Evaluation of the CSM-CROPGRO-Cotton Model for the Texas Rolling Plains Region and Simulation of Deficit Irrigation Strategies for Increasing Water Use Efficiency

Abstract

Cotton is one of the major crops cultivated in the Texas Rolling Plains region, and it is a major contributor to the regional economy. Cotton cultivation in this region is facing severe challenges due to an increase in the frequency of droughts and a projected decrease in rainfall in the future. Development and evaluation of deficit irrigation strategies for this region could potentially conserve water while maintaining cotton yields. In this study, the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model (CSM) CROPGRO-Cotton was extensively tested and then used for evaluating various deficit irrigation strategies for this region. The model inputs were obtained from field experiments conducted at Chillicothe, Texas, during four growing seasons: 2008-2010 and 2012. The model was first calibrated using the data from a 100% evapotranspiration (ET) replacement irrigation scheduling experiment conducted in 2012 and then validated on three other irrigation scheduling treatments (75% ET replacement, soil moisture based, and tensiometer based) conducted in the same year. The model was further evaluated using the data from cotton tillage and irrigation experiments conducted in an adjacent field during 2008-2010. The model calibration, validation, and evaluation results were satisfactory except under dry conditions (0% ET replacement and 33% ET replacement). Simulated maximum seed cotton yields under normal and dry weather conditions were achieved at 100% and 110% ET replacement, respectively. Percentage decrease in seed cotton yield was marginal (3.5% to 8.8%) when the amount of irrigation water applied was decreased from 100% to 66% ET replacement under normal rainfall conditions. However, under less than normal rainfall (drier) conditions, the percentage decrease in seed cotton yield was substantial (about 17.5%) when the irrigation strategy was switched from 100% to 70% ET replacement. The simulations demonstrate that adopting deficit irrigation practices under normal weather conditions can conserve water without adversely affecting seed cotton yields. However, under dry conditions, there is a risk of increased yield loss, and therefore producers should consider that risk when adopting deficit irrigation strategies.

Simulated Effects of Winter Wheat Cover Crop on Cotton Production Systems of the Texas Rolling Plains

“…Photothermal duration between first flower and first pod (FL-SH), which was important to simulate the timing of first boll, was adjusted to 4, and photothermal time between first flower and end of leaf expansion (FL-LF) was adjusted to 50 days. Similarly, other sensitive parameters that affect the photosynthesis rate, transpiration, and assimilation of carbon in Modala et al (2015) for the TRP region and by Adhikari et al (2016) for the nearby THP region.…”

“…Salmerón et al (2014) used the DSSAT CSM to evaluate the impact of a cover crop-maize rotation on N leaching for a range of soil types and irrigation management practices in Spain. Modala et al (2015) used the DSSAT CSM-CROPGRO-Cotton model to identify appropriate deficit-irrigation strategies for increasing water use efficiency in the TRP region. Recently, Adhikari et al (2016) used the CSM-CROPGRO-Cotton model to simulate future (2041-2070) seed cotton yields in the THP region under increasing and constant atmospheric CO 2 concentration scenarios.…”

Determining Optimum Irrigation Termination Periods for Cotton Production in the Texas High Plains

“…The DSSAT CSM can simulate crop growth, development, and yield in response to variability in weather conditions, soil properties, and management practices (Jones et al, 2003;Hoogenboom et al, 2012Hoogenboom et al, , 2015Thorp et al, 2014). The DSSAT CSM CROPGRO-Cotton model has been extensively used by researchers worldwide for various applications (Buttar et al, 2007;Pathak et al, 2007;Ortiz et al, 2009;Pereira et al, 2009;Thorp et al, 2010Thorp et al, , 2014Modala et al, 2015;Adhikari et al, 2016Adhikari et al, , 2017Mauget et al, 2017;Loison et al, 2017;Amin et al, 2018;Spivey et al, 2018).…”

Cotton Irrigation Scheduling Using a Crop Growth Model and FAO-56 Methods: Field and Simulation Studies

“…As one example, Suleiman et al (2007) used the CSM-CROPGRO-Cotton model to schedule irrigation for cotton in Georgia and analyzed the experimental results using FAO-56 water balance methods (Allen et al, 1998). More routinely, crop growth models are used for post-hoc analysis of data from past field experiments, which culminate as an effort in model evaluation (Farahani et al, 2009;Guerra et al, 2004;Modala et al, 2015;Thorp et al, 2014b). Once evaluated, models are often applied as simulation tools to address a variety of research questions related to irrigation management (Baumhardt et al, 2009;Cammarano et al, 2012;DeJonge et al, 2007;Kisekka et al, 2016;McCarthey et al, 2014;Nair et al, 2013), crop water use (Droogers, 2000), or regional water management issues (Guerra et al, 2007;Yang et al, 2010).…”