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Over semi-arid agricultural regions such as the U.S. Southern High Plains (SHP) producers of dryland crops need to know which management practices increase yields and decrease production risk. Here, a modeling approach is used to explore management options (MO) that increase dryland cotton yields and estimate those practice's yield risk effects under current SHP climate conditions. To simulate current dryland yield variability, dense distributions of lint yield outcomes were generated using the CROPGRO-Cotton crop model driven by weather inputs from 21 SHP weather stations during 2005–2016. Management effects were explored by repeating simulations over 32 MOs defined by 4 planting dates, 4 planting densities, and applying or not applying nitrogen. Both earlier planting date and decreased plant density increased median simulated yields, with earlier planting having the greatest positive yield effects. The simulated MO that produced the highest median lint yields planted on the earliest planting date (May 15), at the lowest density (3 plants m−1), and applied no nitrogen. Recent SHP field studies generally confirm the earlier planting date effect, but suggest insignificant yield effects for different seeding rates. Even so, negligible yield effects and lower input costs favor lower seeding densities from a profit standpoint. These crop simulations demonstrate a modeling-based method for climate-related agricultural risk management, and suggest mid-May planting dates and low plant densities as part of management practices that increase yields and profits in dryland SHP cotton production.

Sorghum's heat and drought tolerance make it, together with upland cotton, one of two crops produced profitably under dryland conditions in the U.S. Southern High Plains (SHP). Here, a simulation-based method evaluates management options that increase median (50th percentile) SHP dryland sorghum yields and estimates those practice's yield risk effects. This method generates climate-representative distributions of grain yields via a crop model driven by weather inputs from 21 SHP weather stations during 2005–2016. Optimal management practices for current SHP climate conditions were sought by generating yield distributions under 32 management options defined by four planting dates, four plant densities, and applied or no applied N. The highest median grain yields resulted from management options with the latest planting date (July 5) and the lowest plant density (24.7 K plants ha−1), while applied N had essentially no yield effect. Increased yields with later planting dates are consistent with sorghum's growth cycle and SHP summer rainfall climatology. Confirming the low plant density yield effect may require additional field studies, as supporting evidence of higher yields at lower densities from other SHP field and modeling studies is inconclusive. These crop simulations, however, suggest late June to early July planting as part of management practices that maximize yields in dryland SHP sorghum production.