夜间增温对稻田甲烷排放的影响及其高光谱估算

昼夜不对称增温是全球气候变化的主要特征之一,有关夜间增温对稻田甲烷(CH_4)排放影响的报道尚不多见。通过田间模拟试验,研究了被动式夜间增温下水稻田CH_4排放及高光谱的特征,并用高光谱数据对稻田甲烷排放进行定量模拟。田间试验设夜间增温(NW)和对照处理(CK),夜间增温即在整个水稻生育期的夜间(19:00—6:00)用铝箔反射膜覆盖水稻冠层。结果表明,夜间增温显著促进水稻拔节期和抽穗期-灌浆期CH_4排放。水稻冠层近红外光谱反射率表现为,在分蘖期和拔节期时,NWCK;而在抽穗-灌浆期和成熟期时,CKNW。水稻冠层光谱反射率、一阶导数光谱及光谱特征值均与CH_4排放通量显著相关,相关系数最大可达0.8(P0.01),其中以"蓝边面积"(SD_b)构成的二次多项式模型模拟精度和检验精度综合最佳,决定系数R~2分别为0.70和0.72。研究结果对稻田CH_4排放通量遥感监测的可行性提供了理论依据和技术支持。

Methane emission in response to nighttime warming and its hyperspectral estimation in a paddy field

Asymmetric diurnal warming is one of the main features of global climate change, but the effects of nighttime warming on CH₄emission from paddy fields is unclear. A field experiment with rice was conducted at the Station of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing, China, to investigate the effects of passive nighttime warming on CH₄ emission in a paddy field and rice canopy hyperspectral characteristics. CH₄ emission flux was estimated with hyperspectral data. The tested rice was hybrid rice cv. Y Liangyou 3399. The tested paddy soil was classified as a Typic Stagnic Anthrosol. The experiment was designed with two levels of warming, i.e., nighttime warming(NW) and control(CK). NW was created by covering the rice canopy with an aluminum foil reflective film at night(19:00-6:00).CH₄ emission was measured by the closed chamber method at one-week intervals during the rice-growing period. The results showed that NW significantly increased CH₄ emission at the rice jointing and heading-grain filling stages. Compared to CK, NW increased the reflectance of the near-infrared spectrum on the canopy at the tillering and jointing stages, but decreased at the heading-grain filling and maturity stages. Positive correlations were observed in the relationships of CH₄ emission with spectral reflectance and the first derivative and the characteristic value of the spectrum. After comparing correlation coefficients (R²) of the fitting models and prediction models, the quadratic polynomial model by ''Area of Blue Edge'' (SD_b) was found to be the best model(fitting model R²=0.70, prediction model R²=0.72) for estimating CH₄ emission. The results of this study provide a theoretical basis for and demonstrate the feasibility of non-destructively monitoring of CH₄ emission in paddy fields.