Simulated dryland cotton yield response to selected scenario factors associated with soil health

Authors: ALE, SRINIVASULU - Texas A&M Agrilife; HIMANSHU, SUSHIL - Texas A&M Agrilife; Mauget, Steven; HUDSON, DARREN - Texas Tech University; Goebel, Timothy; LIU, BING - Texas Tech University; Baumhardt, Roland; BORDOVSKY, JAMES - Texas A&M Agrilife; BRAUER, DAVID - Retired ARS Employee; Lascano, Robert; GITZ III, DENNIS - Retired ARS Employee

Submitted to: Frontiers in Sustainable Food Systems
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/22/2020
Publication Date: 2/9/2021
Citation: Ale, S., Himanshu, S.K., Mauget, S.A., Hudson, D., Goebel, T.S., Liu, B., Baumhardt, R.L., Bordovsky, J.P., Brauer, D.K., Lascano, R.J., Gitz III, D.C. 2021. Simulated dryland cotton yield response to selected scenario factors associated with soil health. Frontiers in Sustainable Food Systems. 4. Article 617509. https://doi.org/10.3389/fsufs.2020.617509.
DOI: https://doi.org/10.3389/fsufs.2020.617509

Interpretive Summary: The main source of irrigation water on the Texas High Plains is the declining Ogallala aquifer. Year-on-year well yields are declining, meaning that a transition to dryland agriculture is underway. Cotton is a crop that can be grown both with irrigation and as a dryland crop. There is interest in whether soil health improvements could lead to better dryland cotton yields. USDA ARS, Texas A&M, and Texas Tech University scientists worked together to model crop yield as affected by possible improvements in soil health factors such as reduced surface runoff, increased soil water holding capacity, changes in soil reflection of sunlight back to the atmosphere, and increases in soil organic carbon. Increasing soil organic carbon had no effect on yield. Changes of all of these factors increased modeled seed-cotton yields, but there was no field research result that supported that soil health practices would result in the supposed changes in soil health factors.

Technical Abstract: 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 25mm, 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.