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.

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.