Optimizing biochar application rate and predicting of climate change impacts on net greenhouse gas emissions in paddy systems using DNDC-BC model

Abstract

The effects of biochar application and controlled irrigation (CI, a water-saving irrigation technique) on greenhouse gas (GHG) emissions, soil organic carbon (SOC), and rice yield from paddy fields under future climate change have not been thoroughly investigated. The purpose of this study was to optimize biochar application rates to minimize net greenhouse gas emissions (NGHGE), sequestered carbon, and increase rice yield. After testing the performance of Denitrification-Decomposition-Biochar-CI (DNDC-BC), based on a two-year field experiment, the biochar application rate was optimized based on the DNDC-BC model and CMIP5 future data after Bayesian Model Averaging. The scenarios under 6 biochar amounts (C0-C50 represent 0 t ha⁻¹ to 50 t ha⁻¹) were simulated in the next 17 years (2024–2040), and the NGHGE of each were also assessed. Under the four future climate scenarios, compared with C0, the average non-CO₂ greenhouse gas emissions of C40 decreased by 48.41 %-62.63 % over the next 17 years, while the average SOC and rice yield increased by 14.58 %-21.02 % and 7.58 %-8.76 %, respectively. 40 t ha⁻¹ is the optimal biochar application rate for CI paddy fields in decreasing NGHGE in the Lake Taihu region of China. The biochar amount has a strong positive correlation with SOC and rice yield. This is the first study to optimize the biochar application for mitigating GHG, sequestrating SOC and boosting rice yield in CI paddy fields under future climate change. This study evaluates GHG, SOC, rice yield, and economic benefits of the rice system at the same time, and can be extended to other systems and regional scales.