Location: Forage and Livestock Production ResearchTitle: Calibration and validation of CSM-CROPGRO-cotton model using lysimeter data in the Texas High Plains Author
|Adhikari, Pradip - Oklahoma State University|
|Brauer, David - Dave|
|Kisekka, Isaya - Kansas State University|
|Rocatelli, Alex - Oklahoma State University|
Submitted to: Journal of Contemporary Water Research and Education
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/6/2017
Publication Date: 1/2/2018
Citation: Adhikari, P., Gowda, P., Marek, G.W., Brauer, D.K., Kisekka, I., Northup, B.K., Rocatelli, A. 2018. Calibration and validation of CSM-CROPGRO-cotton model using lysimeter data in the Texas High Plains. Journal of Contemporary Water Research and Education. 162: 61-78.
Interpretive Summary: The Texas High Plains is experiencing rapid declines in groundwater levels as annual groundwater withdrawals have outpaced natural recharge of Ogallala Aquifer. This has resulted large decline in the amount of water available for use as well as increased groundwater pumping costs. A well calibrated crop model using the field experimental data could successfully be used to simulate crop responses under different irrigation strategies. In this study, we calibrated the DSSAT crop simulation model for estimating evapotranspiration, leaf area index and yield for irrigated cotton in the Texas High Plains. Comparison of measured and simulated leaf area index (LAI), above ground biomass (AGB) and ET, soil moisture and lint yield showed very good agreement during calibration and validation. The model slightly under predicated the ET during peak vegetative growth and development stage except some occasions due to under predicted leaf area index. Overall, performance statistics indicated that DSSAT is capable of simulating evapotranspiration, LAI and lint yield accurately and suitable for evaluating cotton under different irrigation strategies.
Technical Abstract: The Texas High Plains (THP) is one of the most important food and fiber producing regions in the Ogallala Aquifer Region, currently facing rapid decline of groundwater levels. Predicated climate extremes and high temporal variability in growing season precipitation in the future may demand growers to pump more groundwater from the Ogallala Aquifer to meet higher crop water demand. The Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model (CSM) is a widely used crop simulation tool for evaluating impacts of different water and crop management practices including irrigation on crop yield and water use efficiency. In this study, CROPGRO-Cotton module of the DSSAT was calibrated and validated using long term data (2000-2010) from an irrigated lysimeter field managed by the USDA-ARS Conservation and Production Research Laboratory at Bushland, TX. Data were divided equally for calibration and validation purposes. Crop growth characteristics including leaf area index (LAI), above ground biomass (AGB) and ET, soil moisture and lint yield from 2000, 2001, 2002 and 2010 cotton growing seasons were used for model calibration and validation. During calibration process some of the cultivar and ecotype parameters that influences LAI, AGB and lint yield were adjusted for better statistical results. Measured and simulated LAI, AGB, ET, soil moisture and lint yield showed a very good agreement during calibration and validation as indicated by the performance statistics. The model under predicated the ET during peak vegetative growth and development stage except some occasions which was associated with under predicted LAI.