Reducing methane (CH) emissions is increasingly recognized as an urgent greenhouse gas mitigation priority for avoiding ecosystem ‘tipping points’ that will accelerate global warming. Agricultural systems, namely ruminant livestock and rice cultivation are dominant sources of CH emissions. Efforts to reduce methane from rice typically focus on water management strategies that implicitly assume that irrigated rice systems are consistently flooded and that farmers exert a high level of control over the field water balance. In India most rice is cultivated during the monsoon season and hydrologic variability is common, particularly in the Eastern Gangetic Plains (EGP) where high but variable rainfall, shallow groundwater, and subtle differences in topography interact to create complex mosaics of field water conditions. Here, we characterize the hydrologic variability of monsoon season rice fields ( = 207) in the Indian EGP (‘Eastern India’) across two contrasting climate years (2021, 2022) and use the eitrification eomposition (DNDC) model to estimate GHG emissions for the observed hydrologic conditions. Five distinct clusters of field hydrology patterns were evident in each year, but cluster characteristics were not stable across years. In 2021, average GHG emissions (8.14 mt CO-eq ha) were twice as high as in 2022 (3.81 mt CO-eq ha). Importantly, intra-annual variability between fields was also high, underlining the need to characterize representative emission distributions across the landscape and across seasons to appropriately target GHG mitigation strategies and generate accurate baseline values. Simulation results were also analyzed to identify main drivers of emissions, with readily identified factors such as flooding period and hydrologic interactions with crop residues and nitrogen management practices emerging as important. These insights provide a foundation for understanding landscape variability in GHG emissions from rice in Eastern India and suggest priorities for mitigation that honor the hydrologic complexity of the region.

中文翻译：

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水文变化控制着印度东部水稻种植系统的温室气体排放


减少甲烷（CH）排放越来越被认为是缓解温室气体排放的紧迫优先事项，以避免生态系统“临界点”，从而加速全球变暖。农业系统，即反刍牲畜和水稻种植是甲烷排放的主要来源。减少水稻甲烷排放的努力通常集中在水管理策略上，这些策略隐含地假设灌溉水稻系统持续被洪水淹没，并且农民对田间水平衡进行高度控制。在印度，大多数水稻是在季风季节种植的，水文变化很常见，特别是在东部恒河平原 (EGP)，这里降雨量高但变化无常、地下水浅层和地形的微妙差异相互作用，形成了田间水条件的复杂镶嵌。在这里，我们描述了印度 EGP（“印度东部”）季风季节稻田 (= 207) 在两个对比气候年份（2021 年、2022 年）的水文变化，并使用电化合成 (DNDC) 模型来估算观测到的水文条件。每年都有五个明显的实地水文模式集群，但集群特征在不同年份之间并不稳定。 2021 年，平均温室气体排放量（8.14 吨二氧化碳当量公顷）是 2022 年（3.81 吨二氧化碳当量公顷）的两倍。重要的是，田地之间的年内变异性也很高，这突显了需要描述整个景观和跨季节的代表性排放分布特征，以适当地确定温室气体减排战略并生成准确的基线值。 还对模拟结果进行了分析，以确定排放的主要驱动因素，其中容易识别的因素，例如洪水期和与作物残留物的水文相互作用以及氮管理实践变得越来越重要。这些见解为了解印度东部水稻温室气体排放的景观变化奠定了基础，并提出了尊重该地区水文复杂性的缓解优先事项。