Eco-balance analysis of six agricultural land uses in the Ikushunbetsu watershed [Japan]

This study quantified and evaluated the greenhouse gas emissions of farmland soils at a watershed scale using parameters available at a regional scale. The estimation was based on field monitoring data in the Ikushunbetsu River Watershed, Hokkaido, Japan. Simple regression models were created for carbon dioxide, nitrous oxide and methane emissions associated with six major agricultural land uses, and forest as an alternative land use to farmland. An eco-balance method involves conducting an analysis on the basis of farmland surplus nitrogen (N) and global warming potential (GWP). Uncertainties associating the estimations were estimated using Monte Carlo simulation. The eco-balance is the analysis of the relationship between production and environmental load. In this study, production and environmental load were compared by changing each of the land use combinations by 10%. Farmland surplus N was lowest for soybean with 8.2 kg N/ha/year, followed by paddy rice. The highest value was recorded for vegetables with 99.8 kg N/ha/year. The weighted mean of total farmland based on the land use proportion was 44+-33.8 kg N/ha/year. The calculated GWP was 7.3 Mg CO2 eq/ha/year for paddy rice and 0.1 to 6.8 Mg CO2 eq/ha/year for upland crops. The weighted mean of the total farmland area was 4.0+-3.4 Mg CO2 eq/ha/year. The eco-balance analysis showed that there were 59 combinations out of 8008 combinations able to reduce GWP more than 6%, but less than 7%, than the value in 2005. Among them, in 30 combinations, farmland surplus N became less than the value in 2005; production was reduced compared with the value in 2005 in 27 combinations. Soybean occupied 20-80% in the seven combinations where production was increased compared with 2005, while keeping farmland surplus N below the value in 2005. The estimation of greenhouse gases in this study exhibited high uncertainty because of variability in management and errors in evaluation procedures. Quantification of the data variability is set at maximum, which comprises the measured values in this area. Based on the quantification of the uncertainty, more efficient quantification methods can be established to clarify mitigation potential. This type of quantification and comparison between production and emission enables decision makers to set some threshold values that allow a compromise between production and environmental load.