Publications by authors named "Zhuangji Wang"
Article Synopsis
- - GOSSYM is a detailed cotton crop simulation model that recently enhanced its below-ground process simulations by upgrading to a more advanced 2D soil model called 2DSOIL, focusing on daily water movement.
- - The model's photosynthesis and transpiration calculations were improved by implementing the Farquhar biochemical model and the Ball-Berry leaf energy balance model, leading to better accuracy in predictions.
- - The modifications resulted in a significant enhancement in predicting net photosynthesis and transpiration, as well as a 6.0% improvement in yield predictions, making the updated GOSSYM more effective at modeling cotton crop growth.
Extreme climate events including heat waves and droughts are projected to become more frequent under future climate change conditions. However, the mechanisms between soybean yields and climate factors, specifically involving variable rainfall and high heat episodes, are still unclear, particularly with respect to spatial trends in the United States (US) Midwest. A recently modified version of the model GLYCIM was used to evaluate rainfed soybean production across 12 states at a 10 km spatial resolution for three time periods (2011-2020, 2051-2060, 2091-2099) under Representative Concentration Pathway (RCP) scenarios 4.
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