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Short-rotation woody crops have maintained global prominence as biomass feedstocks for bioenergy, in part due to their fast growth and coppicing ability. However, the water usage efficiency of some woody biomass crops suggests potential adverse hydrological impacts. Monitoring tree water use in large-scale plantations would be very time-consuming and cost-prohibitive because it would typically require the installation and maintenance of sap flux sensors and dataloggers or other instruments. We developed a model to estimate the sap flux of eastern cottonwood (Populus deltoides. Bartr. ex Marsh.)) grown in bioenergy plantations. This model is based on adjusted vapor pressure deficit (VPD) using Structural Thinking and Experiential Learning Laboratory with Animation (STELLA) software (Architect Version 1.8.2), and is validated using the sap flux data collected from a 4-year-old eastern cottonwood biomass production plantation. With R2 values greater than 0.79 and Nash Sutcliffe coefficients greater than 0.69 and p values < 0.001, a strong agreement was obtained between measured and predicted diurnal sap flux patterns and annual sap flux cycles. We further validated the model using eastern cottonwood sap flux data from Aiken, South Carolina, USA with a good agreement between method predictions and field measurements. The model was able to predict a typical diurnal pattern, with sap flux density increasing during the day and decreasing at night for a 5-year-old cottonwood plantation. We found that a 10% increase in VPD due to climate change increased the sap flux of eastern cottonwood by about 5%. Our model also forecasted annual sap flux characteristics of measured cycles that increased in the spring, reached a maximum in the summer, and decreased in the fall. The model developed here can be adapted to estimate sap flux of other trees species in a time- and cost-effective manner. [ABSTRACT FROM AUTHOR]