DNDC模型评估苜蓿绿肥对水稻产量和温室气体排放的影响

DNDC(denitrifiction-decompostion)模型是以生物地球化学进程为基础模拟碳氮循环的模型,被广泛用来预测稻田温室气体的排放,但利用DNDC模型研究苜蓿绿肥对稻田生态系统的相关研究尚未见报道。因此,本研究结合两种绿肥在上海地区的使用,模拟了4个不同处理:对照(未施氮肥和绿肥)、氮肥(200 kg/hm²)、紫花苜蓿绿肥(3000 kg DM/hm²)+氮肥和蚕豆绿肥(3000 kg DM/hm²)+氮肥,研究苜蓿绿肥对水稻产量和稻田温室气体排放的影响,同时,对DNDC模型进行本地化修正,建立适宜我国长江中下游地区绿肥-水稻轮作生态系统的DNDC模型,结果表明,与对照相比,苜蓿、蚕豆和氮肥处理下的水稻产量分别提高了41.85%,29.81%和25.36%;蚕豆绿肥处理下的CH₄排放量高于苜蓿绿肥处理,温室气体的排放强度在苜蓿绿肥处理下未显著提高。通过对DNDC模型多个参数的调整和模拟,DNDC模型对水稻产量和CH₄排放的模拟值与实测值十分接近,其中,水稻产量实测值和模拟值的决定系数R²为0.89,相对平均误差RMD为-0.8%。大气温度、大气CO₂浓度、土壤有机碳和土壤粘粒对稻田CH₄和N₂O排放十分敏感,其中,大气温度、CO₂浓度和土壤有机碳与CH₄和N₂O的排放强度呈显著的正相关关系,而土壤粘粒与CH₄排放呈显著的负相关关系,本研究结果说明本地化改进的DNDC模型能够准确模拟紫花苜蓿绿肥对水稻产量和稻田温室气体排放的作用效果。

Effects of alfalfa green manure on rice production and greenhouse gas emissions based on a DNDC model simulation

The denitrification and decomposition (DNDC) model simulates carbon and nitrogen cycles on the basis of biogeochemical processes, and it has been widely used to simulate greenhouse gas emissions in rice (Oryza sativa) paddy fields. However, few studies have used the DNDC model to simulate the effects of green manure on paddy fields in southern China. In this study, we applied four management scenarios, including a control (no N fertilizer, no green manure), N fertilizer (200 kg/ha), alfalfa (Medicago sativa)+N (3000 kg DM/ha+200 kg N/ha), and broad bean (Vicia faba)+N (3000 kg DM/ha+200 kg N/ha), to investigate the effects of green manure on rice production and greenhouse gas emissions. The overall aim of the study was to establish the relationships between green manures and production and greenhouse gas emissions by using the DNDC model. The results showed that the average grain yields in the two years were 41.85%, 29.81%, and 25.36% higher in the alfalfa+N, broad bean+N, and N fertilizer treatments, respectively, than in the control. The most pronounced increase in CH₄ emissions was in the broad bean+N treatment, which had a high C/N. The greenhouse gas intensity (GHGI) was not significantly different between the alfalfa+N, control, and N-fertilizer scenarios. Through adjusting the cropping parameters in the DNDC model, the simulated values and observed values for grain yield were quite similar, and the R² value between them in a correlation analysis was 0.89 (relative mean deviation, -0.8%). Air temperature, CO₂ concentration, soil organic carbon, and the soil clay fraction were all sensitive to CH₄ and N₂O emissions. Temperature, CO₂ concentration, and soil organic carbon were all positively related to CH₄ and N₂O emissions, while the soil clay fraction was negatively related to CH₄ emissions. These results indicated that the localized DNDC model could accurately simulate the effects of alfalfa green manure on rice grain yield and greenhouse gas emissions.