Improving photosynthate allocation dynamic simulations of crops under water stress conditions
- 1Institute of Atmospheric Physics (Beijing, China)
Abstract
Accurately simulating crop photosynthate allocation under water stress is critical for predicting both food security and ecosystem carbon inputs. Current crop models often rely on static or growth-stage-fixed allocation coefficients, which limits their ability to capture the physiological plasticity of crops responding to fluctuating environmental conditions. This study develops a water-driven, stage-dependent carbon allocation scheme within the Agro-C model to better represent crop responses to soil moisture variability. The scheme dynamically adjusts photosynthate allocation coefficients for roots (PR) and leaves (PL), integrates the yellow-to-green leaf ratio (YGR), and incorporates a water stress-induced leaf senescence module. By coupling carbon allocation to both soil moisture and crop development, the approach improves the representation of physiologically regulated allocation processes and enhances the realism of crop simulations. Model evaluation using extensive observation datasets for maize and wheat demonstrates substantial improvements in simulation accuracy, with R ² values reaching 0.77–0.95 for aboveground biomass (AGB) and 0.62–0.83 for belowground biomass (BGB). These results underscore the importance of dynamically representing carbon allocation under water stress and offer an improved framework for simulating carbon–water interactions in agroecosystems.
Versions
Related
- Improving snow simulations through improved representations of vegetation conditions: insights from high resolution simulations over California
- Improving low-cost NO₂ sensor reliability under real-world air quality conditions by calibrating distributions instead of data points
- A cost-effective data assimilation system for improving ROMS simulations in the Southwest Atlantic
- Improved permafrost soil representation in a dynamic global vegetation model enhances simulations of carbon dynamics and vegetation structure in boreal forests of Northeast China
- Dynamic response and energy dissipation-transfer characteristics of coal subjected to impact loading under coupled thermo-gas-stress conditions
BibTeX
@article{xu2026improving,
title = {{Improving photosynthate allocation dynamic simulations of crops under water stress conditions}},
author = {Wei Xu and Wen Zhang and Yongqiang Yu and Qing Zhang},
journal = {Geoscientific Model Development},
year = {2026},
month = oct,
doi = {10.5194/gmd-19-9973-2026},
url = {https://gmd.copernicus.org/articles/19/9973/2026/},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Improving photosynthate allocation dynamic simulations of crops under water stress conditions
AU - Wei Xu
AU - Wen Zhang
AU - Yongqiang Yu
AU - Qing Zhang
PY - 2026
DA - 2026/10/19
JO - Geoscientific Model Development
DO - 10.5194/gmd-19-9973-2026
UR - https://gmd.copernicus.org/articles/19/9973/2026/
AB - Accurately simulating crop photosynthate allocation under water stress is critical for predicting both food security and ecosystem carbon inputs. Current crop models often rely on static or growth-stage-fixed allocation coefficients, which limits their ability to capture the physiological plasticity of crops responding to fluctuating environmental conditions. This study develops a water-driven, stage-dependent carbon allocation scheme within the Agro-C model to better represent crop responses to soil moisture variability. The scheme dynamically adjusts photosynthate allocation coefficients for roots (PR) and leaves (PL), integrates the yellow-to-green leaf ratio (YGR), and incorporates a water stress-induced leaf senescence module. By coupling carbon allocation to both soil moisture and crop development, the approach improves the representation of physiologically regulated allocation processes and enhances the realism of crop simulations. Model evaluation using extensive observation datasets for maize and wheat demonstrates substantial improvements in simulation accuracy, with R ² values reaching 0.77–0.95 for aboveground biomass (AGB) and 0.62–0.83 for belowground biomass (BGB). These results underscore the importance of dynamically representing carbon allocation under water stress and offer an improved framework for simulating carbon–water interactions in agroecosystems.
SN - 1991-9603
ER -