|ADHIKARI, P. - Texas A&M Agrilife|
|ALE, S. - Texas A&M Agrilife|
|BORDOVSKY, J.P. - Texas A&M Agrilife|
|MODALA, N.R. - Integrashare Solutioneering, Inc|
|RAJAN, N. - Texas A&M University|
|BARNES, E.M. - Cotton, Inc|
Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/14/2015
Publication Date: 1/1/2016
Publication URL: http://handle.nal.usda.gov/10113/62261
Citation: Adhikari, P., Ale, S., Bordovsky, J., Thorp, K.R., Modala, N., Rajan, N., Barnes, E. 2016. Simulating future climate change impacts on seed cotton yield in the Texas High Plains using the CSM-CROPGRO-Cotton model. Agricultural Water Management. 164:317–330.
Interpretive Summary: Crop simulation models are increasingly being used as research tools to address a variety of agricultural issues, including irrigation water management and climate change impact assessment. Recent efforts have evaluated the CSM-CROPGRO-Cotton model using cotton data sets from research sites in Texas and Arizona. The next step is to use the evaluated model for studying irrigation water management alternatives and potential climate change impacts on cotton production. The objective of the present study was to further evaluate CSM-CROPGRO-Cotton using four years of data collected at a research site near Halfway, Texas. The evaluated model was then used to simulate cotton yield under historic weather conditions and future climate conditions projected by three climate models. Results showed that future increases in carbon dioxide concentration increased cotton yield. However, concomitant increases in air temperature will necessitate additional water resources to prevent yield losses due to heat and drought stress. This is problematic for the Texas High Plains, which is already experiencing water shortages due to decreasing water levels in the Ogallala aquifer. Results of the study will be useful for scientists and researchers who study the interrelation of water and climate in cotton production systems.
Technical Abstract: The Texas High Plains (THP) region contributes to about 25% of the US cotton production. Dwindling groundwater resources in the underlying Ogallala aquifer, future climate variability and frequent occurrences of droughts are major concerns for cotton production in this region. Assessing the impacts of climate change on cotton production enables development and evaluation of irrigation strategies for efficient utilization of groundwater resources in this region. In this study, the CROPGRO-Cotton module within the Cropping System Model (CSM) that is distributed with the Decision Support System for Agrotechnology Transfer (DSSAT) was evaluated for the THP region using measured data from cotton water use efficiency experiments at Halfway over a period of four years (2010 to 2013). Simulated seed cotton yield matched closely with observed yield during model calibration (average percent error of 0.1) and validation (average percent error of 6.5). The evaluated model was able to accurately simulate seed cotton yield under various irrigation strategies over the four growing seasons. The evaluated CROPGRO-Cotton model was later used to simulate the seed cotton yield under historic (1971 to 2000) and future (2041 to 2070) climate scenarios projected by three climate models. On an average, when compared to historic seed cotton yield, simulated future seed cotton yield across the THP decreased within a range of 4% to 17% when carbon dioxide (CO2) concentration was assumed to be constant at the current level (380 ppm) under three climatic model scenarios. In contrast, when the CO2 concentration was assumed to increase from 493 ppm (in year 2041) to 635 ppm (in year 2070) according to the Intergovernmental Panel on Climate Change (IPCC) A2 emission scenario, the simulated future average seed cotton yield in the THP region increased within a range of 14% to 29% as compared to historic average yield. These results imply that cotton is sensitive to atmospheric CO2 concentrations, and cotton production in the THP could potentially withstand the effects of future climate variability under moderate increases in CO2 levels.