基于模型和GIS的江苏省农田土壤有机碳动态研究
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摘要
本研究建立在前期建模研究工作基础上，以农田土壤有机碳分解模型为核心，以江苏省农田土壤基本理化特性、基础气象资料、1985-2000年逐年粮食作物产量、常规农作措施为数据源，应用地理信息系统(Geographic Information System，GIS)技术，模拟从1985年到2000年江苏省农田土壤有机碳变化动态，并在此基础上预测不同秸秆还田量下2010年江苏省农田土壤有机碳分布状况。继而，根据模拟和预测研究结果探讨秸秆还田的现实意义。
首先是对模型中外源有机物影响因子子模型的修正。选取19种有机物料，包括植物的根、茎、叶，初始全氮含量范围为4.0-35.2 g／kg，初始木质素为157.7-254.0 g／kg，不同含量值在该范围分布比较均匀，从而保证统计结果的合理性和所建模型在该范围的整体适用性。采用实验室培养实验，定量研究这些有机物料在25℃、400 g／kg含水量(100 g风干土40 g水)条件下的分解特征，探讨有机物料的化学组成与其在土壤中分解动态的定量描述关系。采用多元逐步回归(Multiple Stepwise Regression)的统计方法，建立易分解组分比例与初始全氮和初始木质素含量的定量关系方程：F_w=150+1.496N-0.572L(R~2=0.7990，p＜0.001，n=17)，式中F_w为易分解比例(％)，N为初始氮含量(g／kg)，L为初始木质素含量(g／kg)，易分解组分比例总体与初始全氮含量呈正相关，与初始木质素含量呈负相关。
然后收集整理了铜山、宜兴、丹阳、兴化四个长期培肥试验点的土壤培肥数据和有机质含量动态资料，它们分属徐淮、太湖、宁镇丘陵和里下河四个传统农业区，其种植制度和轮作方式基本代表了江苏省农田土壤利用的整体情况，同时初始有机碳含量有明显的梯度(6.0-13.5 g／kg)，用此数据验证所建模型在全省范围内的整体适用性，同时还用山东陵县的土壤培肥资料进一步验证该模型在土壤有机碳背景值很低(4.2 g／kg)条件下的适用性。这5个点的验证结果表明，农田土壤有机碳分解模型能较好的描述不同背景含量下农田土壤有机碳的动态变化趋势，并且模拟值与实测值十分接近，模拟值基本能反映土壤有机碳的实际含量。111组实测值和模拟值数据的相关分析方程为：Y=0.757X+1.9545(R~2=0.6278，Y为模拟值，X为实测值)，零截距方程为：Y=0.9656x(R~2=0.5784，Y为模拟值，X为实测值)，零截距方程表明模型模拟结果可靠。
最后，在模型验证通过的基础上，我们尝试将模型与GIS技术进行结合，从而快速而直观的展现有机碳动态区域差异。GIS是分析具有地理特征对象的通用技术，模型与GIS的结合，拓展了模型的使用范围，便捷的实现区域模拟和预测，使我们可以从以前只能通过表格了解一个点的现状到现在可以从图(静态和动态)直观的看到一
基于模型和Gls的江苏省农田土壤有机碳动态模拟
个区域甚至更大范围的现状差异和动态演变过程，从而发现变化趋势和规律，提出解
决方案。栅格格式数据可与模型很好的结合，我们以户Jcinfo的Grid数据格式实现模
型和Gls的结合。通过基本的矢量数据修正、矢量属性追加、栅格数据生成、数据格
式转换等数据处理，以A SCn码为交换文件格式，以Visual Basic 6.0为开发工具，实
现全省农田土壤有机碳1 985一2000年动态模拟以及2001一2010年的动态预测。模拟及
预测结果表明，自第二次土壤普查以来，全省77%的农田土壤有机碳含量有所增加。
到2000年，苏北和沿海地区的增加量1 .0一3.09瓜g之间，苏南太湖地区增加量3.5一5.0
g瓜g之间;苏中的江淮平原和宁镇丘陵区略有下降，降低0.5一1 .59瓜g之间。不同桔
秆还田量(常规还田和50%还田)条件下2010年预测情景分析结果表明，全省大部
分地区农田土壤有机碳含量将继续增加，土壤仍然具有较大的固持外源有机碳的能
力.通过增加桔秆还田量，可以增加或维持较高的土壤有机碳含量，这对改善土壤性
状、促进农业可持续发展、增加土壤碳储量，以及减缓大气CO:浓度增加的趋势具有
现实意义。
应用结果证明，模型和GIS的藕合是切实可行的，栅格文件为这种结合提供了很
好的接入点.模型和栅格数据的结合，可以方便的实现区域模拟，直观的展现空间差
异，模型应用得到极大的拓展.
Regarding organic carbon decomposition model of agricultural soils as the core, using database consisting of physics and chemistry characters of agriculture soils, meteorological information, production of crops from 1985 to 2000 and agriculture management in Jiangsu province, combining with Geographic Information System technique, the dynamics from 1985 to 2000 and distribution in 2000 of agricultural soils carbon in Jiangsu province was simulated and predicted. Based on these results, the distribution of agricultural soils carbon 2010 was predicted, and the importance of returning straw to soils was discussed.
At first, the sub-model of external organic matter impact factor was modified. Nineteen residues were sampled from different organs with 13 plants, their initial Total Nitrogen content ranged from 4.0 g/kg to 35.2 g/kg, while initial Lignin content from 157.7 g/kg to 254.0 g/kg and the variation is relatively uniformity. The relation of plants chemical content and their dynamic decomposition were investigated by an incubation experiment with 19 plant residues plus soil under 25 C and water content of 400 g/kg air dried soil. Then quantitative relation of plant nitrogen and lignin content on the residue carbon decomposition was set up by a multiple stepwise regression method. The relation can be well quantitatively described by Fw=l50+1.496N-0.572L(R2=0.7990,p<0.001, n=17). The Y represents decomposition percentage. The N and L represent the initial contents of nitrogen and lignin for a given residue, respectively. The Y could be either the first-order decay rate (B0=3.51 X 10-2, B1=4.61 X 10-4, B2= -1.53 X10
-4, R2= 0.812**, n=19), or the percentage of CO2-C released over the 9-week period (B0=100, B1 =0.974, B2= -0.364, R2= 0.828**, n=19), or the percentage of weight loss over the 23-week period in the field burying experiment (B0=150,B1=1.496, B2= -0.572, R2= 0.799**, n=17). The percentage of easily decomposition has a positive relation with the initial nitrogen contents as a whole and a negative relation with the initial lignin.
Secondly, in order to ensure this model could be applied totally in Jiangsu Province, data on soil fertilizer composting and organic matter contents of test points in Tongshan, Yixing, Danyang, Xinghua were collected. Four samples belong to traditional agricultural area of Xuhuai, Taihu, Ningzhen Hill, Lixia River respectively. The landing system and
farm rotation represent basically common situation utilization of soils in Jiangsu province. In addition, the initial organic carbon had distinct grads. The validation results showed that this model can greatly described the dynamic variation of soil organic matter. Furthermore, the simulative value was close to the real value, which means the simulative value can represent the real situation. Relative equation of 111 groups of simulated value and observed value was Y = 0.757X + 1.9545 (R2 = 0.6278** ), zero intercept equation was Y = 0.9656X (R2 = 0.5784** ) . The results of superficial stimulation of zero intercept equation could completely represent the real results.
At last, based on model validation, we tried to combine model with GIS technique. Before using the technology, we only describe the situation in one period from tables or figures. Now, we can use GIS technology to describe the trends and process intuitionally. Using GRID format file and Visual Basic 6.0, the integration of models and GIS technique is realized. Simulation and prediction results indicated that the soil organic matter content in approximately 77% of the agricultural soils in Jiangsu province has been increased since the 2nd soil survey completed in the early 1980s. Compared with the values in 1985, the soil organic matter content in the 2000 was estimated to increase by 1.0-3.0 g/kg for the regions of northern Jiangsu and the coastal area, and 3.5-5.0 g/kg for the region of Tai lake in the southern Jiangsu. A slight decrease of 0.5-1.5 g/kg was estimated for the central section of Jiangsu and the Nanjing-Zhenjiang hilly area. Model predic
首先是对模型中外源有机物影响因子子模型的修正。选取19种有机物料，包括植物的根、茎、叶，初始全氮含量范围为4.0-35.2 g／kg，初始木质素为157.7-254.0 g／kg，不同含量值在该范围分布比较均匀，从而保证统计结果的合理性和所建模型在该范围的整体适用性。采用实验室培养实验，定量研究这些有机物料在25℃、400 g／kg含水量(100 g风干土40 g水)条件下的分解特征，探讨有机物料的化学组成与其在土壤中分解动态的定量描述关系。采用多元逐步回归(Multiple Stepwise Regression)的统计方法，建立易分解组分比例与初始全氮和初始木质素含量的定量关系方程：F_w=150+1.496N-0.572L(R~2=0.7990，p＜0.001，n=17)，式中F_w为易分解比例(％)，N为初始氮含量(g／kg)，L为初始木质素含量(g／kg)，易分解组分比例总体与初始全氮含量呈正相关，与初始木质素含量呈负相关。
然后收集整理了铜山、宜兴、丹阳、兴化四个长期培肥试验点的土壤培肥数据和有机质含量动态资料，它们分属徐淮、太湖、宁镇丘陵和里下河四个传统农业区，其种植制度和轮作方式基本代表了江苏省农田土壤利用的整体情况，同时初始有机碳含量有明显的梯度(6.0-13.5 g／kg)，用此数据验证所建模型在全省范围内的整体适用性，同时还用山东陵县的土壤培肥资料进一步验证该模型在土壤有机碳背景值很低(4.2 g／kg)条件下的适用性。这5个点的验证结果表明，农田土壤有机碳分解模型能较好的描述不同背景含量下农田土壤有机碳的动态变化趋势，并且模拟值与实测值十分接近，模拟值基本能反映土壤有机碳的实际含量。111组实测值和模拟值数据的相关分析方程为：Y=0.757X+1.9545(R~2=0.6278，Y为模拟值，X为实测值)，零截距方程为：Y=0.9656x(R~2=0.5784，Y为模拟值，X为实测值)，零截距方程表明模型模拟结果可靠。
最后，在模型验证通过的基础上，我们尝试将模型与GIS技术进行结合，从而快速而直观的展现有机碳动态区域差异。GIS是分析具有地理特征对象的通用技术，模型与GIS的结合，拓展了模型的使用范围，便捷的实现区域模拟和预测，使我们可以从以前只能通过表格了解一个点的现状到现在可以从图(静态和动态)直观的看到一
基于模型和Gls的江苏省农田土壤有机碳动态模拟
个区域甚至更大范围的现状差异和动态演变过程，从而发现变化趋势和规律，提出解
决方案。栅格格式数据可与模型很好的结合，我们以户Jcinfo的Grid数据格式实现模
型和Gls的结合。通过基本的矢量数据修正、矢量属性追加、栅格数据生成、数据格
式转换等数据处理，以A SCn码为交换文件格式，以Visual Basic 6.0为开发工具，实
现全省农田土壤有机碳1 985一2000年动态模拟以及2001一2010年的动态预测。模拟及
预测结果表明，自第二次土壤普查以来，全省77%的农田土壤有机碳含量有所增加。
到2000年，苏北和沿海地区的增加量1 .0一3.09瓜g之间，苏南太湖地区增加量3.5一5.0
g瓜g之间;苏中的江淮平原和宁镇丘陵区略有下降，降低0.5一1 .59瓜g之间。不同桔
秆还田量(常规还田和50%还田)条件下2010年预测情景分析结果表明，全省大部
分地区农田土壤有机碳含量将继续增加，土壤仍然具有较大的固持外源有机碳的能
力.通过增加桔秆还田量，可以增加或维持较高的土壤有机碳含量，这对改善土壤性
状、促进农业可持续发展、增加土壤碳储量，以及减缓大气CO:浓度增加的趋势具有
现实意义。
应用结果证明，模型和GIS的藕合是切实可行的，栅格文件为这种结合提供了很
好的接入点.模型和栅格数据的结合，可以方便的实现区域模拟，直观的展现空间差
异，模型应用得到极大的拓展.
Regarding organic carbon decomposition model of agricultural soils as the core, using database consisting of physics and chemistry characters of agriculture soils, meteorological information, production of crops from 1985 to 2000 and agriculture management in Jiangsu province, combining with Geographic Information System technique, the dynamics from 1985 to 2000 and distribution in 2000 of agricultural soils carbon in Jiangsu province was simulated and predicted. Based on these results, the distribution of agricultural soils carbon 2010 was predicted, and the importance of returning straw to soils was discussed.
At first, the sub-model of external organic matter impact factor was modified. Nineteen residues were sampled from different organs with 13 plants, their initial Total Nitrogen content ranged from 4.0 g/kg to 35.2 g/kg, while initial Lignin content from 157.7 g/kg to 254.0 g/kg and the variation is relatively uniformity. The relation of plants chemical content and their dynamic decomposition were investigated by an incubation experiment with 19 plant residues plus soil under 25 C and water content of 400 g/kg air dried soil. Then quantitative relation of plant nitrogen and lignin content on the residue carbon decomposition was set up by a multiple stepwise regression method. The relation can be well quantitatively described by Fw=l50+1.496N-0.572L(R2=0.7990,p<0.001, n=17). The Y represents decomposition percentage. The N and L represent the initial contents of nitrogen and lignin for a given residue, respectively. The Y could be either the first-order decay rate (B0=3.51 X 10-2, B1=4.61 X 10-4, B2= -1.53 X10
-4, R2= 0.812**, n=19), or the percentage of CO2-C released over the 9-week period (B0=100, B1 =0.974, B2= -0.364, R2= 0.828**, n=19), or the percentage of weight loss over the 23-week period in the field burying experiment (B0=150,B1=1.496, B2= -0.572, R2= 0.799**, n=17). The percentage of easily decomposition has a positive relation with the initial nitrogen contents as a whole and a negative relation with the initial lignin.
Secondly, in order to ensure this model could be applied totally in Jiangsu Province, data on soil fertilizer composting and organic matter contents of test points in Tongshan, Yixing, Danyang, Xinghua were collected. Four samples belong to traditional agricultural area of Xuhuai, Taihu, Ningzhen Hill, Lixia River respectively. The landing system and
farm rotation represent basically common situation utilization of soils in Jiangsu province. In addition, the initial organic carbon had distinct grads. The validation results showed that this model can greatly described the dynamic variation of soil organic matter. Furthermore, the simulative value was close to the real value, which means the simulative value can represent the real situation. Relative equation of 111 groups of simulated value and observed value was Y = 0.757X + 1.9545 (R2 = 0.6278** ), zero intercept equation was Y = 0.9656X (R2 = 0.5784** ) . The results of superficial stimulation of zero intercept equation could completely represent the real results.
At last, based on model validation, we tried to combine model with GIS technique. Before using the technology, we only describe the situation in one period from tables or figures. Now, we can use GIS technology to describe the trends and process intuitionally. Using GRID format file and Visual Basic 6.0, the integration of models and GIS technique is realized. Simulation and prediction results indicated that the soil organic matter content in approximately 77% of the agricultural soils in Jiangsu province has been increased since the 2nd soil survey completed in the early 1980s. Compared with the values in 1985, the soil organic matter content in the 2000 was estimated to increase by 1.0-3.0 g/kg for the regions of northern Jiangsu and the coastal area, and 3.5-5.0 g/kg for the region of Tai lake in the southern Jiangsu. A slight decrease of 0.5-1.5 g/kg was estimated for the central section of Jiangsu and the Nanjing-Zhenjiang hilly area. Model predic
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