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机构地区:[1]广西壮族自治区气象减灾研究所,南宁530022 [2]广西壮族自治区气候中心,南宁530022
出 处:《应用气象学报》2007年第2期219-224,共6页Journal of Applied Meteorological Science
基 金:广西壮族自治区气象局项目"巴西旱稻的农业气象问题研究";广西壮族自治区科技厅项目(桂科攻0428008-5H)共同资助
摘 要:根据巴西陆稻IAPAR-9生长发育对气候条件的要求,结合其在广西的多年引种试验结果,分析确定了影响广西种植巴西陆稻的关键气候因子和气候区划指标,采用GIS技术对区划指标进行小网格推算,得出广西不同地理背景下l km×l km网格点上的有关气候要素值,通过GIS的空间分析和多层复合方法,对广西种植巴西陆稻进行气候区划,并对区划结果评述和建议,为广西发展巴西陆稻生产进行合理布局提供科学依据。Since the successful cultivation of the Brazilian Upland Rice (IAPAR-9) in Guangxi, it is decided to be the first choice to widely promote the farming at present, because of its characteristics of wide adaptation, strong resistance to virus and adversity, high yield and high rice quality. In order to reasonably use the climate resources, to get high and steady yield and popularize the Brazilian Upland Rice, and to avoid losing because of blindfold development in unfit region, it is necessary to study on the zoning of fitting region for Brazilian Upland Rice planting in Guangxi by using GIS technology and small grid calculating method of the climate resources, which will provide scientific basis on reasonable distribution of developing Brazilian Upland Rice in Guangxi. According to the request for climate conditions of Brazilian Upland Rice during its growth and development, considering the several years experimental results of cultivation in Guangxi, it is analyzed and the key climate factor and the climatic zoning index which have effects on the growth of Brazilian Upland Rice in Guangxi are determined. Using the climatic data from 1961 to 2000 and geographical information data of 86 weather stations in Guangxi, space calculating models for the zoning index are founded by the regress method of mathematical statistic. In the model, the geographical factors including the longitude, latitude and height above sea level are independent variables and the climatic zoning index is dependent variable. Based on the GIS technology, and the use of the basic Guangxi geographic data on the scale of 1 to 250000, calculation of small gridding and correction of error are operated for those zoning index. The actual distribution of the climatic zoning index is worked out on a small grid of 1 km×1 km, which gives different values under different geographical conditions. Using the function of spatial analyses and multi-overlapping method of GIS and according to the zoning index on all kinds of the dividing grades in clima
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