Terry A. Howell

Effect of mulch, irrigation, and soil type on water use and yield of maize

Abstract Tillage practices that maintain crop residues on the soil surface help reduce evaporation of soil water, which can benefit high water use crops such as maize ( Zea mays L.). Management practices, climatic conditions, and soil type may affect how well a crop responds to surface residue. We conducted experiments with short season maize in 1994 and 1995 in Bushland, TX, USA, utilizing a rain shelter facility that has lysimeters containing monolithic cores of the Pullman (fine, mixed, thermic Torrertic Paleustolls), the Ulysses (fine-silty, mixed, mesic Aridic Haplustolls), and the Amarillo (fine-loamy, mixed, thermic Aridic Paleustalfs) soil series. In 1994, the treatments were a flat wheat ( Triticum aestivum L.) straw and coconut ( Cocus nucifera L.) fiber mulch of 4xa0Mgxa0ha −1 with infrequent irrigations totaling 25% and 75% of long-term average rainfall for the growing season (200xa0mm). The 1995 treatments were similar, but used a heavier mulch of 6.7xa0Mgxa0ha −1 and more frequent irrigations totaling 60% and 100% of long-term average rainfall. The mulch was applied at the 3-leaf growth stage. Mean potential grass reference evapotranspiration for the vegetative and reproductive growth stages in 1994 was 6.6 and 6.3xa0mmxa0day −1 , respectively, and in 1995 it was 6.8 and 7xa0mmxa0day −1 , respectively. The mulched and bare soil surface treatments used similar amounts of water in each year. In 1994, mulch did not affect yield, yield components, or leaf area index (LAI). No significant differences occurred in plant available water (PAW) between mulched and bare soil treatments from emergence through harvest. In 1995, mulch increased grain yield by 17%, aboveground biomass by 19%, and grain water use efficiency (WUE) by 14% compared with bare soil treatments. Mulched treatments also maintained significantly greater PAW compared with bare soil treatments until near anthesis and, after anthesis, LAI was significantly greater in the mulched treatments compared with the bare soil treatments. In 1995, mulch significantly increased grain yield and grain WUE of the maize crop in the Pullman soil, grain yield and biomass WUE of the crop in the Amarillo soil, and had no significant effect on the crop in the Ulysses soil compared with the bare soil treatments. The significant increase in water use efficiency in 1995 was the result of soil water being used for crop growth and yield rather than in evaporation of soil water. The more favorable soil water regime in 1995 compared with 1994 between the mulched and bare soil treatments was possibly due to the higher evaporative demand environment, the increase in mulch mass, and the increased irrigation frequency. This was especially important in soils where textural characteristics affected both rooting and soil water extraction by maize which limited its ability to tolerate water stress.

Remote Sensing Based Energy Balance Algorithms for Mapping ET: Current Status and Future Challenges

Evapotranspiration (ET) is an essential component of the water balance and a major consumptive use of irrigation water and precipitation on cropland. Remote sensing based agrometeorological models are presently most suited for estimating crop water use at both field and regional scales. Numerous ET models have been developed in the last three decades to make use of visible, near-infrared (NIR), shortwave infrared (SWIR), and most importantly, thermal data acquired by sensors on airborne and satellite platforms. In this article, a literature review is done to evaluate numerous remote sensing based algorithms for their ability to accurately estimate regional ET. The remote sensing based models generally have the potential to accurately estimate regional ET; however, there are numerous opportunities to further improve them. The spatial and temporal resolution of currently available remote sensing data from the existing set of earth-observing satellite platforms are not sufficient enough to be used in the estimation of spatially distributed ET for on-farm irrigation scheduling purposes, especially at the field scale (~10 to 200 ha). This will be constrained further if the thermal sensors on future Landsat satellites are abandoned. Research opportunities exist to improve the spatial and temporal resolution of ET by developing algorithms to increase the spatial resolution of surface temperature data derived from ASTER/MODIS thermal images using same/other-sensor high-resolution visible, NIR, and SWIR images.

Surface Energy Balance Based Evapotranspiration Mapping in the Texas High Plains

Agriculture on the Texas High Plains (THP) uses approximately 89% of groundwater withdrawals from the Ogallala Aquifer. Consequently, groundwater levels are declining faster than the recharge rate. Therefore, efficient agricultural water use is essential for economic viability and sustainability of the THP. Accurate regional evapotranspiration (ET) maps would provide valuable information on actual crop water use. In this study, METRIC (Mapping Evapotranspiration at High Resolution using Internalized Calibration), a remote sensing based ET algorithm, was evaluated for mapping ET in the THP. Two Landsat 5 Thematic Mapper images acquired on 27 June (DOY 178) and 29 July (DOY 210) 2005 were used for this purpose. The performance of the ET model was evaluated by comparing the predicted daily ET with values derived from soil moisture budget at four commercial agricultural fields. Daily ET estimates resulted with a prediction error of 12.7±8.1% (mean bias error ± root mean square error) on DOY 178 and -4.7±9.4% on DOY 210 when compared with ET derived from measured soil moisture through the soil water balance. These results are good considering the prevailing advective conditions in the THP. METRIC have the potential to be used for mapping regional ET in the THP region. However, more evaluation is needed under different agroclimatological conditions.

Agricultural Water Conservation- A Global Perspective

Summary Water for agriculture generally is adequate in humid regions, but water conservation often is needed in subhumid and semiarid regions for good crop production, even with irrigation because of limited supplies. Increasingly, urban, industrial, environmental, and recreational users compete for agricultural water supplies. Although temporally and spatially variable, annual total supplies are relatively constant. The increasing competition, therefore, makes it imperative that agriculture does its share to conserve water to achieve greater production for an ever-increasing populace. In this report, we discuss basic principles of and some practices for achieving agricultural water conservation, both under dryland (rainfed) and irrigated conditions.

Evapotranspiration of Corn and Forage Sorghum for Silage

In the U.S. Southern High Plains, dairies have expanded and have increased the regional demand for forage and silage. The objectives were to measure water use and determine crop coefficients for corn (Zea mays L.) and forage sorghum (Sorghum bicolor (L.) Moench) produced for silage on the Southern High Plains. Water use was measured with large, precision weighing lysimeters in 2006 and 2007. Both growing seasons had normal to above normal rainfall. The 2006 season was more advective with greater mean daily reference evapotranspiration (ET) rates. Seasonal ET was 671 mm for forage sorghum with a yield of 1.48 kg m -2 in 2006 and 489 mm in 2007 with a yield of 1.70 kg m -2 ; water productivity was 2.21 kg m -3 in 2006 and 3.47 kg m -3 in 2007. Seasonal ET was 418 mm for corn for silage with a yield of 1.52 kg m -2 in 2006 and 671 mm in 2007 with a yield of 2.44 kg m -2 ; water productivity was 3.63 kg m -3 in 2006 and 3.64 kg m -3 in 2007. Using the 2007 season as a better species comparison, forage sorghum can achieve comparable water productivity as corn with less ET (~73% of corn ET) and irrigation requirement although with a reduced yield (~62% of corn dry matter).

Artificial Neural Network Approach for Mapping Contrasting Tillage Practices

Abstract: Tillage information is crucial for environmental modeling as it directly affects evapotranspiration, infiltration, runoff, carbon sequestration, and soil losses due to wind and water erosion from agricultural fields. However, collecting this information can be time consuming and costly. Remote sensing approaches are promising for rapid collection of tillage information on individual fields over large areas. Numerous regression-based models are available to derive tillage information from remote sensing data. However, these models require information about the complex nature of underlying watershed characteristics and processes. Unlike regression-based models, Artificial Neural Network (ANN) provides an efficient alternative to map complex nonlinear relationships between an input and output datasets without requiring a detailed knowledge of underlying physical relationships. Limited or no information currently exist quantifying ability of ANN models to identify contrasting tillage practices from remote sensing data. In this study, a set of Landsat TM-based ANN models was developed to identify contrasting tillage practices in the Texas High Plains. Observed tillage data from Moore and Ochiltree Counties were used to develop and evaluate the models, respectively. The overall classification accuracy for the 15 models developed with the Moore County dataset varied from 74% to 91%. Statistical evaluation of these models against the Ochiltree County dataset produced results with an overall classification accuracy varied from 66% to 80%. The ANN models based on TM band 5 or

Hydraulic Pulldown Procedure for Collecting Large Soil Monoliths

ABSTRACT SOIL monoliths 3-m (9.8-ft) square and 2.4-m (7.8-ft) deep were collected by hydraulically jacking bottomless steel boxes into a clay loam soil. Four jacking assemblies that utilized commercially availabe 178-kN (40,000-lb) hydraulic jacks were anchored to bell-bottomed piers at the corners of the steel boxes. A pulldown frame supported the jacking assemblies over the piers and uniformly distributed the pulldown force over the 9.5-mm (3/8-in.) thick walls of the steel boxes. Soil around the walls of the steel boxes was excavated as the boxes were jacked down. The procedure is a major advance in the collection of large soil monoliths. Bell-bottomed piers or similar anchors provide larger pulldown forces than are practical with deadweights, and hydraulic jacks or cylinders offer precise control of the downward movement. The technique is economically feasible for large soil monoliths, especially where the pulldown equipment can be reused to collect several monoliths.

Crop Production Comparison with Spray, LEPA, and Subsurface Drip Irrigation in the Texas High Plains

Irrigation application method may affect crop yield and water productivity. Crop production was compared for spray, LEPA drag sock, and subsurface drip irrigation (SDI) application methods in the Texas High Plains. Crops included three seasons of grain sorghum, one season of soybean, and four seasons of cotton. Irrigation treatments were 0, 25, 50, 75, and 100% of replacing full crop evapotranspiration, which was measured by neutron probe. For grain sorghum, SDI resulted in the largest grain yield and water use efficiency at the 25 and 50% irrigation treatments, followed by LEPA, but spray outperformed LEPA and SDI at the 75 and 100% treatments. For soybean, the same trend was observed at the 25 and 50% treatments, but SDI performed best at 75%, and spray performed best at 100%. Cotton productivity and gross returns were consistently best for SDI, followed by LEPA, and spray at all irrigation treatments.

Estimating Evapotranspiration for Dryland Cropping Systems in the Semiarid Texas High Plains Using SWAT

The Soil and Water Assessment Tool (SWAT) is one of the most widely used watershed models for simulating hydrology in response to agricultural management practices. However, limited studies have been performed to evaluate the SWAT models ability to estimate daily and monthly evapotranspiration (ET) in semiarid regions. ET values were simulated using ArcSWAT 2012 for a lysimeter field managed under dryland conditions at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas, and compared with measured lysimeter values from 2000 to 2010. Two scenarios were performed to compare SWATs performance: (1) use of default plant leaf area index (LAI) values in the embedded plant database and (2) adjusted LAI values. Scenario 1 resulted in an “unsatisfactory” Nash-Sutcliffe efficiency (NSE) of 0.42 and 0.38 for the calibration and validation periods, respectively. Scenario 2 resulted in a “satisfactory” NSE value for the calibration period while achieving a “good” NSE of 0.70 for the validation period. SWAT generally underestimated ET at both the daily and monthly levels. Overestimation during fallow years may be due to the limitations of the pothole function used to simulate furrow diking. Users should be aware of potential errors associated with using default LAI parameters. Inaccuracies in ET estimation may also stem from errors in the plant stress functions, particularly when evaluating water management practices for dryland watersheds.

ET Mapping with High-Resolution Airborne Remote Sensing Data in an Advective Semiarid Environment

AbstractAccurate estimates of spatially distributed evapotranspiration (ET) are essential for managing water in irrigated regions and for hydrologic modeling. METRIC (Mapping ET at high Resolutions with Internal Calibration) energy balance algorithm was applied to derive ET from six high-resolution aircraft images (0.5–2.0xa0m pixels). Images were acquired over the USDA Agricultural Research Service (USDA-ARS) Conservation and Production Research Laboratory (CPRL) in the semiarid Southern High Plains. The remote sensing (RS) campaign occurred during the 2007 summer cropping season. Daily ET estimations were evaluated using measured ET data from five monolithic weighing lysimeters located in the CPRL. On average, errors in estimating hourly ET were -0.7±11.6%; for daily ET, errors were 2.4±9.3%. Results indicated that METRIC algorithm estimated ET values well when the surface roughness for momentum transfer considered heterogeneous surface conditions and when the grass reference ET fraction was used to extra...