Simulation of Energy Sorghum under Limited Irrigation Levels Using the EPIC Model Academic Article uri icon


  • © 2018 American Society of Agricultural and Biological Engineers. Energy sorghum is one of the most attractive alternatives for producing energy in many regions of the world because of the high biomass productivity obtained in a short period. However, it faces many challenges, particularly where water resources are limited. Crop simulation models are suitable decision support tools for the assessment of crop water use and biomass production under different spatial and climatic conditions. Calibration of simulation models to local conditions is a necessary procedure to improve model reliability. The objective of this study was to calibrate and evaluate the Environmental Policy Integrated Climate (EPIC) model for the production of energy sorghum under different irrigation levels. The model was then used to simulate crop biomass productivity and crop water use to identify appropriate irrigation strategies. This study was conducted at the Texas A&M AgriLife Research Center in Weslaco, Texas. Simulations were performed to determine the total dry biomass, crop water use, the relationship between crop productivity and crop evapotranspiration (ET c ), and water use efficiency (WUE). Simulated ETc agreed well with estimates from a weather station, except for a few simulation events. The statistical parameters derived from measured versus simulated dry biomass in the calibrated model, which indicated that the model performed well, were R 2 = 0.99 and PBIAS = -5.35%. The calibrated model showed great potential for simulating the total dry biomass. At full irrigation, the difference between measured and simulated total dry biomass was 4.3% in 2013 and 3.0% in 2015. This study showed that energy sorghum requires approximately 600 mm of water to obtain 23 Mg ha -1 of total dry biomass. It also demonstrated that the EPIC model could be used for assessment of crop water use and total biomass under limited irrigation levels, especially in semi-arid regions.

author list (cited authors)

  • Chavez, J. C., Enciso, J., Meki, M. N., Jeong, J., & Singh, V. P.

publication date

  • January 1, 2018 11:11 AM