Location: Water Quality and Ecology ResearchTitle: Comparing eddy covariance-based cotton evapotranspiration with CSM-CROPGRO and APSIM-OzCot simulations in Mississippi
|ANAPALLI, S - US Department Of Agriculture (USDA)|
Submitted to: Water
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/6/2022
Publication Date: 12/9/2022
Citation: Chatterjee, A., Anapalli, S.S. 2022. Comparing eddy covariance-based cotton evapotranspiration with CSM-CROPGRO and APSIM-OzCot simulations in Mississippi. Water. 14(24):4022. https://doi.org/10.3390/w14244022.
Interpretive Summary: Crop irrigation contributes to the success of Mississippi Delta’s agricultural productivity. However, with declining groundwater levels, it is critical for farmers to optimize their crop water use efficiency during irrigation events. Using field experimental data and measured weather parameters from recent years, computer modeling can help predict how crops will respond to weather conditions in the future. Two specific crop models were used, and their results reasonably estimated cotton yields when compared to field-validated data. However, the models need improvement in certain areas before further applications on crop water use efficiency can be made in the Mississippi Delta.
Technical Abstract: Optimizing irrigation water use efficiency (WUE) is critical to reduce the dependency of irrigated cotton (Gossypium spp.) production on depleting aquifers. Cropping system models can integrate and synthesize data collected through experiments in the past and simulate management changes for enhancing WUE in agriculture. This study evaluated the simulation of cotton growth and evapotranspiration (ET) in a grower’s field using the CSM-CROPGRO -cotton module within the Decision Support System for Agrotechnology Transfer (DSSAT) and APSIM (Agricultural Production Systems simulator)-OzCot during 2017-18 growing seasons. Crop ET was quantified using the eddy covariance (EC) method. Data collected in 2017 was used in calibrating the models and in 2018 validating. Over two cropping seasons, the simulated seedling emergence, flowering, and maturity dates were less than a week for both models. Simulated leaf area index (LAI) varied from measured with the relative root mean squared errors (RRMSE) ranging between 20.6% to 38.7%. Daily ET deviated from EC estimates with root mean square errors (RMSEs) of 1.90 mm and 2.03 mm (RRMSEs of 63.1% and 54.8%) for the DSSAT and 1.95 mm and 2.17 mm (RRMSEs of 64.7% and 58.8%) for APSIM, during 2017 and 2018, respectively. Model performance varied with growing seasons, indicating improving ET simulation processes and long-term calibrations and validations are necessary for adapting the models for decision support in optimizing WUE in cotton cropping systems.