Evaluation of CSM-CROPGRO-Cotton for simulating effects of management and climate change on cotton growth and evapotranspiration in an arid environment

Authors: Thorp, Kelly; BARNES, EDWARD - Non ARS Employee; Hunsaker, Douglas - Doug; Kimball, Bruce; White, Jeffrey; Nazareth, Vijay; HOOGENBOOM, G - University Of Washington

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/14/2014
Publication Date: 12/1/2014
Citation: Thorp, K.R., Barnes, E.M., Hunsaker, D.J., Kimball, B.A., White, J.W., Nazareth, V.J., Hoogenboom, G. 2014. Evaluation of CSM-CROPGRO-Cotton for simulating effects of management and climate change on cotton growth and evapotranspiration in an arid environment. Transactions of the ASABE. 57(6):1627-1642.

Interpretive Summary: Crop simulation models are increasingly being used as research tools to address a variety of agricultural issues, such as crop water use and irrigation water management, nitrogen dynamics and fertilizer management, and climatology and global climate change. In the United States, development of crop simulation models began in the late 1960's and focused on cotton. Several cotton simulation models have been developed since then, one of which is the CSM-CROPGRO-Cotton model. Past evaluations and applications of CSM-CROPGRO-Cotton have focused mainly in the humid southeastern United States, and there has been a need to test the model for the arid and semi-arid cotton production regions of the western United States. The objective of this study was to perform a comprehensive evaluation of CSM-CROPGRO-Cotton for irrigated cotton systems in the arid conditions of central Arizona. Cotton growth and water use data from five field experiments conducted at the Maricopa Agricultural Center in Maricopa, Arizona were used in the evaluation. Simulations of cotton growth in response to water deficit, nitrogen deficit, planting density, and elevated carbon dioxide were comparable to field measurements. A main outcome of the evaluation was an improvement of the model's calculation of crop water use to better match standardized methods previously developed for the western United States. Other opportunities for improvement of the model were also identified. With this research effort, an important cotton simulation tool has been evaluated and improved, which will provide benefit to a growing number of cotton scientists and researchers who use simulation models to solve important cotton production problems.

Technical Abstract: Originally developed for simulating soybean growth and development, the CROPGRO model was recently re-parameterized for cotton. However, further efforts are necessary to evaluate the model's performance against field measurements for new environments and management options. The objective of this study was to evaluate CSM-CROPGRO-Cotton using data from five cotton experiments conducted at the Maricopa Agricultural Center in Maricopa, Arizona. The field experiments tested ambient atmospheric carbon dioxide (CO2) versus free-air CO2 enrichment (FACE) over two growing seasons (1990 and 1991), two irrigation levels and two nitrogen fertilization levels for one growing season (1999), and three planting densities and two nitrogen fertilization levels with optimum irrigation for two growing seasons (2002 and 2003). The model was calibrated by adjusting cultivar and soil parameters for the most optimal or standard treatment of each field trial, and the model's responses to suboptimal irrigation, suboptimal nitrogen fertilization, nonstandard planting density, and CO2 enrichment were evaluated. Modifications to the model's evapotranspiration (ET) routines were required for more realistic ET simulations in the arid conditions of central Arizona. Data quality and availability among the field trials were highly variable, but the combination of data sets from multiple field investigations permitted a more thorough model evaluation. Simulations of leaf area index, canopy weight, canopy height, and canopy width responded appropriately compared to measurements from experimental treatments, although some experiments did not impose enough treatment variability to elicit substantial model responses. Simulation results for densely planted cotton were particularly deficient as compared to other experimental treatments. The model simulated seed cotton yield with root mean squared errors ranging from 107 to 1120 kg ha-1(3% to 29% of mean values), and total seasonal ET was simulated with root mean squared errors ranging from 11 to 40 mm (1% to 4% of mean values). Seed cotton yield and ET variability due to the imposed experimental treatments was simulated appropriately (p<0.05), independent of the year-to-year variability due to individual experiments. Modification of the ET routines permitted a maximum simulated crop coefficient of 1.14 for four of five growing seasons, which was more realistic than that obtained from default ET methods in the model. Overall, the evaluation demonstrated appropriate model responses to water deficit, nitrogen deficit, planting density, and CO2 enrichment. Potential opportunities for further model improvement include the estimation of crop responses to high planting densities, the simulation of cotton maturity and defoliation events, and the calculation of canopy temperature as part of a complete energy balance algorithm.