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.

In the semi-arid Texas High Plains, the underlying Ogallala Aquifer is experiencing continuing decline due to long-term pumping for irrigation with limited recharge. Accurate simulation of irrigation and other associated water balance components are critical for meaningful evaluation of the effects of irrigation management strategies. Modelers often employ auto-irrigation functions within models such as the Soil and Water Assessment Tool (SWAT). However, some studies have raised concerns as to whether the function is able to adequately simulate representative irrigation practices. In this study, observations of climate, irrigation, evapotranspiration (ET), leaf area index (LAI), and crop yield derived from an irrigated lysimeter field at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas were used to evaluate the efficacy of the SWAT auto-irrigation functions. Results indicated good agreement between simulated and observed daily ET during both model calibration (2001–2005) and validation (2006–2010) periods for the baseline scenario (Nash-Sutcliffe efficiency; NSE ≥ 0.80). The auto-irrigation scenarios resulted in reasonable ET simulations under all the thresholds of soil water deficit (SWD) triggers as indicated by NSE values > 0.5. However, the auto-irrigation function did not adequately represent field practices, due to the continuation of irrigation after crop maturity and excessive irrigation when SWD triggers were less than the static irrigation amount.

Texas High Plains (THP), one of the most important food and fiber producing regions in the Ogallala Aquifer Region, currently faces rapid decline of groundwater levels. Predicted climate extremes and high temporal variability in growing season precipitation may require growers to pump more groundwater from the Ogallala Aquifer to meet higher crop water demand. The Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model (CSM) is a widely used crop simulation tool for evaluating impacts of different water and crop management practices, including irrigation on crop yield and water use efficiency. In this study, CROPGRO‐Cotton module of the DSSAT was calibrated and validated using 2000, 2001, 2002, and 2010 irrigated lysimeter field data managed by the USDA‐ARS (United States Department of Agriculture ‐ Agricultural Research Service) Conservation and Production Research Laboratory at Bushland, TX. The lysimeter field consisted of four equal plots designated as NE, SE, NW, and SW. Crop growth characteristics including leaf area index (LAI), above ground biomass (AGB), evapotranspiration (ET), soil moisture, and lint yield of 2000‐NE, 2000‐SE, and 2001‐NE, were used for calibration and 2002‐NE, 2010‐NE, and 2010‐SE were used for validation. The calibrated and validated model was used to simulate the long term (1924–2012) crop yield and seasonal crop ET. During the calibration process, some of the cultivar and ecotype parameters that influence LAI, AGB, and lint yield were adjusted for better statistical results. Measured and simulated LAI, AGB, ET, soil moisture, and lint yield showed good agreement during calibration and validation as indicated by performance statistics such asr²from 0.70 to 0.82, and percent error (PE) = −0.85 to 17.3% for LAI;r²= 0.89 to 0.95, andPE= −7.36 to −13.66% for AGB; andr²= 0.90 to 0.94, and PE = 3.20 to 3.44% for ET during calibration and validation, respectively. The model underestimated ET during peak vegetative growth and development stage except in some circumstances. The calibrated and validated model was able to simulate lint yield and seasonal ET during a long term (1924–2012) historic period for Bushland, TX, under irrigated conditions. The calibrated model could be used to schedule ET based irrigation management practices in the THP and to estimate future ET for other modeling experiments.

The Ogallala Aquifer has experienced a continuous decline in water levels due to decades of irrigation pumping with minimal recharge. Corn is one of the major irrigated crops in the semi-arid Northern High Plains (NHP) of Texas. Selection of less water-intensive crops may provide opportunities for groundwater conservation. Modeling the long-term hydrologic impacts of alternative crops can be a time-saving and cost-effective alternative to field-based experiments. A newly developed management allowed depletion (MAD) irrigation scheduling algorithm for Soil and Water Assessment Tool (SWAT) was used in this study. The impacts of irrigated farming, dryland farming, and continuous fallow on water conservation were evaluated. Results indicated that simulated irrigation, evapotranspiration, and crop yield were representative of the measured data. Approximately 19%, 21%, and 32% reductions in annual groundwater uses were associated with irrigated soybean, sunflower, and sorghum, respectively, as compared to irrigated corn. On average, annual soil water depletion was more than 52 mm for dryland farming scenarios. In contrast, only 18 mm of soil water was lost to evaporation annually, for the long-term continuous fallow simulation. The fallow scenario also showed 31 mm of percolation for aquifer recharge.

Performance evaluations and corrections of soil water sensors have not been studied using different installation orientations under various irrigation treatments in the Texas High Plains. This study evaluated the performance of four sensors using factory calibration and derived field corrections as compared to calibrated neutron moisture meters (NMMs). Sensor performance was assessed using horizontal insertion, laid horizontal placement, and vertical insertion at 15.2, 45.7, and 76.2 cm depths in a clay loam soil with three irrigation treatments. Results indicated the factory-calibrated Acclima 315 L performed satisfactorily using horizontal insertion as compared to NMM measurements at 45.7 and 76.2 cm depths with a ±2% mean difference (MD) and 60 mm) in the 0.9 m soil profile using the Watermark 200SS. In summary, field corrections are required for Decagon GS1, Campbell Scientific 655, and Watermark 200SS sensors.

The Ogallala Aquifer Program (OAP) was created in 2003 with support from Congressmen from Kansas and Texas. The OAP is a research‐education consortium seeking solutions from problems arising from declining water availability from the Ogallala Aquifer in western Kansas and the Texas High Plains. The consortium is led by the Agricultural Research Service (ARS) laboratories in Bushland and Lubbock, TX, and the university partners are Kansas State University, Texas A&M AgriLife Research and Extension Service, Texas Tech University, and West Texas A&M University. The OAP has provided over $40 million to support research and education activities. About half of these funds were used to support permanent ARS scientists and ARS hired post‐docs. The other half were used by university scientists to supplement on‐going projects by providing support for supplies, sample analyses, temporary employees, etc. Initially, OAP activities were focused on seven priorities. In 2013, four objectives replaced the original seven priorities. A fifth priority was added in 2017. The current objectives are: 1) Develop and evaluate water management strategies and technologies that could reduce water withdrawals for irrigation by 20% in 2020 compared to 2012; 2) Develop and evaluate management strategies and technologies that would increase the productivity and profitability of dryland cropping systems; 3) Improve the understanding of hydrological and climatic factors that affect water use and agricultural profitability; 4) Determine the impacts of alternative water withdrawal/use policies on the economic viability of the agriculture industry of the Southern Ogallala Aquifer Region; and 5) Develop best management practices for production of high value and alternative crops for both dryland and irrigated systems. The objectives of the program and distribution of resources are decided by an executive committee with a member from each of the four universities, two from ARS, one from Bushland, and the other from Lubbock. Proposed projects that utilize resources from more than one participating institution, leverage existing resources, and address the stated objectives are more likely to be provided support. The impact of the OAP on research directed at agriculture on the High Plains has been recognized by three prestigious awards.