Skip to main content
ARS Home » Plains Area » Lubbock, Texas » Cropping Systems Research Laboratory » Wind Erosion and Water Conservation Research » Research » Publications at this Location » Publication #362362
Title: Determining water-use-efficient irrigation strategies for cotton using the DSSAT CSM CROPGRO-cotton model evaluated with in-season data

Author
item GARIBAY, VICTORIA - Texas A&M University
item KOTHARI, KRITIKA - Purdue University
item SRINIVASULU, ALE - Texas A&M Agrilife
item Gitz, Dennis
item MORGAN, GAYLON - Texas A&M University
item MUNSTER, CLYDE - Texas A&M University

Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/29/2019
Publication Date: 8/20/2019
Citation: Garibay, V., Kothari, K., Srinivasulu, A., Gitz, D.C., Morgan, G.D., Munster, C.J. 2019. Determining water-use-efficient irrigation strategies for cotton using the DSSAT CSM CROPGRO-cotton model evaluated with in-season data. Agricultural Water Management. 223. https://doi.org/10.1016/j.agwat.2019.105695.
DOI: https://doi.org/10.1016/j.agwat.2019.105695

Interpretive Summary: Irrigation water on the Southern High Plains is becoming increasingly scarce, increasingly regulated, and more expensive to obtain and apply. More efficient irrigation methods are needed. In order to predict how different irrigation management schemes many approaches are usually tried side by side over several years in different fields. This is time and resource intensive. It would be nice if researchers would be able to identify bad approaches, and select those most likely to work out before moving to the field to test them. So, researchers decided to test how well a crop model could predict growth and yield responses to different irrigation amounts and timing. Researchers from Texas A&M, Purdue University and USDA-ARS grew a commercial cotton line under several irrigation routines, and measured growth and yield. A crop model was calibrated using growth and environmental data. Then the model was run using various irrigation levels and timing to see if the most efficient irrigation scheme could be predicted (and it was!). These results are important because modeling before actually trying proposed irrigation schemes allows us to focus only on approaches that show promise, which results in faster and more efficient product development.

Technical Abstract: 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 modeling software that uses meteorological, soil, and field experimental 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 data, and crop yield from a field study, and 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 including the Time Temperature Threshold (TTT)-5.5hr, TTT-7.5hr, Daily Irrigation (DI), and percent ET replacement, to determine the most efficient irrigation strategy that results in maximum yield with minimum irrigation water. 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 hr TTT strategy was found to be the best strategy to achieve a maximized yield with the greatest irrigation water use efficiency.