A novel approach developed to enhance spatiotemporal accuracy for static chamber observations of carbon fluxes in paddy: A case study of double-site experiments in Southern China

More precise measurements of carbon fluxes (CH 4 and CO 2 ) in paddy fields have been crucial for estimating the global carbon budget, yet they were largely constrained by varying observational methods. Our study employed a carbon emission monitoring experiment at a dual-site rice paddy in southern China, aiming to refine the widely used static chamber method (STCM) through the integration of limited eddy covariance system (ECS) observations and environmental factor regressions. This approach sought to provide more convenient methods and accurate assessments for paddy field management and monitoring practices. The results revealed that STCM tended to overestimate carbon fluxes particularly CH 4 , compared to ECS across different temporal scales. Stepwise regression models using environmental factors demonstrated both simplicity and accuracy in simulating CH 4 and CO 2 , effectively enhancing the temporal resolution of STCM. Our proposed method achieved an index of agreement above 79.54 % for any carbon flux simulation under various treatments, significantly improving the spatiotemporal precision of paddy field CH 4 and CO 2 monitoring and estimations. By reassessing the greenhouse effect in the study area, we found that the corrected emission reduction potential of the basin is 30.3 %. Our novel approach for STCM can exhibit superior scalability, providing robust support for achieving agricultural carbon neutrality goals. • Static chamber method (STCM) overestimates CH 4 and CO 2 flux in paddy across various temporal scales than eddy covariance. • CH 4 or CO 2 flux exhibits a higher temperature sensitivity to soil than to air temperature. • Stepwise regression model of environmental factors performs excellent simulations. • Our methodology improves spatiotemporal accuracy of carbon emissions for STCM.