太湖地区小麦生育期麦田土壤铵态氮和硝态氮含量的模拟与预测

[目的]以T-FACE(temperature-free air carbon dioxide enrichment)模拟的气候情景下的田间实测数据为参照,对DNDC模型在太湖地区的适用性及拟合效果进行分析,并预测农田土壤中无机氮素的变化趋势.[方法]基于太湖地区稻麦轮作体系的T-FACE田间试验,采用DNDC模型研究了温度升高和CO2含量升高对土壤中硝态氮和铵态氮含量变化的影响.[结果]DNDC模型对试验区耕作层土壤中硝态氮和铵态氮含量的模拟值与田间实测值较为吻合,相关系数分别为0.942 1(P<0.01)和0.763 6(P<0.05),具有较高的可信度.年降水量和氮肥使用量的敏感性指数较大,分别为-2.282、0.692(铵态氮)和-3.417、0.433(硝态氮).[结论]试验区耕作层土壤内无机氮素含量受气候因子的影响较大,并存在明显的季节性差异.模拟结果在小麦生长季后期与实测值较接近;在生长季前期和施肥后以及CO2含量和温度升高处理后较实测值偏高.降水量和施肥量是影响无机态氮含量的关键因素,年平均温度、pH值也有一定影响.DNDC模型对其他参数的敏感性不高.
[Objectives]Based on the T-FACE(temperature-free air carbon dioxide enrichment)platform, the inorganic nitrogen content in soils was measured and used as a reliable standard to the simulated values by DNDC model in order to verify the DNDC model fitting degree in Tai Lake area under climate change condition and to predict the variation tendency of inorganic nitrogen. [Methods]The NO3--N and NH4+-N contents were measured and simulated by DNDC model in order to probe the influences of rising CO2 concentration and temperature. The T-FACE technique was used to enrich CO2 concentration in the open air in circular plots. Infrared equipments were used within T(temperature elevated)and CT(CO2 concentration and temperature elevated)circles to ensure the temperature being 2 ℃ higher than ambient. Air blowers and infrared equipments were installed in the non-CO2 enriched arrays to ensure no indirect microclimate changes confounded the effects of treatments. A sensitivity analysis was carried out for all parameters selected. The parameters that showed a strong deviation across the selected input parameters range were sensitive. In contrast, parameters that were uniformly distributed were considered less sensitive. Then the most sensitive parameters would be confirmed. The main parameters in this study were mean air temperature, CO2 concentration, soil pH, soil organic carbon(SOC), and N applicating amount. The base values were set as the field situation. [Results]Both of annual precipitation and N applicating amount had substantial influence on N contents. The sensitivity indices were -2.282, 0.692 for NH4+-N and -3.417, 0.433 for NO3--N respectively. Simulated values fitted the tested values well during the wheat growth period. The significant correlation coefficients were 0.942 1(P<0.01)and 0.763 6(P<0.05)for NO3--N and NH4+-N respectively, which demonstrated that DNDC model can forecast inorganic nitrogen contents with high credibility under simulated climate change conditions. [Conclusions]The inorganic nitrogen contents in plough layer soil showed