Evaluating regional budgets of methane (CH₄), a potent greenhouse gas and short-lived climate forcer, is an important task for future climate management. This study estimated historical CH₄ emissions from paddy fields in East Asia by using a process-based terrestrial biogeochemical model driven by climate and land-use data. To capture the range of estimation uncertainty, this study used two CH₄ emission schemes, four paddy field maps, and two seasonal inundation methods for a total of 16 simulations. The mean CH₄ emission rate during 2000-2015 was estimated to be 5.7 Tg CH₄ yr^-1, which is similar to statistical inventories and other estimates. However, the large standard deviation (± 3.2 Tg CH₄ yr^-1) among the simulations implies that serious estimation uncertainties remain. Three factors - CH₄ emission scheme, paddy field map, and inundation seasonality - were responsible for the disparity of the estimates. Because of the lack of historical management data, the model simulation did not show a decreasing trend in the agricultural CH₄ emissions. A sensitivity analysis for temperature indicated that a 1-2 °C temperature rise (typical warming in mitigation-oriented scenarios) would substantially enhance CH₄ emissions. However, a sensitivity analysis for water management indicated that a lower water-table depth would largely mitigate the emission increase. Additional studies to improve agricultural datasets and models for better paddy field management are still needed.

中文翻译：

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基于模型的东亚稻田甲烷排放评价

评估甲烷（CH ₄）的区域预算，这是一种强效温室气体和短寿命气候强迫因素，是未来气候管理的一项重要任务。本研究利用气候和土地利用数据驱动的基于过程的陆地生物地球化学模型估算了东亚稻田的历史 CH _{4排放量。}为了捕捉估计不确定性的范围，本研究使用了两种 CH ₄排放方案、四种稻田地图和两种季节性淹没方法，总共进行了 16 次模拟。2000-2015 年平均 CH ₄排放率估计为 5.7 Tg CH ₄ yr ^-1，这类似于统计库存和其他估计。然而，模拟之间的大标准偏差（± 3.2 Tg CH ₄ yr ^-1）意味着仍然存在严重的估计不确定性。三个因素——CH ₄排放方案、稻田地图和洪水季节性——是造成估计差异的原因。由于缺乏历史管理数据，模型模拟并未显示农业 CH ₄排放量呈下降趋势。对温度的敏感性分析表明，温度上升 1-2 °C（以缓解为导向的情景中的典型升温）将显着提高 CH ₄排放。然而，对水管理的敏感性分析表明，较低的地下水位深度将在很大程度上缓解排放增加。仍然需要进一步研究以改进农业数据集和模型，以更好地管理稻田。