Monitoring of heavy metal stress in crops is vital for food security and agricultural production management. Traditional remote sensing methods focus on the stress-induced changes to the aerial organs of plants, whereas roots are considered to be more directly and severely stressed. In this study, the dry weight of rice roots (WRT) was used as an indicator for monitoring cadmium (Cd) stress levels in rice tissues. The World Food Study (WOFOST) model is a widely used analysis tool for describing the fundamental processes of crop growth, and has been tested for similar applications. We used this model to incorporate a Cd stress factor (fCd), allowing us to simulate the WRT values more accurately.
Then, an optimized method of assimilating remotely sensed leaf area index (LAI) into the modified WOFOST model was used to optimize the simulation process and obtain the optimum value of fCd. Thus, the dynamic simulation of WRT under Cd stress was adjusted. Based on the WRT values of two sample plots with different soil Cd concentrations, the ratio between them (WRTStress/WRTSafe) was calculated subsequently. The variation in the ratio curve generally reflected the stress mechanism in time scale, indicating that the dynamic simulation of WRT was reliable. This study suggests that the method of assimilating remote sensing data into the crop growth model is applicable for simulating crop growth under Cd stress on spatial-time scale, providing a reference for dynamically monitoring heavy metal contamination in rice tissues.