (ET) was examined over two agricultural regions in the U.S. One site is in a rainfed corn and soybean production region in central Iowa. The other lies within the Texas High Plains, an irrigated agricultural area. It is concluded that in the absence of fine (sub-field scale) resolution thermal data, TsHARP provides an important tool for monitoring ET over rainfed agricultural areas. In contrast, over irrigated regions, TsHARP applied to kilometer-resolution thermal imagery is unable to provide accurate fine resolution land surface temperature due to significant sub-pixel moisture variations that are not captured in the sharpening procedure. Consequently, reliable estimation of ET and crop stress requires thermal imagery acquired at high spatial resolution, resolving the dominant length-scales of moisture variability present within the landscape

A crop water stress index and time threshold for automatic irrigation scheduling of grain sorghum

Variations of the crop water stress index (CWSI) have been used to characterize plant water stress and schedule irrigations. Usually, this thermal-based stress index has been calculated from measurements taken once daily or over a short period of time, near solar noon or after and in cloud free conditions. A method of integrating the CWSI over a day was developed to avoid the noise that may occur if weather prevents a clear CWSI signal near solar noon. This CWSI and time threshold (CWSI-TT) was the accumulated time that the CWSI was greater than a threshold value (0.45); and it was compared with a time threshold (CWSI-TT) based on a well-watered crop. We investigated the effectiveness of the CWSI-TT to automatically control irrigation of short and long season grain sorghum hybrids (Sorghum bicolor (L.) Moench, NC+ 5C35 and Pioneer 84G62); and to examine crop response to deficit irrigation treatments (i.e. 80%, 55%, 30% and 0% of full replenishment of soil water depletion to 1.5-m depth). Results from automated irrigation scheduling were compared to those from manual irrigation based on weekly neutron probe readings. In 2009, results from the Automatic irrigation were mixed; biomass yields in the 55% and 0% treatments, dry grain yields in the 80% and 0% treatments, and WUE in the 80%, 55%, and 0% treatments were not significantly different from those in the corresponding Manual treatments. However, dry grain yields in the 55% and 30% treatments were significantly less than those in the Manual control plots. These differences were due mainly to soil water variability in the beginning of the growing season. This conclusion is reinforced by the fact that IWUE for dry grain yield was not significantly different for 30% and 55% treatments, and was significantly greater for Automatic control at 80%. In 2010, there were no significant differences in biomass, dry grain yield, WUE, or IWUE for irrigation control methods when compared across the same amount treatments. Similar results between irrigation methods for at least the highest irrigation rate (80% of soil water depletion) in 2009 and among all irrigation treatment amounts in 2010 indicate that the CWSI-TT method can be an effective trigger for automatically scheduling either full or deficit irrigations for grain sorghum in a semi-arid region