Gary W. Marek

Modeling long-term water use of irrigated cropping rotations in the Texas High Plains using SWAT

The Ogalalla Aquifer is used to supplement insufficient precipitation for agricultural production in the semiarid Texas High Plains. However, decades of pumping combined with minimal recharge has resulted in decreased well capacity in most areas. A calibrated Soil and Water Assessment Tool (SWAT) model was used to compare simulated yields, crop water use, and required irrigation for crop rotations of the region using measured long-term (90xa0years) historical weather data. Crop rotations included continuous corn and cotton, corn–cotton, sorghum–cotton, cotton–winter wheat, and corn–winter wheat. Results demonstrated that a calibrated SWAT model simulated crop water use and yields well for all listed crops except cotton. The plant growth algorithms in SWAT appear unable to simulate representative cotton yields typical of cotton management in the Texas High Plains. A work-around for a limitation of the auto-irrigate function in SWAT to be suspended during the dormancy period of winter wheat was also used. Summary statistics for crop yield, crop water use, and irrigation were presented for all rotations. Long-term water use of simulations and irrigation probability exceedance statistics are presented for all simulated crops. These data may serve as a decision support tool for producers considering crop rotation strategies.

Time-Varying PM10 Emissions from Open-Lot Dairies and Cattle Feedyards

Typical PM emission-factor studies for dairies and feedyards have involved measuring ground-level concentration as close to the plume centerline as weather predictions permit, followed by dispersion modeling using a single-valued emission factor to match the 24-hour average concentration. Using AERMOD as our dispersion-modeling platform, we confirm that the 24-hour average emission factor cannot reproduce the hourly average concentrations throughout the day and vastly underpredicts the magnitude of the evening dust peak. Moreover, matching a single concentration measurement near the plume centerline is not as rigorous a dispersion-modeling test as attempting to match an entire transverse cross-section of the plume along the downwind boundary.

Determination of Feedyard Evaporation Using Weighing Lysimeters

Six shallow, weighing lysimeters were installed near Etter, TX, to measure quasi-instantaneous nevaporation rates from simulated feedyard surfaces. The data revealed a pronounced and consistent nhygroscopic period during which the manure appears to have absorbed water from the atmosphere. Daily nmeasurements during late autumn 2003 showed lysimeter evaporation to be 30% of reference evapotranspiration n(ETo) of well-watered grass. Warm-season data from an upgraded load-cell system capable of ncontinuous monitoring showed lysimeter evaporation to be poorly correlated with ETo, with a mean of napproximately 20% and a range of 15-30%. The lower ratio in the most recent data may be attributed to (a) nsmaller manure particle size and greater sorptive affinity as compared to the first experiment, (b) increased nevaporative demand in the warm-season experiment, which may not have been satisfied due to a flux-limiting nhydraulic conductivity in the manure matrix and (c) other unknown factors that require further investigation. nThe hygroscopic behavior of the manure surface during the nighttime hours dramatically decreases the net ndaily evaporation, is loosely associated with a decrease in the vapor pressure deficit and reduces the expected nwater needs for feedyard dust control. Future investigations will quantify the sensitivity of the evaporation rate nto surface roughness, manure particle size, target moisture content and advanced manure/soil layering nprocedures.

Evaluation of the Oceanic Niño Index as a decision support tool for winter wheat cropping systems in the Texas High Plains using SWAT

Abstract The semi-arid Texas High Plains has experienced decreasing well capacities due to decades of pumping with negligible recharge. Improvements in irrigation system efficiency and advances in drought tolerant crop varieties have improved water use efficiency. However, a gradual transition of irrigated lands to dryland management systems is expected for many areas in the region within the coming decades. Producers may elect to allocate more acreage to dryland crops such as winter wheat during this transition. Precipitation forecasting approaches may aid producers when considering planting acreage and additional inputs. Classifications of the El Nino Southern Oscillation (ENSO) periods have been associated with seasonal fluctuations of precipitation in North America. In this study, the Oceanic Nino Index (ONI), used to classify El Nino and La Nina phases of the ENSO, was evaluated for predicting growing season precipitation for winter wheat using measured data from the USDA-ARS Conservation and Production Laboratory (CPRL) for 1950–2015. Although not statistically significant, probability exceedance plots revealed a tenable correlation between precipitation and ONI classifications. Corresponding winter wheat yields were also simulated using the Soil and Water Assessment Tool (SWAT) model using both continuous and single-year scenarios designed to determine the effects of antecedent soil water resulting from inter-seasonal precipitation and residual soil water. The sporadic and uncertain nature of precipitation appeared to outweigh the ONI signal for prediction of precipitation for the winter wheat growing season in the Texas High Plains. However, simulated minimum yield values associated with El Nino phase classifications were nearly three times those of La Nina and phase neutral values, suggesting that ONI-based predictions of El Nino conditions have a lower probability of reduced yields. This finding in part supports the use of the ONI as a decision support tool for the planting of increased acreage and/or additional inputs for winter wheat crops in the Texas Panhandle. Additional analysis using long term precipitation data from multiple sites in the region would provide a more comprehensive determination of the efficacy of the ONI as a management tool.

Net ecosystem exchange of CO 2 and H 2 O fluxes from irrigated grain sorghum and maize in the Texas High Plains

Net ecosystem exchange (NEE) of carbon dioxide (CO2) and water vapor (H2O) fluxes from irrigated grain sorghum (Sorghum bicolor L. Moench) and maize (Zea mays L.) fields in the Texas High Plains were quantified using the eddy covariance (EC) technique during 2014-2016 growing seasons and examined in terms of relevant controlling climatic variables. Eddy covariance measured evapotranspiration (ETEC) was also compared against lysimeter measured ET (ETLys). Daily peak (7-day averages) NEE reached approximately -12u202fgu202fCu202fm-2 for sorghum and -14.78u202fgu202fCu202fm-2 for maize. Daily peak (7-day averages) ETEC reached approximately 6.5u202fmm for sorghum and 7.3u202fmm for maize. Higher leaf area index (5.7 vs 4-4.5u202fm2u202fm-2) and grain yield (14 vs 8-9u202ftu202fha-1) of maize compared to sorghum caused larger magnitudes of NEE and ETEC in maize. Comparisons of ETEC and ETLys showed a strong agreement (R2u202f=u202f0.93-0.96), while the EC system underestimated ET by 15-24% as compared to lysimeter without any corrections or energy balance adjustments. Both NEE and ETEC were not inhibited by climatic variables during peak photosynthetic period even though diurnal peak values (~2-weeks average) of photosynthetic photon flux density (PPFD), air temperature (Ta), and vapor pressure deficit (VPD) had reached over 2000u202fμmolu202fm-2u202fs-1, 30u202f°C, and 2.5u202fkPa, respectively, indicating well adaptation of both C4 crops in the Texas High Plains under irrigation. However, more sensitivity of NEE and H2O fluxes beyond threshold Ta and VPD for maize than for sorghum indicated higher adaptability of sorghum for the region. These findings provide baseline information on CO2 fluxes and ET for a minimally studied grain sorghum and offer a robust geographic comparison for maize outside the United States Corn Belt. However, longer-term measurements are required for assessing carbon and water dynamics of these globally important agro-ecosystems.

Evaluation of Sensible Heat Flux and Evapotranspiration Estimates Using a Surface Layer Scintillometer and a Large Weighing Lysimeter

Accurate estimates of actual crop evapotranspiration (ET) are important for optimal irrigation water management, especially in arid and semi-arid regions. Common ET sensing methods include Bowen Ratio, Eddy Covariance (EC), and scintillometers. Large weighing lysimeters are considered the ultimate standard for measurement of ET, however, they are expensive to install and maintain. Although EC and scintillometers are less costly and relatively portable, EC has known energy balance closure discrepancies. Previous scintillometer studies used EC for ground-truthing, but no studies considered weighing lysimeters. In this study, a Surface Layer Scintillometer (SLS) was evaluated for accuracy in determining ET as well as sensible and latent heat fluxes, as compared to a large weighing lysimeter in Bushland, TX. The SLS was installed over irrigated grain sorghum (Sorghum bicolor (L.) Moench) for the period 29 July–17 August 2015 and over grain corn (Zea mays L.) for the period 23 June–2 October 2016. Results showed poor correlation for sensible heat flux, but much better correlation with ET, with r2 values of 0.83 and 0.87 for hourly and daily ET, respectively. The accuracy of the SLS was comparable to other ET sensing instruments with an RMSE of 0.13 mm·h−1 (31%) for hourly ET; however, summing hourly values to a daily time step reduced the ET error to 14% (0.75 mm·d−1). This level of accuracy indicates that potential exists for the SLS to be used in some water management applications. As few studies have been conducted to evaluate the SLS for ET estimation, or in combination with lysimetric data, further evaluations would be beneficial to investigate the applicability of the SLS in water resources management.