Research On Rice Potential Productivity Model In Vulnerable Ecosystem Of Soil Hilly Region Of South-China

Based on current environmental factors, rice model estimate productivity of crop and help government to make correct decision for agriculture. It has a great significance for agriculture modernization, protecting environment and solvig the problem of food security.The area of red soil hilly region in South-China is broad and it has superiority nature conditions. It is an important production base for rice. It's soil environment has become worse as unreasonable management and shortage of input these years. Under this circumstance, it is not good for food security of our country. In this paper, Taoyuan Agricultural Experimental Station of the Chinese Academy of Sciences is selected as the representative area of red soil hilly region for the study of rice model selecting and testing. The rice model based on mechanism method is selected acoording to the research. In the paper, the relationship among environment factors, management and rice productivity are researched.Combining with Geographical Information System (GIS), we spread and apply the rice model to the area of Dong ting lake. Digital information of factors which affect rice productivity is gathered. It is obtained charts of rice simulating production and fertility index of soil between 2003 year and 2007 year. Analysis the data in time, spatial, and compare the simulating production with the actual yield, reached that high-producing area are in Chang Decity, east of ChangShang city and north east of YueYang city. The reaserch is showed that:(1) Rice model based on mechanism method can simulate the actual rice yields of the area of Dong ting lake. The deviations between actual yield and simulating yield are less than 15%. (2) Amount of precipitation, soil's pH value, content of organic matter and rapidly available phosphorus are the main soil characters that limit the rice productivity. (3) Ecological environment has a great impact on rice productivity, Extreme climatic condition and water loss and soil erosion lead to a low-productivity year.