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应用生态学报 ›› 2019, Vol. 30 ›› Issue (8): 2725-2736.doi: 10.13287/j.1001-9332.201908.022

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太阳辐射对稻田甲烷排放的影响

马莉1,2, 娄运生1,2*, 李君2, 李睿2, 张震2   

  1. 1南京信息工程大学气象灾害预报预警与评估协同创新中心, 南京 210044;
    2南京信息工程大学江苏省农业气象重点实验室, 南京 210044
  • 收稿日期:2018-09-15 出版日期:2019-08-15 发布日期:2019-08-15
  • 通讯作者: * E-mail: yunshlou@163.com
  • 作者简介:马莉,女,1993年生,硕士研究生.主要从事农业气象方面的研究.E-mail:mali9311@163.com
  • 基金资助:
    国家自然科学基金项目(41875177,41375159)和中国地质调查局地质调查项目(DD20190305)

Effects of solar radiation on CH4 emission in paddy field

MA Li1,2, LOU Yun-sheng1,2*, LI Jun2, LI Rui2, ZHANG Zhen2   

  1. 1Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China;
    2Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China.

  • Received:2018-09-15 Online:2019-08-15 Published:2019-08-15
  • Contact: * E-mail: yunshlou@163.com

摘要: 太阳辐射减弱是气候变化的主要特征之一,而太阳辐射减弱对稻田甲烷(CH4)排放的影响尚不明确,且缺少高光谱遥感用于估算稻田CH4排放的研究.通过田间模拟试验,研究了不同遮阴强度对稻田CH4排放和水稻冠层光谱特征的影响,并基于冠层高光谱数据估算了CH4排放通量.采用单因子试验设计,遮阴强度设3个水平,即对照(不遮阴,CK)、轻度遮阴(S1,单层遮阴,遮阴率为60%)和重度遮阴(S2,双层遮阴,遮阴率为84%).结果表明:与对照相比,遮阴明显降低了稻田CH4排放,但重度遮阴下CH4排放高于轻度遮阴;近红外波段水稻冠层反射率表现为CK>S2>S1;水稻冠层光谱反射率(699~1349 nm)与CH4排放通量呈极显著正相关,最高相关系数达0.64,6种植被指数与CH4排放通量也呈极显著相关,其中比值植被指数(RVI)与CH4排放通量的相关系数最大,达0.84;建立了以RVI、归一化植被指数(NDVI)和507 nm原始反射率(ρ507)为参数估算CH4排放通量的逐步回归模型,决定系数R2分别为0.86和0.85,利用该模型可为开展区域稻田温室气体排放的遥感监测提供试验依据.

Abstract: Decrease in solar radiation is one of the main components of climate change. Studies aimed at examining the effects of decreased solar radiation on CH4 emission and estimation of CH4 emission based on hyperspectral data in paddy fields are still scarce. A field simulation experiment was conducted to investigate the effects of shading intensity on CH4 emission in a paddy field and rice canopy hyperspectral properties. CH4 emission flux was estimated with rice canopy hyperspectral data. The shading intensities were set at three levels, i.e. control (CK, no shading), light shading (S1, 60% of shading rate), and heavy shading (S2, 84% of shading rate). The results showed that shading significantly reduced CH4 emission. However, CH4 emission under heavy shading (S2) was higher than that under light shading (S1). The reflectance of the near-infrared spectrum on rice canopy from the jointing stage to grain filling stage was in the sequence of CK>S2>S1. The spectral reflectance on rice canopy was significantly and positively correlated with CH4 flux in the near-infrared band (699-1349 nm), with a correlation coefficient of 0.64 (P<0.01). The six vegetation indices were significantly correlated with CH4 flux. The correlation coefficient between Ratio Vegetation Index (RVI) and CH4 flux was the largest, with R2=0.84 (P<0.01). The stepwise regression model with RVI, Normalized Difference Vegetation Index (NDVI), and 507 nm original reflectance (ρ507) parameters was the best one (fitting model R2=0.86, prediction model R2=0.85) for estimating CH4 emission.