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Highlights Losses for MESA and LESA were comparable on the day of irrigation and oftentimes greater for the subsequent day. Losses were greater due to incomplete canopy conditions for both MESA and LESA on both days. Evaporative losses from irrigation extended to at least the subsequent day following irrigation in most cases. Losses over two days accounted for as much as 39.5% and 28.0% of irrigation depth for MESA and LESA, respectively. Abstract. Effective irrigation systems that increase crop water productivity by minimizing evaporative losses are paramount for extending the longevity of finite groundwater resources in the semi-arid U.S. Southern High Plains (SHP). Although subsurface drip irrigation (SDI) acreage has increased in recent years, center-pivot sprinkler systems still account for greater than 85% of the irrigated area in the SHP. Modern sprinkler configurations are typically classified according to application height as either mid-elevation spray application (MESA) or low-elevation spray application (LESA). While application drift and evaporative losses are easily measured under fallow conditions, quantifying evaporative losses under cropped conditions is difficult. Lysimeter-derived daily evapotranspiration (ET) values for SDI-irrigated and sprinkler-irrigated fields planted to corn in 2016 (MESA) and 2018 (LESA) near Bushland, TX, were compared for days when sprinkler irrigation events occurred and for subsequent days, when possible. Differences (extra ET) were attributed to evaporative losses associated with MESA and LESA irrigation. Average daily extra ET values for both sprinkler irrigation methods were similar on the day of irrigation, although MESA was slightly larger than LESA at 1.4 and 1.2 mm, respectively. The average daily extra ET values for incomplete canopy conditions were 2.2 mm for MESA and 1.9 mm for LESA, while values were identical for both methods at 0.6 mm for full canopy conditions. Average daily extra ET values were also expressed as a percentage of daily standardized grass reference ET (ETos) values. Average values for MESA and LESA were 20.1% and 13.5%, respectively, for the season, with similar findings of 29.3% and 19.4% for incomplete canopy conditions. Average extra ET/ETos values for incomplete canopy conditions were similar at 7.5% and 7.7% for MESA and LESA, respectively. Evaporative irrigation losses, calculated as the percentage of extra ET to irrigation depth, were slightly larger overall for the day of irrigation for MESA (5.4%) than LESA (5.2%). Losses of 7.9% and 7.0% were observed for incomplete canopy conditions for MESA and LESA, respectively. Average losses for LESA (3.5%) under full canopy conditions were greater than those for MESA (1.9%). A comparison of extra ET values for days following irrigation revealed that evaporative losses from irrigation events extended beyond the day of irrigation. MESA extra ET values for the day following irrigations increased by 57.1% (2.2 mm) overall, 13.6% (2.5 mm) for incomplete canopy conditions, and 150.0% (1.5 mm) for full canopy conditions. The same was true for LESA, with increases of 125.0% (2.7 mm) overall, 78.9% (3.4 mm) for incomplete, and 216.7% (1.9 mm) for full canopy conditions. Summing of extra ET values for the day of irrigation and the subsequent day yielded average values more than double those for the day of irrigation only, at 3.9 and 4.3 mm for MESA and LESA, respectively. Similarly, values for extra ET as a percentage of irrigation depth were also more than double those for the day of irrigation only, with the greatest loss values of 39.5% for MESA and 28.0% for LESA. These findings suggest that although LESA appears to mitigate evaporative losses marginally more in corn than MESA on the day of irrigation, considerably more evaporative losses occurred for both methods during the subsequent day, with slightly increased losses for LESA, resulting in little difference between overall losses over the two days. This may in part be explained by the temporary cooling effect of the irrigation inside the canopy on the day of irrigation, which is diminished by the second day. A greater discrepancy between evaporative losses for MESA and LESA is likely to be observed for crops having shorter stature or lower leaf density, such as cotton, although more study is needed to corroborate this claim. Knowledge of these findings provides useful information for both producers and water managers when considering irrigation management and water planning strategies. Keywords: Evaporation, Evapotranspiration, LESA, MESA, Semi-arid, Sprinkler Irrigation, Subsurface Drip Irrigation, Transpiration, Weighing Lysimeters.

Future climate change may have substantial impacts on both water resources and food security in China's black soil region. The Liao River Basin (LRB; 220,000 km

Corn (Zea mays L.) was grown under full and deficit irrigation in two research field locations near Bushland, TX, in 2018 to compare seasonal water use of two irrigation management approaches. Full irrigation was achieved in both fields by allowing no more than 55% depletion of plant available soil water. However, irrigation depth and frequency were different in each field. The USDA-ARS Conservation and Production Research Laboratory (CPRL) weighing lysimeter fields were generally irrigated twice weekly using irrigation depths ranging from 19 to 32 mm. The Texas A&M AgriLife Research Emeny field was irrigated only once per week, having greater application depths ranging from 35 to 42 mm. Deficit irrigation treatments of 75% of full irrigation were also performed in both research fields. Yield and crop water productivity values for the 100 and 75% lysimeter field irrigation treatments were greater than corresponding values for the Emeny field. Emeny field yields may have been slightly reduced by heat stress incurred between irrigations during early grain fill whereas more frequent irrigations on the lysimeter fields may have reduced heat stress during that period. Results from this study suggest that evaporative losses associated with the more frequent, smaller application depth irrigations on the lysimeter fields did not contribute to appreciably lower CWP values, as losses were likely mitigated by the rapid development of the corn canopy. These findings suggest that corn yield is principally dependent upon seasonal water inputs and losses from frequent, smaller depth irrigations are minimal outside of incomplete canopy conditions.

HighlightsLater planting and greater site elevation or latitude decreased seasonal growing degree days and cotton yield in Kansas.Higher irrigation capacity (rate) usually increased lint yield, which was probably due to increased early boll load.Strategies for splitting land allocations between high irrigation rates and dryland did not increase production.Cotton may reduce irrigation withdrawals from the Ogallala aquifer, but the Kansas growing season limits production.Abstract. Precipitation in the western Great Plains averages about 450 mm, varying little with latitude and providing 40% to 80% of potential crop evapotranspiration (ETc). Supplemental irrigation is required to fully meet crop water demand, but the Ogallala or High Plains aquifer is essentially non-recharging south of Nebraska. Pumping water from this aquifer draws down water tables, leading to reduced water availability and deficit irrigation to produce an alternate crop such as cotton (Gossypium hirsutum L.) with a lower peak water demand than corn (Zea mays L.). Our objective was to compare simulated cotton yield response to emergence date, irrigation capacity, and application period at three western Kansas locations (Colby, Tribune, and Garden City) with varying seasonal energy or cumulative growing degree days (CGDD) and compare split center pivot deficit irrigation strategies with a fixed water supply (i.e., where portions of the center pivot land area are managed with different irrigation strategies). We used actual 1961-2000 location weather records with the GOSSYM simulation model to estimate yields of cotton planted into soil at 50% plant-available water for three emergence dates (DOY 145, 152, and 159) and all combinations of irrigation period (0, 4, 6, 8, and 10 weeks beginning at first square) and capacity (2.5, 3.75, and 5.0 mm d-1). Simulated lint yield and its ratio to ETc, or water use efficiency (WUE), consistently decreased with delayed planting (emergence) as location elevation or latitude increased due to effects on growing season CGDD. Depending on location, simulated cotton lint consistently increased (p = 0.05) for scenarios with increasing irrigation capacity, which promoted greater early season boll load, but not for durations exceeding 4 to 6 weeks, probably because later irrigation and fruiting did not complete maturation during the short growing season. Cotton WUE generally increased, with greater yields resulting from earlier emergence and early high-capacity irrigation. We calculated lower WUE where irrigation promoted vigorous growth with added fruiting forms that delayed maturation and reduced the fraction of open bolls. The irrigation strategy of focusing water at higher capacities on a portion of the center pivot in combination with the dryland balance did not increase net yields significantly at any location because the available seasonal energy limited potential crop growth and yield response to irrigation. However, the overall net lint yield was numerically larger for focused irrigation strategies at the southwest Kansas location (Garden City). Based on lint yields simulated under uniform or split center pivot deficit irrigation, we conclude that cotton is poorly suited as an alternative crop for central western and northwestern Kansas because of limited growing season CGDD. Keywords: Cotton, Crop simulation, Deficit irrigation, Evapotranspiration, Irrigation capacity, Split center pivot irrigation, Water use efficiency, Yield limiting factors.

Dwindling water resources and weather variability present two of the major limiting factors for irrigated cotton production in the Southern Great Plains (SGP) of the United States. Under these conditions, there is a dire need to understand the trends and fluctuations in cotton yields to help producers make better irrigation and crop management decisions. Crop models coupled with long-term weather data provide an opportunity for evaluating yield variabilities by simulating numerous potential scenarios. In this study, the AquaCrop model was calibrated and validated for cotton at two sites in the SGP. The validated model was then applied to investigate the effect of variable irrigation capacity (IC) on cotton yield during a 33-year period (1981–2013). The AquaCrop model performed with acceptable accuracy for simulating canopy cover, soil water content, evapotranspiration and yield indicating that it is a potential tool for evaluating variable cotton irrigation scenarios in the SGP. The response of cotton yield to IC was highly dependent on heat unit availability. Yields increased significantly with increase in water availability in years when total growing season heat units were above 1100 °C day. The yield response to irrigation diminished considerably as the magnitude of growing season heat units decreased. No significant increase in mean cotton yield was found at IC higher than 0.3 L s−1 ha−1.

The use of soil water sensors is commonly advocated to aid and improve irrigation management in crop production systems. However, there are concerns about how sensor type, installation technique, sensor orientation, and soil texture may affect sensor accuracy. A field study was conducted to compare the performance of three commercially available soil water sensors (Acclima 315L, Decagon GS1, and Campbell Scientific 655) and a soil water potential sensor (Watermark 200SS) using different installation orientations of horizontal insertion, laid horizontal placement, and vertical insertion at depths of 15, 46, and 76 cm (6, 18, and 30 in.) in an irrigated clay loam soil field. Results indicated all sensors demonstrated similar trends of soil water content in response to wetting events (precipitation and irrigation) at the 15 cm depth following a 4-month settling period prior from the start of the growing season. Comparatively, the Acclima 315L performed well using horizontal insertion compared to calibrated neutron moisture meters (NMMs) at depths of 46 and 76 cm with R2 of 0.73 and 0.96 and slopes of 1.36 and 1.47, respectively. In addition, water storage in the 0.9 m soil profile integrated using the horizontally inserted Acclima 315L across the three depths matched closely with profile water storage determined by the NMMs with a mean difference (MD) and root mean square error (RMSE) of 25.7 and 36.4 mm. However, site-specific corrections or calibrations for each sensor type are required for accurate soil water content estimations with this clay loam soil for irrigation management applications. Keywords: Corn, Irrigation management, Neutron moisture meter, Soil water content, Soil water sensors, Semi-arid region.

HighlightsCrop coefficients for SDI scheduling for grain corn should be reduced by ~10% from those used for sprinkler irrigation.FAO 56 methods to calculate crop coefficients for surface drip irrigation under full-cover plastic mulch were applicable to SDI.A recent drought-resistant corn hybrid appeared to begin rapid leaf area development about 10 days earlier than older hybrids.A recent drought-resistant corn hybrid appeared to finish earlier than older hybrids by about 15 days.Abstract. Subsurface drip irrigation (SDI) has become an important irrigation application method in the U.S. Southern High Plains where pan evaporation exceeds 2,400 mm per year. Early research comparing SDI with spray sprinklers showed that SDI was over-applied when scheduling irrigations using crop coefficients developed using sprinkler irrigation. Thus, crop coefficients developed using SDI may be smaller than those developed using sprinkler irrigation. Grain corn was grown for two years on large, precision weighing lysimeters at Bushland, Texas, with two lysimeters irrigated by SDI and two by mid-elevation spray (MESA) irrigation. Data used in this study were for fields irrigated to replenish soil water in the top 1.5 m of the soil to field capacity, as indicated by weekly neutron probe readings (100% replenishment). Crop coefficients developed for SDI (Kc_SDI) were compared with those developed for MESA (Kc_MESA) using ASCE standardized reference ET equations. The value of Kc_SDI ranged from 0.83 to 0.89 of Kc_MESA for the two years. Values of Kc_SDI remained consistently less than Kc_MESA even after maximum leaf area index was reached, indicating that considerable evaporative loss from the soil surface occurred with MESA irrigation even after full canopy cover. When we shortened the initial period after planting from 30 to 20 d and followed FAO 56 recommendations for surface drip irrigation under full-cover plastic mulch, we calculated basal Kc (Kcb) values (ETo basis) that were reasonably close to our Kc values for SDI for the crop development and early mid-season periods but were greater than our data for the later mid-season and late season periods. Keywords: Crop coefficient, FAO56, MESA, SDI, Sprinkler irrigation, Subsurface drip irrigation.

HighlightsDaily maximum crop coefficient (Kc) values were similar for legacy hybrids and a modern drought-tolerant (DT) hybrid.Later planting dates for a DT hybrid resulted in average season lengths ~25 days shorter than those of legacy hybrids.Results illustrated the effects of environment, planting date, interannual variation in temperature, and the importance of climate-specific Kc functions.DT hybrids may be more effective at reproductive growth during periods of heat stress in semi-arid environments, although additional data are needed to support this conclusion.Abstract. Corn (Zea mays L.) is a major irrigated crop grown in the Southern High Plains including the Texas Panhandle. Irrigation from the Ogallala Aquifer is required to sustain profitable corn production in the region by supplementing inadequate and erratic rainfall. Effective irrigation scheduling works to extend limited groundwater resources by avoiding water losses associated with runoff and/or percolation below the root zone. The use of crop coefficient (Kc) and reference evapotranspiration (ETo) values to estimate daily crop water use (ETc) remains an effective scheduling tool that can complement other irrigation scheduling approaches. Both Food and Agriculture Organization (FAO-56) piecewise and curvilinear Kc values for corn are found in the literature. However, advances in corn genetics have led to questions about the applicability of Kc values developed using legacy corn hybrids to irrigation of modern drought-tolerant (DT) hybrids. Lysimeter-derived Kc values for legacy corn hybrids grown in large weighing lysimeter fields at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas, were compared with those derived from a modern DT corn hybrid recently grown in the same fields. Results indicated that although midseason daily Kc values were similar for all hybrids, average season length was ~25 days shorter for the modern DT hybrid, characterized by a shortened initial growth period followed by more rapid increase of Kc during the development period. However, plots of Kc over thermal time illustrated that the differences in season length were likely attributable to later planting dates associated with the DT corn hybrids. Average seasonal water use was 730 and 811 mm for the legacy and modern DT hybrids, respectively (three years each), with corresponding average yields of 1.2 and 1.4 kg ha-1. Results suggest that published Kc and Kcb values developed with legacy corn hybrids remain largely applicable to modern DT corn hybrids when used with accurate estimates of effective canopy-based growth stages and climate-specific Kc functions. Keywords: Crop coefficients, Drought-tolerant, Evapotranspiration, Maize, Weighing lysimeters.

HighlightsSWAT soil water assessment was performed using soil water measurements.Dryland SWAT model soil water content was greater than the irrigated SWAT model.Using SWAT soil water estimates for real-time (daily) irrigation management purposes with the existing SWAT soil water subroutines and available soils data is considered risky.The surface layer showed the greatest soil water variability compared to deeper layers.Abstract. Soil water content (SWC) is a challenging measurement at the field, watershed, and regional scales. Soil and Water Assessment Tool (SWAT) soil water estimates were evaluated at three locations: the St. Joseph River watershed (SJRW) in northeast Indiana, the USDA-ARS Conservation and Production Research Laboratory (CPRL) at Bushland, Texas, and the USDA-ARS Limited Irrigation Research Farm (LIFR) at Greeley, Colorado. The soil water estimates were evaluated under two scenarios: (1) for the defined soil profile, and (2) by individual layer. Each site’s soil water assessment was performed based on the existing management conditions during each experiment, whether dryland or irrigated, and for various periods depending on SWC measurement availability at each site. The SWAT soil water was evaluated as follows: the Indiana site was evaluated under dryland conditions using daily soil water observations for one year; the Texas site was evaluated for a ten-year period under irrigated and dryland conditions using weekly soil water observations from four lysimeters; and the Colorado site was evaluated under irrigated conditions for a four-year period. The simulated soil water was evaluated by comparing the model simulations with observed daily and weekly soil water measurements at the three sites. Based on the results, even though all the SWAT models were considered to perform as good models following calibration (streamflow, ET, etc.), the soil water simulations were unacceptable for the defined soil profile and for individual layers at the three sites. Deeper soil layers had observations greater than field capacity values, indicating poor soil parameterization. The dryland model had greater water content than the irrigated model, contradicting the soil water measurements. This greater soil water simulation with the dryland model is a result of SWAT model uncertainties with ET reduction under dryland conditions due to water stress. This study indicated that soil water estimation using the default SWAT soil water equations has many sources of uncertainties. Two apparent sources resulted in the SWAT model’s poor performance: (1) SWAT soil water routines that do not fully represent soil water moving between layers to meet plant demand and (2) uncertainty in soil parameterization. Keywords: Hydrologic modeling, Soil moisture, Soil moisture sensor, Soil water, Soil and Water Assessment Tool.

Highlights Irrigation scheduling using accurate ET network data can conserve energy and water. ET networks can be a valuable, cost effective, and feasible management tool in water policy. The Texas High Plains ET Network saved irrigated producers an estimated $US 22M dollars annually. ET network benefits and use extend beyond the agricultural sector. Abstract . Evapotranspiration (ET) networks have been developed and used to support weather and related ET information needs of U.S. agricultural production for nearly half a century, but many networks have been affected by inherent problems associated with sustaining operations. Consequently, these challenges have led to the discontinuation of network service in many cases. Most ET networks have been impacted by inadequate financial support compounded by inadequate public awareness and understanding of their usefulness and value in irrigation management, water conservation and water planning, and policy activities. Data accuracy is vital to usefulness, yet network data quality is often degraded when limited resources result in reduced equipment maintenance and data QA/QC. A discussion of ET network requirements and associated costs is presented. Estimates of the value and pumping reduction using the Texas High Plains ET networks are presented documenting the improvements of crop water use estimates and the impact associated with these improvements on irrigation groundwater withdrawal. Keywords: ET network, Evapotranspiration network, Irrigation scheduling, Irrigation value, Water management tools, Water savings.

Highlights Unmanned aerial systems (UAS) are able to provide data for precision irrigation management. Improvements are needed regarding UAS platforms, sensors, processing software, and regulations. Integration of multi-scale imagery into scientific irrigation scheduling tools are needed for technology adoption. Abstract . Several research institutes, laboratories, academic programs, and service companies around the United States have been developing programs to utilize small unmanned aerial systems (sUAS) as an instrument to improve the efficiency of in-field water and agronomical management. This article describes a decade of efforts on research and development efforts focused on UAS technologies and methodologies developed for irrigation management, including the evolution of aircraft and sensors in contrast to data from satellites. Federal Aviation Administration (FAA) regulations for UAS operation in agriculture have been synthesized along with proposed modifications to enhance UAS contributions to irrigated agriculture. Although it is feasible to use sUAS technology to produce maps of actual crop coefficients, actual crop evapotranspiration, and soil water deficits, for irrigation management, the technology and regulations need to evolve further to facilitate a successful wide adoption and application. Improvements and standards are needed in terms of cameras’ spectral (bands) ranges, radiometric resolutions and associated calibrations, fuel/power technology for longer missions, better imagery processing software, and easier FAA approval of higher altitudes flight missions among other issues. Furthermore, the sUAS technology would play a larger role in irrigated agriculture when integrating multi-scale data (sUAS, ground-based or proximal, satellite) and soil water sensors is addressed, including the need for advances on processing large amounts of data from multiple and different sources, and integration into scientific irrigation scheduling (SIS) systems for convenience of decision making. Desirable technological innovations, and features of the next generation of UAS platforms, sensors, software, and methods for irrigated agriculture, are discussed. Keywords: Agricultural water management, Irrigation prescription mapping, Irrigation scheduling, Precision irrigation, Remote sensing, Sensors, Spatial crop evaOotranspiration, Unmanned aerial systems.

Properly designed, calibrated, and operated weighing lysimeters are recognized as accurate tools for measuring changes of soil water storage (ΔS) in the soil profile contained in the lysimeter. The...

A SWAT model equipped with an alternative auto-irrigation algorithm was used to evaluate the effects of planting date on hybrid corn yield and seasonal water use in the Texas High Plains. Research field data from the USDA-ARS Conservation and Production Research Laboratory at Bushland, TX and the Texas A&M AgriLife North Plains Research Field near Etter, TX were used for model calibration. A long-term weather data set was used to simulate continuous corn using five planting dates (15-April, 1-May, 15-May, 1-June, and 15-June) for both long- and short-season corn hybrids. Results suggested that delayed planting resulted in a reduction of seasonal water use for both hybrids. Reductions in seasonal irrigation between the 15-April and 15-June were 28 % and 31 % for long- and short-season hybrids, respectively, using an application depth of 25.4 mm. Corresponding reductions in yield were considerably less at 8.9 and 8.8 % for long- and short-season hybrids. Reduced irrigation was attributed to decreased temperature stress and lower evapotranspiration of the later growing season. However, simulation of long season corn for the 15-June planting resulted in late season cold temperature stress. Further analysis of 19.1 mm and 31.8 mm irrigation depths revealed the latter resulted in an average of 4.4 and 4.7 % reductions in seasonal irrigation for long- and short-season hybrids, respectively. Results from this assessment study suggest the delayed planting of corn may result in decreased irrigation while maintaining profitable yields, potentially reducing withdrawals from the Ogallala Aquifer in the Texas High Plains region.

Efforts to improve agroecosystem models require methods for unbiased comparisons among simulation algorithms. With focus on evapotranspiration (ET) in Cotton2K, the objectives were to develop a novel methodology for evaluating model parameterization options and to compare model performance using three ET algorithms. The Cotton2K model was updated to include a standardized ET method, and two Penman approaches were also tested. Sobol global sensitivity analysis and multiobjective optimization were used to identify influential parameters and select feasible parameterization options. The three ET methods led to differences in simulation accuracy for ET, soil water contents, and several plant growth metrics ( p 0.05 ). However, no ET method could consistently outperform the other two methods, and ET simulation errors were up to 60%. The simulation methodology permitted unbiased comparison of three ET methods in Cotton2K and highlighted areas for model improvement, including the surface evaporation simulation and the linkage between simulated ET and crop growth.

Modeling the effects of climate change on hydrology and crop yield provides opportunities for choosing appropriate crops for adapting to climate change. In this study, climate change impacts on irrigated corn and sorghum, dryland (rainfed) sorghum, and continuous fallow in the Northern High Plains of Texas were evaluated using an improved Soil and Water Assessment Tool (SWAT) model equipped with management allowed depletion (MAD) irrigation scheduling. Projected climate data (2020–2099) from the Coupled Model Intercomparison Project Phase 5 (CMIP 5) of 19 General Circulation Models (GCMs) were used. Climate data were divided into four 20-year periods of near future (2020–2039), middle (2040–2059), late (2060–2079), and end (2080–2099) of the 21st century under two Representative Concentration Pathway (RCP) emission scenarios (RCP 4.5 and RCP 8.5). For irrigated corn, median annual crop evapotranspiration (ET) and irrigation decreased by 8%–25% and 15%–42%, respectively, under the climate change scenarios compared to the historical period (2001–2010). The median yield was reduced by 3%–22% with exponentially decreases in the latter half of the 21st century. For sorghum, the reduction of median annual crop ET ranged from 6%–27%. However, the decline in the median annual irrigation was within 15%, except for the 2060–2079 and 2080–2099 periods under RCP 8.5 scenarios with 30% and 49% reductions in median annual irrigation. The median irrigated sorghum yield declined by 6%–42%. The median annual crop ET of dryland sorghum decreased by 10%–16%. The reduction in median yield was within 10% of the historical dryland sorghum yield. The decrease in median annual evaporation varied from 15%–23% under future continuous fallow conditions. The elevated CO2 level of future climate scenarios was the primary factor for the decrease in the ET and irrigation. The reduction in future crop yield was mainly attributed to the shortening of the maturity period caused by increased future temperature.

High quality estimates of evapotranspiration (ET) are needed for water-limited agriculture where irrigation is necessary to efficiently grow crops. Eddy covariance (EC) systems are observational tools used to measure water and heat fluxes, but a tendency to underestimate fluxes causes a lack of surface energy balance closure. Surface energy budgets are useful for verifying ET estimates, especially in advective conditions that affect energy partitioning. Here, we explored the effect of heat storage and advective conditions on surface energy balance closure for the 2014 and 2015 growing seasons in Bushland, Texas. Storage components were estimated near the center of an irrigated sorghum field using an array of soil and surface layer measurements. A comparison of EC estimated turbulent fluxes and available energy consisting of net radiation, soil heat flux, and storage was used to identify advective conditions and assess surface energy balance closure. Our results indicated daytime mean heat storage of approximately 40 W m−2 with a diurnal pattern featuring a midday peak that exceeded the evening minimum in magnitude, mostly reflective of soil heat storage but also affected by air, water, and biomass heat storage during the morning hours and photosynthesis storage during midday hours. Daytime advective conditions were associated with higher heat storage frequently under stable atmospheric conditions. The surface energy balance was more closed in 2014 than 2015; the 2014 energy balance exhibited a hysteretic pattern with a surplus of turbulent energy in the afternoon, whereas systematic underestimation was common in 2015. This finding is related to a larger proportion of data in 2014 being advective, characterized by a lower Bowen ratio and greater ET, particularly during the late afternoon. Regardless of advection classification, heat storage was demonstrated to be important for daytime energy balance in this irrigated cropland.

Greater than 80% of the irrigated area in the Southern High Plains is served by center-pivot irrigation, but the area served by subsurface drip irrigation (SDI) is increasing due to several factors including declining well yields and improved yields and crop water productivity (CWP), particularly for cotton. Not as well established is the degree to which the reduced soil water evaporation (E) in SDI systems affects the soil water balance, water available to the crop, and overall water savings. Grain corn ( L.) and sorghum ( L. Moench) were grown on four large weighing lysimeters at Bushland, Texas, in 2013 (corn), 2014 and 2015 (sorghum), and 2016 (corn). Evapotranspiration (ET) was measured using the lysimeters and using a neutron probe in the surrounding fields. Two of the lysimeters and surrounding fields were irrigated with SDI, and the other two were irrigated with mid-elevation spray application (MESA). The lysimeter-measured evaporative losses were 149 to 151 mm greater from sprinkler-irrigated corn fields than from SDI fields. When growing sorghum, the lysimeter-measured evaporative losses were 44 to 71 mm greater from sprinkler-irrigated fields than from SDI fields. The differences were affected by plant height and became smaller when plant height reached the height of the spray nozzles, indicating that the use of LEPA or LESA nozzles could decrease the evaporative losses from sprinkler-irrigated fields in this region with its high evaporative demand. Annual weather patterns also influenced the differences in evaporative loss, with increased differences in dry years. SDI reduced overall corn water use by 13% to 15%, as determined by neutron probe, while either not significantly affecting yield (2016) or increasing yield by up to 19% (2013) and increasing CWP by 37% (2013) to 13% (2016) as compared with MESA full irrigation. However, sorghum yield decreased by 15% and CWP decreased by 14% in 2014 when using SDI compared with MESA full irrigation due to an overly wet soil profile in the SDI fields and deep percolation that likely caused nutrient losses. In 2015, there were no significant sorghum yield differences between irrigation methods. Sorghum CWP was significantly greater (by 14%) in one SDI field in 2015 compared with MESA fully irrigated sorghum. Overall, sorghum CWP increased by 8% for SDI compared with MESA full irrigation in 2015. These results indicate that SDI will be successful for corn production in the Texas High Plains, but SDI is unlikely to benefit sorghum production. Keywords: Corn, Crop water productivity, Evaporative loss, Evapotranspiration, Irrigation application method, Sorghum, Water use efficiency, Weighing lysimeter.