Challenges in mechanistic modeling of methane production and release in agricultural soils: Perspective on limitations and opportunities

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Accurate prediction of methane (CH4) emissions from agricultural lands, particularly rice paddies, is essential for effective climate change mitigation. Although current models capture broad emission trends, they often struggle to represent the complex interactions among the processes that govern CH4 production, oxidation, transport, and release. These challenges arise from multiple interconnected factors, including dynamic microbial communities with diverse metabolic pathways; fluctuating substrate availability shaped by rice management practices; and several transport mechanisms, such as diffusion, ebullition, and plant-mediated pathways, that are difficult to parameterize and scale. This review examines four interconnected dimensions of CH4 modeling: (a) how major CH4-related processes are conceptualized in existing models; (b) the quantitative performance of widely used CH4 models in rice systems; (c) the key limitations and challenges that constrain process-based CH4 simulations; and (d) opportunities for model improvement. Across these dimensions, the review provides an in-depth synthesis of the key biogeochemical and rice crop processes, including redox dynamics, substrate supply, microbial activity, CH4 production and oxidation, transport mechanisms, and rice plant–root–soil interactions. We argue that discrepancies between modeled and observed CH4 emissions arise not only from model assumptions and structural limitations but also from the inherent complexity of the system and limited data available for model development and evaluation. To enhance predictive accuracy, we highlight the need for improved representation of microbial processes, soil biogeochemistry, plant–soil interactions, and scaling approaches. Overall, this review provides an integrated perspective to guide the development of more advanced CH4 modeling tools for rice agricultural systems.