Effects of solar radiation on CH4 emission in paddy field

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.