Abstract
Rice paddies are an important source of the greenhouse gas methane (CH4). Global methane emission estimates are highly uncertain and do not account for effects of interpolation or data resolution errors. This paper determines such scaling effects for the influence of soil properties on calculated CH4 emissions for the island of Java, Indonesia. The effects of different interpolation techniques, variograms and neighbor optimization were tested for soil properties by cross-validation. Interpolated organic carbon values were not significantly different from the original soil samples, in contrast to interpolated soil iron contents. Interpolation of soil properties coupled to a process-based model on CH4 emissions led to a significant change in distribution of calculated CH4 emissions, i.e., the variance decreased. Effects of data resolution were examined by interpolating soil properties to derive data at different data resolutions and then calculating CH4 emissions by applying the process-based model at these resolutions. The soil properties did not differ significantly for different data resolutions, in contrast to calculated CH4 emissions. These scaling effects were caused by the combination of interpolation and a non-linear model. Real scaling effects may even be larger because small-scale variability was not accounted for. Scaling effects, including those caused by small-scale variability, have to be considered to achieve unbiased and less uncertain global CH4 emissions estimates from rice paddies.
Original language | English |
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Pages (from-to) | 5-26 |
Journal | Environmental and Ecological Statistics |
Volume | 9 |
DOIs | |
Publication status | Published - 2002 |
Keywords
- rice
- emission
- methane
- geostatistics