基于GIS的县域尺度农田土壤有机碳储量与变化研究
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摘要
土壤有机碳库是陆地生态系统的主要组成部分,在碳循环中有重要作用。农田土壤碳库极易受人类活动影响,又与人类生存发展密不可分。本论文基于GIS技术和模型研究方法,选取典型红壤和水稻土区域的湖南省宁乡县为研究对象,开展县域尺度的农田土壤有机碳库研究。研究内容主要包括:采用国际常用的土壤类型法对县域尺度农田土壤有机碳储量进行估算;在前期建模研究工作基础上,以自主研发的有机碳转换模拟预测系统为核心,模拟县域农田土壤有机碳变化。
论文首先根据湖南省宁乡县1986年第二次土壤普查等收集的资料,分析了不同土种的土壤有机碳密度,估算了土壤有机碳储量。在农田表层土壤(0—20cm)各土种土壤有机碳密度中,90%的土地的土壤有机碳密度分布在3.5-5.5 kg/m~2之间,其中有机碳密度为极值的土种面积占农田总面积比例较小。各土种平均碳密度为4.29kg/m~2,基于土壤分类单元估算湖南宁乡县农田表层土壤有机碳储量是5.57×10~9Kg。利用GIS软件,编制宁乡县不同土种土壤有机碳密度分布图,从空间分布上直观显示土种有机碳密度差异。
在已有的点位模型研究基础上,使用面向对象的开发平台Visual Basic 6.0和数据库引擎技术,利用GIS二次开发平台:SuperMap Objects 2003,构建了县域农田土壤有机碳模拟预测系统,拓展了模型的使用范围,实现了县域空间的模拟和预测。模型以宁乡县农田土壤理化数据,气象数据,外源有机碳的输入,主要农作物及其产量为数据源,建立属性数据库,以月为时间步长,对外源投入物和土壤本身进行分组,分别模拟有机碳周转。系统根据预测时间,假设现有土地利用和耕作措施稳定的情况下,预测有机质的变化,界面友好,操作方便,扩展性强。模型应用于对1986年到2004年间在不同施肥条件下的有机质的模拟,模拟值与实测值的相对误差在10%的范围内,并预测了2014年平均土壤有机质含量。
Soil organic carbon (SOC) pool is an important factor in regional carbon cycle because it serves as a reservoir of large amounts of organic carbon. Cultivated soil carbon pools are vulnerable to the impact of human activities, and are inseparable with human survival and development. Based on geographical information system (GIS) and soil organic carbon model, I select the typical red earth and paddy soil for Ningxiang County in Hunan regional to study on the cultivated soil organic carbon pool of county scale. Researches are divided into two parts: Firstly, the soil organic carbon pool (SOCP) is predicted by the popular soil type method. Secondly, based on the pre-modeling research work, and regarding organic carbon decomposition model of agricultural soils as the core, the dynamics of agricultural soils carbon of county scale is simulated and predicted.
According to the 2nd soil survey and other information gathered by the census in 1986, SOCD of the different soil and SOCP in Ningxiang County in Hunan are counted and analyzed. The extreme value of soil organic density in the farmland topsoil(0-20cm) is a smaller proportion of total area, the density of soil between 3.5 to 5.5 kg/m~2 is 90% of total soil, the average density of soil carbon is 4.29 kg/m~2. The estimate of soil organic carbon stocks using the popular soil type method is 5.57×10~9kg. Using GIS software, different kinds of soil organic carbon density of Ningxiang is given ,and it displays the spatial differences of soil carbon density.
Based on the point model verification, I expand the use of the model and established a simulation system of Farmland SOC, realize the modeling and prediction of SOC in the county scale using Object-Oriented platform:Visual Basic 6.0, databases engine technology, and GIS secondary development platform: SuperMap-Objects 2003. Using database consisting of physics and chemistry characters of cultivated soils, meteorological information, the import of organic carbon sources and production of major crops in Ningxiang county, the monthly turnover of organic carbon is simulated, and change in organic matter is predicted. The model is user-friendly, easy to operate, and strong expansion. And it is applied to simulate the soil organic matter under different fertilization from 1986 to 2004. The model has a good performance and all simulations are found within 10% of the comparative errors. At last, the model gives us the average soil organic matter in 2014.
论文首先根据湖南省宁乡县1986年第二次土壤普查等收集的资料,分析了不同土种的土壤有机碳密度,估算了土壤有机碳储量。在农田表层土壤(0—20cm)各土种土壤有机碳密度中,90%的土地的土壤有机碳密度分布在3.5-5.5 kg/m~2之间,其中有机碳密度为极值的土种面积占农田总面积比例较小。各土种平均碳密度为4.29kg/m~2,基于土壤分类单元估算湖南宁乡县农田表层土壤有机碳储量是5.57×10~9Kg。利用GIS软件,编制宁乡县不同土种土壤有机碳密度分布图,从空间分布上直观显示土种有机碳密度差异。
在已有的点位模型研究基础上,使用面向对象的开发平台Visual Basic 6.0和数据库引擎技术,利用GIS二次开发平台:SuperMap Objects 2003,构建了县域农田土壤有机碳模拟预测系统,拓展了模型的使用范围,实现了县域空间的模拟和预测。模型以宁乡县农田土壤理化数据,气象数据,外源有机碳的输入,主要农作物及其产量为数据源,建立属性数据库,以月为时间步长,对外源投入物和土壤本身进行分组,分别模拟有机碳周转。系统根据预测时间,假设现有土地利用和耕作措施稳定的情况下,预测有机质的变化,界面友好,操作方便,扩展性强。模型应用于对1986年到2004年间在不同施肥条件下的有机质的模拟,模拟值与实测值的相对误差在10%的范围内,并预测了2014年平均土壤有机质含量。
Soil organic carbon (SOC) pool is an important factor in regional carbon cycle because it serves as a reservoir of large amounts of organic carbon. Cultivated soil carbon pools are vulnerable to the impact of human activities, and are inseparable with human survival and development. Based on geographical information system (GIS) and soil organic carbon model, I select the typical red earth and paddy soil for Ningxiang County in Hunan regional to study on the cultivated soil organic carbon pool of county scale. Researches are divided into two parts: Firstly, the soil organic carbon pool (SOCP) is predicted by the popular soil type method. Secondly, based on the pre-modeling research work, and regarding organic carbon decomposition model of agricultural soils as the core, the dynamics of agricultural soils carbon of county scale is simulated and predicted.
According to the 2nd soil survey and other information gathered by the census in 1986, SOCD of the different soil and SOCP in Ningxiang County in Hunan are counted and analyzed. The extreme value of soil organic density in the farmland topsoil(0-20cm) is a smaller proportion of total area, the density of soil between 3.5 to 5.5 kg/m~2 is 90% of total soil, the average density of soil carbon is 4.29 kg/m~2. The estimate of soil organic carbon stocks using the popular soil type method is 5.57×10~9kg. Using GIS software, different kinds of soil organic carbon density of Ningxiang is given ,and it displays the spatial differences of soil carbon density.
Based on the point model verification, I expand the use of the model and established a simulation system of Farmland SOC, realize the modeling and prediction of SOC in the county scale using Object-Oriented platform:Visual Basic 6.0, databases engine technology, and GIS secondary development platform: SuperMap-Objects 2003. Using database consisting of physics and chemistry characters of cultivated soils, meteorological information, the import of organic carbon sources and production of major crops in Ningxiang county, the monthly turnover of organic carbon is simulated, and change in organic matter is predicted. The model is user-friendly, easy to operate, and strong expansion. And it is applied to simulate the soil organic matter under different fertilization from 1986 to 2004. The model has a good performance and all simulations are found within 10% of the comparative errors. At last, the model gives us the average soil organic matter in 2014.
引文
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