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HighlightsIrrigation water use efficiency was consistently higher under deficit irrigation as compared to full irrigation.Irrigation water use was always less than the annual allowable pumping limit under deficit irrigation.The first/second week of September was ideal for terminating irrigation under full/deficit irrigation in normal years.Ideal irrigation termination periods in wet/dry years were a week earlier/later than those in normal years.Abstract. Cotton ( L.) production in the Texas High Plains (THP) region relies heavily on irrigation with groundwater from the underlying Ogallala Aquifer. However, rapidly declining groundwater levels in the aquifer and increasing pumping costs pose challenges for sustainability of irrigated cotton production in this region. Adoption of efficient irrigation strategies, such as terminating irrigation at an appropriate time in the growing season, could enable producers to increase irrigation water use efficiency (IWUE) while maintaining desired yield goals. The objective of this study was to determine optimum irrigation termination periods for cotton production in the THP under full and deficit irrigation conditions using the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Cotton model, which was evaluated in a prior study in the THP using measured data from an IWUE field experiment at Halfway, Texas. The treatment factors in the field experiment included irrigation capacities of 0 mm d-1 (low, L), 3.2 mm d-1 (medium, M), and 6.4 mm d-1 (high, H), applied during the vegetative, reproductive, and maturation growth stages. This study focused on a full irrigation (HHH) treatment and three deficit irrigation (LMH, LHM, and LMM) treatments. Eight irrigation termination dates with a one-week interval between 15 August and 30 September were simulated, and the impact of irrigation termination date on cotton IWUE and seed cotton yield were studied by dividing the 39-year (1978 to 2016) simulation period into dry, normal, and wet years based on the precipitation received from 1 April to the simulated irrigation termination date. Results indicated that the simulated IWUE was consistently higher under the LHM, LMH, and LMM treatments when compared to the HHH treatment. Based on the simulated average seed cotton yield and IWUE, optimum irrigation termination periods for cotton were found to be the first week of September (about 118 days after planting, DAP) for the HHH and LMH treatments and the second week of September (125 DAP) for the LHM and LMM treatments in normal years. In wet years, optimum irrigation termination periods were a week earlier than those in normal years and a week later in dry years for the HHH, LHM, and LMM treatments. For the LMH treatment, the optimum irrigation termination period in wet years was the same as that in normal years and two weeks later in dry years. The results from this study along with field-specific, late-season information will assist THP cotton producers in making appropriate irrigation termination decisions for improving economic productivity of the Ogallala Aquifer and thereby ensuring water security for agriculture. However, the recommendations from this study should be used with caution, as the optimum irrigation termination periods could potentially change with changes in cultivar characteristics, soil type, climate, and, crop management practices. Keywords: CROPGRO-Cotton, Deficit irrigation, DSSAT, Full irrigation, Irrigation water use efficiency, Seed cotton yield.

HighlightsASABE and ISAE convened the Global Water Security Conference for Agriculture and Natural Resources in Hyderabad, India, in 2018.Recommendations represent collective contribution of attendees and presenters in seven key priorities.Continuation of a narrow focus on technical aspects will likely prevent the success of technical solutions.Scientists and engineers should work together across all disciplines and boundaries to ensure global water security. Keywords: Climate change, Crop water productivity, Food security, Irrigation efficiency, Natural resource policy, Wastewater reuse, Water resource infrastructure, Water scarcity.

HighlightsIrrigated grain sorghum yield and irrigation water use decreased under climate change.Increase in growing season temperature beyond 26°C resulted in a sharp decline in grain sorghum yield.Irrigating during early reproductive stages resulted in the most efficient use of limited water.Irrigating to replenish soil water to 80% of field capacity was found suitable for both current and future climates. Groundwater overdraft from the Ogallala Aquifer for irrigation use and anticipated climate change impacts pose major threats to the sustainability of agriculture in the Texas High Plains (THP) region. In this study, the DSSAT-CSM-CERES-Sorghum model was used to simulate climate change impacts on grain sorghum production under full and deficit irrigation strategies and suggest optimal deficit irrigation strategies. Two irrigation strategies were designed based on (1) crop growth stage and (2) soil water deficit. For the first strategy, seven deficit irrigation scenarios and one full irrigation scenario were simulated: three scenarios with a single 100 mm irrigation scheduled between panicle initiation and boot (T1), between boot and early grain filling (T2), and between early and late grain filling (T3) growth stages; three 200 mm irrigation treatments with combinations of T1 and T2 (T4), T1 and T3 (T5), and T2 and T3 (T6); one 300 mm irrigation scenario (T7) that was a combination of T1, T2, and T3; and a full irrigation scenario (T8) in which irrigation was applied throughout the growing season to maintain at least 50% of plant-available water in the top 30 cm soil profile. For the second strategy, the irrigation schedule obtained from auto-irrigation (T8) was mimicked to create a full irrigation scenario (I100) and six deficit irrigation scenarios. In the deficit irrigation scenarios, water was applied on the same dates as scenario I100; however, the irrigation amounts of scenario I100 were reduced by 10%, 20%, 30%, 40%, 50%, and 60% to create deficit irrigation scenarios I90, I80, I70, I60, I50, and I40, respectively. Projected climate forcings were drawn from nine global climate models (GCMs) and two representative concentration pathways (RCP 4.5 and RCP 8.5). Climate change analysis indicated that grain sorghum yield under full irrigation was expected to be reduced by 5% by mid-century (2036 to 2065) and by 15% by late-century (2066 to 2095) under RCP 8.5 compared to the baseline period (1976 to 2005). Simulated future irrigation water demand of grain sorghum was reduced due to the shorter growing season and improved dry matter- and yield-transpiration productivity, likely due to CO2 fertilization. Based on the simulated grain sorghum yield and irrigation water use efficiency, the most efficient use of limited irrigation was achieved by applying irrigation during the early reproductive stages of grain sorghum (panicle initiation through early grain filling). A 20% deficit irrigation scenario was found to be optimal for current and future conditions because it was more water use efficient than full irrigation with a minor yield reduction of

HighlightsWe provide context and perspectives on 13 articles in the Global Water Security collection.Limited irrigation, precision irrigation, and sustainable water resources management were critical themes.The collection emphasizes the need for adopting location-specific technologies to achieve global water security.Advances in data acquisition, data analysis, and modeling should be utilized to aid managing water resources. Abstract. This article introduces the Global Water Security collection in this issue of Transactions of the ASABE and issue 36(1) of Applied Engineering in Agriculture. Researchers, educators, industry partners, agricultural producers, and policymakers from 19 countries met at Hyderabad, India, to discuss critical issues and advancements at the Global Water Security Conference for Agriculture and Natural Resources. The conference was organized jointly by ASABE and the Indian Society of Agricultural Engineers (ISAE). This special collection consists of 13 articles selected from the 245 meeting presentations as well as invited articles. A perspectives article in this collection summarizes seven key priorities identified for action at the conference: reduce food waste, increase wastewater reuse, increase agricultural resiliency and efficiency, optimize irrigation efficiency and increase crop water productivity, improve water supply management, improve water resource infrastructure, and enhance water resource decision-making and policy formulation. The remaining 12 articles address a wide range of water security topics grouped by four themes: sustainable management of water resources (3 articles), limited irrigation for water conservation (5 articles), precision irrigation management (2 articles), and water management in hilly regions (2 articles). While these articles are not inclusive of all water security challenges in the agriculture and natural resources sectors, they highlight selected important challenges and potential solutions. The research presented in this special collection emphasizes the importance of developing and using appropriate location-specific technologies that increase water application efficiency and water use efficiency while maintaining adequate water supplies for natural resource functions and ecosystem services to ensure global water security. Keywords: Climate change, Crop water productivity, Food security, Irrigation efficiency, Natural resource policy, Wastewater reuse, Water resource infrastructure, Water scarcity.

The Texas High Plains (THP) is a productive agricultural region, and it relies heavily on the exhaustible Ogallala Aquifer for irrigation water for crop production. Efficient use of irrigation water is critical for the sustainability of agriculture in the THP. Grain sorghum is one of the major crops grown in the region, and it is known for its drought tolerance and lower water requirement compared to other cereal crops such as corn. In this study, the CERES-Sorghum and CROPGRO-Cotton modules of the Decision Support System for Agrotechnology Transfer (DSSAT) were evaluated using data from cotton-sorghum rotation experiments at Halfway, Texas over a period of nine years (2006–2014). The evaluated CERES-Sorghum model was then used to identify the optimum (i) initial soil moisture at planting (ISM); (ii) threshold to start irrigation (ITH); (iii) threshold to terminate irrigation; and iv) deficit/excess (DFI) irrigation strategy for grain sorghum production based on simulated sorghum yield, irrigation water use efficiency (IWUE), and grain water use efficiency (WUE). In addition, the effect of weather conditions on simulated strategies was elucidated by dividing the long-term (1977–2016) weather data into cold, warm, wet, dry, and normal climate variability classes based on the 33rd and 66th percentiles of growing season temperature and precipitation. The DSSAT model adequately simulated the grain sorghum and seed cotton yields during calibration (average Percent Error (PE) of 1.3% (sorghum) and 3.4% (cotton)) and evaluation (average PE of −2.2% (sorghum) and −10.5% (cotton)). The results from long-term simulations indicated that weather conditions played a key role in selecting appropriate irrigation management strategies. Under normal/cold/wet weather, ISM of 75% available water holding capacity (AWC), ITH of 50%, and DFI 85% were found to be adequate for irrigated grain sorghum production. However, in warm/dry weather, ISM of 75%, ITH 60%, and DFI at 100% reduced sorghum yield loss.

In the Texas High Plains (THP), diminishing irrigation well-capacities, and increasing costs of energy and equipment associated with groundwater extraction and application are contributing factors to a transition from irrigated to dryland agriculture. The primary goal of this modeling exercise was to investigate whether and to what extent hypothetical changes in factors putatively associated with soil health would affect dryland cotton (Gossypium hirsutum L.) yields. The factors selected were drainage, surface runoff, soil water holding capacity, soil organic carbon (SOC) and albedo. As a first analysis to evaluate these factors, we used the CROPGRO-Cotton module within the Decision Support System for Agrotechnology Transfer (DSSAT) cropping system model. Specifically, we evaluated the effects of reduced surface runoff, increased soil water holding capacity, and SOC, doubling of the soil albedo through stubble mulching, and of soil drainage by enhancing infiltration with no-tillage/cover crops on yield by adjusting related soil properties. In our analysis, we used mean yields simulated with soil properties of a Pullman clay loam soil at Halfway, TX on the THP as baseline, which were compared to values obtained with the adjusted factors using weather data from 2005 to 2019. Simulated mean yield increased by 27% when the soil water holding capacity was increased by 25 mm, 7% when the runoff curve number was decreased from 73 to 60, 16% when soil albedo was increased from 0.2 to 0.4, and by 58% when the soil drainage factor (fraction day−1) was doubled from 0.2. No significant statistical change in simulated mean yield was calculated when SOC was increased by 1%. Further, effects of a 50 mm pre-plant irrigation were also assessed, simulating limited irrigation in the transition to dryland agriculture that resulted in a statistically insignificant 12% increase in seed-cotton yield. Simultaneous implementation of the four statistically significant individual scenarios (increased water holding capacity, infiltration, albedo, and drainage) resulted in the highest increase (93%) in mean seed-cotton yield. An economic and risk analysis of simulated yields under different scenarios indicated that these factors could reduce revenue risk for dryland cotton producers, with most of the effect from soil drainage improvements.

Texas High Plains (THP), which is an important cotton (Gossypium hirsutum L.) growing region in the United States faces challenges from declining/deteriorating groundwater levels/quality, recurring droughts and severe wind erosion. Growing cover crops after harvesting cotton and/or changing land use from cotton to perennial bioenergy crops could not only address above challenges, but also assist in meeting the national biofuel target. The objective of this study is to assess the implications of changes in land use (replacing cotton with Alamo switchgrass (Panicum virgatum L.) and Miscanthus × giganteus) and crop management (growing winter wheat (Triticum aestivum L.) cover crop) on hydrology and wind erosion in the Double Mountain Fork Brazos Watershed using the Agricultural Policy/Environmental eXtender (APEX) model. Simulated average annual wind erosion, total nitrogen (TN) loss to surface water and nitrate-nitrogen (NO3-N) leaching to groundwater reduced by more than 37%, 43% and 73%, respectively, when winter wheat was grown as a cover crop under the 457 mm (18-inch) annual groundwater pumping limit setup by the High Plains Water District. In addition, winter wheat produced about 0.20–0.26 kg m−2 of biomass for biofuel purposes. Land use change from irrigated cotton to switchgrass and rainfed cotton to Miscanthus decreased the TN load, NO3-N leaching and soil loss by wind erosion by > 89% relative to the baseline scenario. Under the groundwater pumping restrictions, multiple harvests of perennial grasses were found to be better in terms of biomass production (>2 kg m−2), and protection of groundwater and soil.

As the Ogallala Aquifer depletes there is a need to identify management options that might make un-irrigated cotton production sustainable over the U.S. Southern High Plains (SHP). To explore those options, the CSM-CROPGRO-Cotton model was used to simulate the effects of planting options and elevation effects on SHP dryland cotton production. Of the management variables that define the 56 planting options simulated, planting date and density account for the most variability in median SHP yields. Cooler SHP growing seasons have the effect of reducing median lint yields relative to those simulated over the lower elevations of the nearby Rolling Plains. This effect is not as evident in median Rolling Plains yields, which suggests it can be traced to the cooler growing environment of the higher SHP elevations. Also, at both higher and lower elevations lower planting densities maximize median yields, while higher densities result in the lowest yields. These results suggest that the yield suppressing effect of the SHP region’s cooler growing conditions might be compensated for by planting early whenever possible and planting at lower densities. The clear decreasing effect on median yields at higher elevation also suggests the possibility of SHP cotton production moving to the lower elevations of the nearby Rolling Plains as Ogallala Aquifer levels drop.

The eddy covariance method was used to investigate carbon fluxes and evapotranspiration (ET) from a high biomass forage sorghum ( Sorghum bicolor L.) field in the Southern U.S. Great Plains for three growing seasons (2013–2015). Above normal precipitation and narrow row spacing (50 cm) led to higher biomass production (25 Mg ha −1 ) and leaf area index (LAI = 7.2) development in 2014. This also resulted in higher carbon uptake or net ecosystem production (NEP) and ET during that year. Early and late season precipitation enhanced ecosystem respiration (R eco ) resulting in lower NEP in 2015. Shorter growing season (119 days) also contributed to lower cumulative NEP in 2015. Estimated gross primary production (GPP) in 2014 (1780 g m −2 ) was 10% higher than the GPP in 2013 (1591 g m −2 ) and 24% higher than the GPP in 2015 (1353 g m −2 ). During all growing seasons, the site was a source of carbon (negative NEP) at the beginning and transitioned to a sink (positive NEP) later in the season. Biomass-GPP relationship indicated that approximately 65% of total GPP was allocated to above ground biomass (AGB). Average monthly ecosystem WUE (expressed as gross carbon gain per unit of ET) ranged from 1.7 g mm −1 to 4.2 g mm −1 . Results from our study indicate that weather conditions, growing season length and crop management are important factors in determining the magnitude of carbon uptake and release, and ET of this cellulosic biofuel feedstock crop in the Southern U.S. Great Plains.

Inappropriate grazing management with high stocking rates can result in significantly higher levels of runoff, sediment and nutrient losses to surface water resources. An assessment of water quality effects of various grazing management practices enables the selection of appropriate management practices. The overall objective of this study was to assess the impacts of alternate grazing management practices including the heavy continuous (HC), light continuous (LC) and adaptive multi-paddock (MP) grazing, and no grazing (EX; exclosure) on water quality at the ranch and watershed scales in the rangeland-dominated (71% rangeland) Clear Creek Watershed (CCW) in north central Texas using the Soil and Water Assessment Tool (SWAT). The SWAT model was calibrated and validated for water quality predictions using the measured data on county-level crop yield (1980–2013), and monthly sediment (1994–2009), total nitrogen (TN) and total phosphorus (TP) loads (1986–2009) at the watershed outlet. The ranch-scale assessment results at two study ranches indicated that when the grazing management was changed from the baseline MP grazing to HC grazing, the simulated average (1980–2013) annual surface runoff, sediment, TN and TP losses increased within the ranges of 106%–117%, 6.0–8.1 ton ha−1, 8.3–11.5 kg ha−1, and 1.6–2.6 kg ha−1, respectively. At the watershed-scale, shifting grazing management from the baseline HC grazing to the improved MP grazing decreased surface runoff, sediment, TN and TP loads by 47.0%, 39.7%, 35.1% and 34.1%, respectively. Thus, adaptive MP grazing was found to be the best grazing management practice for the CCW in terms of water quality protection and improvement in ecosystem functions such as reduced soil erosion and increased nutrient retention at both ranch and watershed scales. However, the magnitudes of water quality benefits due to adoption of MP grazing vary according to the extent of grazing lands in a watershed.

Interest in cover crops has been increasing in the Texas Rolling Plains (TRP) region, mainly to improve soil health. However, there are concerns that cover crops could potentially reduce soil water and thereby affect the yield of subsequent cash crops. Previous field studies from this region have demonstrated mixed results, with some showing a reduction in cash crop yield due to cover crops and others indicating no significant impact of cover crops on subsequent cotton fiber yield. The objectives of this study were to (1) evaluate the CROPGRO-Cotton and CERES-Wheat modules within the cropping system model (CSM) of the Decision Support System for Agrotechnology Transfer (DSSAT) for the TRP region, and (2) use the evaluated model to assess the long-term effects of growing winter wheat as a cover crop on water balances and seed cotton yield under irrigated and dryland conditions. The two DSSAT crop modules were calibrated using measured data on soil water and crop yield from four treatments: (1) irrigated cotton without a cover crop (CwoC-I), (2) irrigated cotton with winter wheat as a cover crop (CwC-I), (3) dryland cotton without a cover crop (CwoC-D), and (4) dryland cotton with a winter wheat cover crop (CwC-D) at the Texas A&M AgriLife Research Station at Chillicothe from 2011 to 2015. The average percent error (PE) between the CSM-CROPGRO-Cotton simulated and measured seed cotton yield was -10.1% and -1.0% during the calibration and evaluation periods, respectively, and the percent root mean square error (%RMSE) was 11.9% during calibration and 27.6% during evaluation. For simulation of aboveground biomass by the CSM-CERES-Wheat model, the PE and %RMSE were 8.9% and 9.1%, respectively, during calibration and -0.9% and 21.8%, respectively, during evaluation. Results from the long-term (2001-2015) simulations indicated that there was no substantial reduction in average seed cotton yield and soil water due to growing winter wheat as a cover crop. Keywords: CERES-Wheat, Cover crop, Crop simulation model, CROPGRO-Cotton, DSSAT, Seed cotton yield, Soil water.

Grazing management practices affect watershed hydrology by altering vegetation cover and soil properties. Long-term success of grazing management depends on how well increased forage harvest efficiency is balanced with the need to maintain soil aggregate stability. The overall objective of this study was to assess the impacts of alternate grazing management practices including the light continuous (LC), heavy continuous (HC), adaptive multipaddock (MP) grazing, and no grazing (EX; exclosure) on hydrological processes at the ranch and watershed scales in a rangeland-dominated (71% rangeland) Clear Creek watershed (CCW) in north central Texas using the Soil and Water Assessment Tool (SWAT). Measured data on vegetation, soil physical and hydrological properties, and grazing management at four study ranches within the watershed (two under MP and one each under LC and HC grazing management) were used to parameterize the SWAT model. The SWAT model was calibrated and validated using the measured standing crop biomass and soil moisture data at the study ranches, and streamflow data at the watershed outlet over a 34-year period from 1980 to 2013. At the ranch scale, when the management was changed from the baseline MP grazing to HC grazing, the simulated average (1980 to 2013) annual surface runoff increased within a range of 106% to 117% and water yield increased within a range of 39% to 53%. While surface runoff was found to be a major contributor (52% to 67%) to streamflow under the HC grazing, baseflow was the dominant (55% to 66%) component of streamflow under the MP and EX practices. At the watershed scale, shifting grazing management from the baseline HC grazing to the improved MP grazing decreased surface runoff by about 47%, increased infiltration by 5%, and decreased streamflow by 29.5%. In addition, improvements to grazing decreased the simulated highest annual streamflow over the 1980 to 2013 period from 8.3 m3 s−1 ([293.1 ft3 sec−1] baseline scenario) to 6.2 m3 s−1 ([219 ft3 sec−1] MP grazing). This reduction in the maximum flow has a potential to reduce the risk of flooding downstream. However, these hydrologic responses vary according to the extent of grazing lands in a watershed. Overall, the MP grazing was found to be the best grazing management practice in terms of water conservation, vegetation regrowth, and the potential to reduce flood risk.

Declining water levels in the southern Ogallala Aquifer and associated reduction in irrigation capacities and increasing pumping costs necessitate adoption of deficit/limited irrigation practices for sustaining cotton production in the Texas High Plains (THP) region. The overall goal of this study was to evaluate the response of cotton crop to water stress in different growth stages and suggest efficient growth-stage-based deficit (GSBD) irrigation schedules for maximizing yield, crop water productivity (CWP) and economic returns under contrasting weather conditions using the CROPGRO-Cotton model. Five growth stages including seedling emergence/germination, squaring, early bloom/flower initiation, peak bloom, and boll opening/late bloom were considered. A combination of five irrigation scenarios (S1 through S5 with seasonal irrigation amounts of 240, 300, 360, 420 and 480 mm) and six irrigation treatments (T1 through T5: no irrigation in one of the five growth stages, and T6: irrigation applied in all five growth stages) were then simulated with a center pivot irrigation system. Skipping irrigation during the peak bloom growth stage (T4 treatment) resulted in the lowest yield, CWP and net returns under all weather conditions. The T1 irrigation treatment in which irrigation was skipped during the seedling emergence/germination stage was identified as the most efficient irrigation strategy for maximizing yield, CWP and net returns among all irrigation scenarios. Application of more than 360, 420 and 480 mm of irrigation water in wet, normal and dry years, respectively, did not significantly improve yield or net returns, and resulted in a decrease in CWP. These results imply that cotton responses to water deficit vary by growth stages, and adoption of appropriate GSBD irrigation strategies could optimize the use of limited water resources and extend the life of the southern Ogallala Aquifer.

Bioenergy crop production has the potential to protect marginal crop lands that generate high surface runoff and produce poor crop yields. Long-term evaluation of the impacts of such land use change on hydrologic fluxes and biofuel production potential is necessary before adopting such strategies on a large scale. In this study, the hydrologic impacts of replacing cotton (Gossypium hirsutum L.) on marginal lands in an intensive agricultural watershed in the Texas High Plains with Alamo switchgrass (Panicum virgatum L.) as a bioenergy crop were evaluated using the Agricultural Policy/Environmental eXtender (APEX) model. The surface runoff to cotton yield ratio was used as a criterion to identify marginal cotton subareas (homogenous spatial units delineated by APEX) in the study watershed, and three replacement scenarios (low (9 %), medium (33 %), and high (57 %) extents of cotton acreage replaced by switchgrass) were implemented in the scenario analysis. The average (1994–2009) annual surface runoff decreased by about 84 and 66 %, and the percolation increased by 106 and 57 % in the irrigated and dryland subareas, respectively, when cotton was replaced by switchgrass under the high replacement scenario. Spatial analysis showed that switchgrass was a feasible bioenergy crop for replacing cotton, especially in the western part of the study watershed, due to its higher water use efficiency and better water conservation effects compared to cotton. It is estimated that 193 and 381 million liters of ethanol could be produced from the dryland and irrigated subareas of the study watershed, respectively, under the high replacement scenario.

The Southern High Plains (SHP) region of Texas in the United States, where cotton is grown in a vast acreage, has the potential to grow cellulosic bioenergy crops such as perennial grasses and biomass sorghum (Sorghum bicolor). Evaluation of hydrological responses and biofuel production potential of hypothetical land use change from cotton (Gossypium hirsutum L.) to cellulosic bioenergy crops enables better understanding of the associated key agroecosystem processes and provides for the feasibility assessment of the targeted land use change in the SHP. The Soil and Water Assessment Tool (SWAT) was used to assess the impacts of replacing cotton with perennial Alamo switchgrass (Panicum virgatum L.), Miscanthus giganteus (Miscanthus sinensis Anderss. [Poaceae]), big bluestem (Andropogon gerardii) and annual biomass sorghum on water balances, water use efficiency and biofuel production potential in the Double Mountain Fork Brazos watershed. Under perennial grass scenarios, the average (1994-2009) annual surface runoff from the entire watershed decreased by 6% to 8% relative to the baseline cotton scenario. In contrast, surface runoff increased by about 5% under the biomass sorghum scenario. Perennial grass land use change scenarios suggested an increase in average annual percolation within a range of 3% to 22% and maintenance of a higher soil water content during August to April compared to the baseline cotton scenario. About 19.1, 11.1, 3.2 and 8.8 Mg ha−1 of biomass could potentially be produced if cotton area in the watershed would hypothetically be replaced by Miscanthus, switchgrass, big bluestem and biomass sorghum, respectively. Finally, Miscanthus and switchgrass were found to be ideal bioenergy crops for the dryland and irrigated systems, respectively, in the study watershed due to their higher water use efficiency, better water conservation effects, greater biomass and biofuel production potential, and minimum crop management requirements. This article is protected by copyright. All rights reserved

The Texas High Plains (THP) region contributes to about 25% of the US cotton production. Dwindling groundwater resources in the underlying Ogallala aquifer, future climate variability and frequent occurrences of droughts are major concerns for cotton production in this region. Assessing the impacts of climate change on cotton production enables development and evaluation of irrigation strategies for efficient utilization of groundwater resources in this region. In this study, the CROPGRO-Cotton module within the Cropping System Model (CSM) that is distributed with the Decision Support System for Agrotechnology Transfer (DSSAT) was evaluated for the THP region using measured data from cotton water use efficiency experiments at Halfway over a period of four years (2010–2013). Simulated seed cotton yield matched closely with observed yield during model calibration (average percent error of 0.1) and validation (average percent error of 6.5). The evaluated model was able to accurately simulate seed cotton yield under various irrigation strategies over the four growing seasons. The evaluated CROPGRO-Cotton model was later used to simulate the seed cotton yield under historic (1971–2000) and future (2041–2070) climate scenarios projected by three climate models. On an average, when compared to historic seed cotton yield, simulated future seed cotton yield across the THP decreased within a range of 4–17% when carbon dioxide (CO2) concentration was assumed to be constant at the current level (380 ppm) under three climatic model scenarios. In contrast, when the CO2 concentration was assumed to increase from 493 ppm (in year 2041) to 635 ppm (in year 2070) according to the Intergovernmental Panel on Climate Change (IPCC) A2 emission scenario, the simulated future average seed cotton yield in the THP region increased within a range of 14–29% as compared to historic average yield. When the irrigation amount was reduced by 40% (from 100% to 60%), the average (2041–2070) seed cotton yield decreased by 37% and 39% under the constant and increasing CO2 concentration scenarios, respectively. These results imply that cotton is sensitive to atmospheric CO2 concentrations, and cotton production in the THP could potentially withstand the effects of future climate variability under moderate increases in CO2 levels if irrigation water availability remains at current levels.

Adaptation measures are required to enhance climate change resilience of agricultural systems and reduce risks associated with climate change at both regional and global scales. The Texas High Plains is a semi-arid region that faces major challenges from climate change risks and dwindling groundwater supply from the exhaustible Ogallala Aquifer for sustaining irrigated agriculture. The overall goal of this study was to assess the impacts of climate change on yield and water use of grain sorghum and identify optimum climate change adaptation strategies for three study sites in the Texas High Plains. Future climate data projected by nine Global Circulation Models (GCMs) under two Representative Concentration Pathways (RCPs) of greenhouse gas emissions (RCPs 4.5 and 8.5) were used as input for the DSSAT CSM-CERES-Sorghum model. The climate change adaptation strategies were designed by modifying crop genotype parameters to incorporate drought tolerance, heat tolerance, high yield potential, and long maturity traits. Irrigated and dryland grain sorghum yield and irrigation water use were projected to decrease at varying percentages at the study sites in the future. On an average (of 9 GCMs), irrigated grain sorghum yield is expected to decrease by 5–13 % and 16–27 % by mid-century (2036–2065) and late-century (2066–2095), respectively under RCP 8.5 compared to the baseline (1976–2005). The irrigation water use is expected to decrease by 7–9% and 14–16 % by the mid-century and late-century, respectively. Among the adaptation strategies, an ideotype with high yield potential trait (10 % higher partitioning to the panicle, radiation use efficiency, and relative leaf size than the reference cultivar) resulted in maximum grain sorghum yield gains in the future under both irrigated (6.9 %–17.1 %) and dryland (7.5 %–17.1 %) conditions, when compared to the reference cultivar. Enhancing drought tolerance by increasing root density at different soil depths also resulted in a significantly higher irrigated grain sorghum yield than the reference cultivar. A longer maturity cultivar will likely increase irrigation water use and, therefore, is not recommended for water limited conditions.

Water is the limiting factor for crop production within the southern US Great Plains and it has become a critical resource for multiple stakeholders. Hence, efficient irrigation and cropping systems are of paramount importance to conserve water resources. The objective of this study was to determine the effect of irrigation timing and quantity, cover crop use and tillage on cotton production in an established conservation tillage system. Evaluated tillage systems included: 1) conventional tillage (CT); 2) strip-tillage (ST); 3) no-till (NT); and 4) NT with a terminated wheat cover crop (NT-W). Irrigation treatments included 1) 5.08-6.35 mm d−1 initiated mid-season (LOW); 2) 6.35-8.38 mm d−1 initiated mid-season (MED); and 3) 5.08-6.35 mm d−1 initiated early-season (HIGH). No significant differences in lint yield or irrigation water use efficiency (IWUE) were observed between MED and HIGH. Although HIGH resulted in 12 % greater lint yields than LOW, HIGH resulted in 67 % greater irrigation water applications. LOW resulted in significantly greater IWUE than MED and HIGH. No-till systems, with and without a cover crop, had significantly greater lint yields and IWUE than CT. Furthermore, inclusion of wheat in NT increased yields and IWUE compared with ST. Applying irrigation water at a critical growth stage proved to be more water efficient than early season irrigation that was used to bank moisture in the soil profile. Delaying irrigation application until critical growth stages and using cover crops should be considered as best management approaches to conserve water resources while sustaining cotton production in the Southern Great Plains.

Identification of efficient crop-growth-stage-based deficit irrigation strategies for cotton (Gossypium hirsutum L.) can play a pivotal role in optimizing the use of available irrigation water in the Southern High Plains (SHP) region, which is facing severe challenges from rapidly declining groundwater levels in the underlying Ogallala Aquifer. The objective of this study was to suggest efficient crop-growth-stage-based deficit irrigation strategies for cotton under nine different climate variability classes using the CROPGRO-Cotton module available in the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model (CSM). Cotton growth stages considered in this study include: i) germination and seedling emergence (GS1), ii) squaring (GS2), iii) flower initiation/ early bloom (GS3), iv) peak bloom (GS4), and v) cutout, late bloom and boll opening stage (GS5). The amount of seasonal irrigation water applied was varied from 120 to 540 mm under eight different irrigation scheduling scenarios with four irrigation application rates of 3, 6, 8 and 9 mm d−1 using the subsurface drip irrigation method. Under each scenario, six growth-stage-based irrigation treatments were adopted, resulting in a total of 48 irrigation strategies. Results indicated that imposing water deficit in the initial (GS1 to GS2) or final (GS5) growth stages had little effect on seed cotton yield. The peak bloom growth stage (GS4) was found to be the most sensitive stage to water stress, and imposing water deficit during this stage resulted in the lowest irrigation water use efficiency (IWUE) and seed cotton yield under most climate variability classes. Application of higher than 420 mm irrigation did not significantly contribute to an increase in seed cotton yield and resulted in a decline in IWUE. The results from this study are useful for the SHP producers to make appropriate crop-growth-stage-based deficit irrigation management decisions for achieving higher seed cotton yield while conserving precious irrigation water resources from the Ogallala Aquifer.

Winter wheat is one of the major crops in the Texas High Plains (THP) region, which is facing challenges from climate change (CC) and exhausting irrigation water supplies from the Ogallala Aquifer. The goal of this study was to assess the impacts of CC on winter wheat production in the THP and evaluate potential adaptation strategies using the Decision Support System for Agrotechnology Transfer (DSSAT) CERES-Wheat model. A thorough calibration of the model against field data resulted in a satisfactory simulation of phenology, leaf area index, grain yield (percent error, |PE

The Texas High Plains (THP) region, a vital part of U.S. grain and fiber production, is experiencing the effects of conflicting interests in the diminishing Ogallala Aquifer, making necessary the adoption of more efficient irrigation strategies. Decision Support System for Agrotechnology Transfer (DSSAT) is a process-based model that uses meteorological, soil, and crop management data to predict crop growth, development, and yield. A well-evaluated DSSAT model is useful for simulation of efficient crop and irrigation management strategies. This study details the evaluation of CROPGRO-Cotton module in the DSSAT model based on measured in-season biomass and canopy height, and crop yield data from a field study as well as the use of the evaluated model for determining the best irrigation strategy for cotton (Gossypium hirsutum L. var. hirsutum) in terms of crop yield and irrigation water use efficiency. Irrigation simulation experiments were conducted over a testing range for four separate irrigation scheduling strategies —Time Temperature Threshold (TTT)-5.5 h, TTT-7.5 h, Daily Irrigation (DI), and percent ET replacement —to determine the most efficient irrigation strategy that results in maximum yield with minimum irrigation water input. The DSSAT CROPGRO-Cotton model demonstrated potential to simulate the effects of various irrigation strategies on cotton yield and water use efficiency. The 12 mm, 7.5 h TTT strategy was found to be the best strategy to achieve a maximized yield with the greatest irrigation water use efficiency, with a modelled yield of 5887 kg ha−1 using 195 mm of irrigation throughout the season.