Accurate quantification of CO<sub>2</sub> fluxes in China’s agricultural ecosystems is frequently hindered by the high spatiotemporal heterogeneity of crop types and phenology, which standard modeling frameworks often oversimplify. This study develops a crop-specific WRF-VPRM framework specifically designed for China’s complex agricultural landscape by replacing the generic cropland category with three distinct modules for rice, wheat, and maize. The primary innovation lies in the integration of high-resolution daily crop distribution data and dynamic phenological information, allowing for the optimization of core VPRM parameters to reflect crop-specific photosynthetic pathways and growing seasons. Simulation results for central and eastern China reveal a national gross ecosystem exchange (GEE) and net ecosystem exchange (NEE) of 1084.7 and 779.2 TgC yr<sup>-1</sup>, respectively, with maize and rice jointly contributing over 80 % of total carbon uptake. The model’s reliability is underscored by strong correlations between simulated NEE and provincial grain yields, alongside high consistency with OCO-2 satellite XCO<sub>2</sub> retrievals. This refined, online-coupled system provides a more granular perspective on China’s agricultural carbon budget and offers a robust modeling tool for evaluating the feedback between crop-specific carbon dynamics and regional climate change.