Researches On Storage And Change Of The Cultivated Land Soil Organic Carbon In County Scale Using GIS

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.