Evaluation of growth-stage-based variable deficit irrigation strategies for cotton production in the Texas High Plains

Authors: HIMANSHU, SUSHIL - Asian Institute Of Technology; ALE, SRINIVASULU - Texas A&M Agrilife; BELL, JOURDAN - Texas A&M Agrilife; FAN, YUBING - Lanzhou University; SAMANTA, SAYANTAN - Texas A&M University; BORDOVSKY, JAMES - Texas A&M Agrilife; Gitz, Dennis; Lascano, Robert; Brauer, David

Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/6/2023
Publication Date: 4/3/2023
Citation: Himanshu, S.K., Ale, S., Bell, J., Fan, Y., Samanta, S., Bordovsky, J., Gitz, D.C., Lascano, R.J., Brauer, D.K. 2023. Evaluation of growth-stage-based variable deficit irrigation strategies for cotton production in the Texas High Plains. Agricultural Water Management. 280. https://doi.org/10.1016/j.agwat.2023.108222.
DOI: https://doi.org/10.1016/j.agwat.2023.108222

Interpretive Summary: The depth to the water-table of the Ogallala aquifer under the Texas High Plains is increasing. As water suitable for irrigation gets deeper, it becomes less available; water-well capacities decrease and it gets more expensive to lift the water from deeper in the ground. By carefully timing sparse irrigation we might be able to maintain existing yields, or at least maintain agricultural profitability and sustainability. Scientists at Texas Agrilife, in conjunction with ARS scientists in Bushland and Lubbock, TX used mathematical models to understand how timing deficit irrigation would affect cotton yield. It was found that the late stage of peak blooming is when cotton is most sensitive to drought. The results will help develop appropriate irrigation management strategies to sustaining cotton production in the Texas High Plains.

Technical Abstract: Irrigated agriculture in the Texas High Plains (THP) region faces severe challenges due to rapidly declining groundwater levels in the underlying Ogallala Aquifer, recurring droughts, and projected warmer and drier future climatic conditions. Scheduling irrigation with appropriate deficits in different crop growth stages could improve irrigation water use efficiency (IWUE), and additional savings in valuable groundwater could be achieved without compromising with the yield. This study aimed to identify efficient growth-stage-based variable deficit irrigation (GS-VDI) strategies for cotton production in the THP region. This study considered four growth stages: (i) first leaf to first square (GS1), (ii) flower initiation/ early bloom (GS2), (iii) peak bloom (GS3), and (iv) cutout, late bloom, and boll opening stage (GS4). A recently evaluated CROPGRO-Cotton model based on observed data from a cotton IWUE experiment conducted at Texas A&M AgriLife Research Center at Halfway, TX, in the THP region was used to achieve the study objective. Long-term (1977-2019) simulations were conducted with four deficit levels (30%, 50%, 70%, and 90% ET replacements) implemented for each growth stage, resulting in 256 combinations of deficit irrigation scenarios. In general, GS3 (Peak bloom growth stage) was found to be the most sensitive to water stress, and GS4 (Cutout, late bloom, and boll opening growth stage) was found to be the least sensitive to water stress. The results from this modeling study could help develop appropriate irrigation management strategies aimed at sustaining cotton production under different climate variability classes while conserving valuable groundwater resources in the Ogallala Aquifer region.