Improving the MCWLA agroecosystem model to better simulate methane emissions from paddy rice fields

Abstract

Rice cultivation stands out as a major greenhouse gas source, emitting 10–20% of global CH₄ emissions. How to accurately estimate CH₄ emissions from paddy rice and their mitigation potential has been key concerns. Agroecosystem models have unique advantages in understanding CH₄ processes, simulating CH₄ emissions dynamics, optimizing management practices, and quantifying mitigation potentials. However, current agroecosystem models need to be substantially improved for these purposes. In this study, we develop a comprehensive agroecosystem model, MCWLA-Rice 2.0, to better depict the production, oxidation, and emission processes of CH₄ and improve the simulation of root exudates, the effect of nitrate fertilizer on CH₄ emissions, and the decomposition of external organic carbon. We calibrate and validate the model and demonstrate its performance in simulating the rice cultivation system under different fertilizer and irrigation treatments at seven sites across Asia. Elaborating on both aboveground and belowground carbon-nitrogen coupling processes, MCWLA-Rice 2.0 is a valuable tool for simulating rice productivity and CH₄ emissions under various environments and managements, effectively supporting the development of climate-smart agriculture.