李雨鸿,孙倩倩,李 辑,李 晶,刘 维,李琳琳,陶苏林.东北地区春播期土壤水分预测方法研究[J].干旱地区农业研究,2015,33(6):178~183
东北地区春播期土壤水分预测方法研究
Research on forecasting method for soil moisture during spring sowing period in Northeast Area of China
  
DOI：10.7606/j.issn.1000-7601.2015.06.30
中文关键词:  土壤相对湿度  气象因子  环流因子  预测模型  东北地区
英文关键词:soil relative humidity  meteorological factors  circular factors  forecasting model  Northeast Area of China
基金项目:公益性行业科研专项“东北地区土壤墒情监测预报及其对主要农作物的影响分析”（GYHY201106026）；2012年江苏省普通高校研究生科研创新计划项目(CXZZ12-0503)
作者单位
李雨鸿 辽宁省气象科学研究所， 辽宁 沈阳 110166 
孙倩倩 中国气象局气象影视中心， 北京 100081 
李 辑 辽宁省气象科学研究所， 辽宁 沈阳 110166 
李 晶 辽宁省气象科学研究所， 辽宁 沈阳 110166 
刘 维 国家气象中心， 北京 100081 
李琳琳 辽宁省气象科学研究所， 辽宁 沈阳 110166 
陶苏林 南京信息工程大学应用气象学院， 江苏 南京 210044 
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中文摘要:
      根据东北五个土壤湿度分区春播期土壤相对湿度与气象因子、环流因子相关关系，甄选土壤相对湿度主要影响因子，构建多元线性回归模型以预测4、5月土壤相对湿度。结果表明：(1) 五个分区土壤相对湿度与封冻雨、降水量呈正相关，与透雨日期、气温及日照时数呈负相关，且4月份土壤相对湿度与封冻雨及透雨日期的相关性较5月更显著；(2) 各分区春播期土壤相对湿度与多项环流因子关系较密切，相关系数绝对值大于0.4且通过信度为0.05的显著性检验，并且这些影响因子主要集中在前一年11、12月；(3) 基于关键气象因子和环流指数构建的4、5月土壤相对湿度多元线性回归模型均通过F显著性检验，复相关系数达0.5以上，且模型预测准确率基本在80%以上，精度较高。
英文摘要:
      According to the related relationship between soil relative moisture with climate factors and circular factors in spring sowing period of five soil moisture regions in Northeast Area, selected the major impact factor for soil relative moisture, constructed the multiple linear regression models to predict the soil relative moisture during April and May. The results indicated that: (1) The soil relative moisture with freezing rain and precipitation were shown positive correlation in five regions, while negative correlation with the date of soaking rain, temperature and sunshine hours. Moreover the relativity of soil relative moisture with freezing rain and the date of soaking rain in April were more remarkable than in May. (2) The soil relative moisture in spring sowing period for each region was rather close relation with multiple circular factors, the absolute values of correlation coefficients was more than 0.4 and passed the significant test at 0.05 level, also these impact factors were major concentrated in November and December of the previous year. (3) Based on key climate factors and circular index to construct the multiple linear regression models for the soil relative moisture during April and May were total passed the F test and the multiple correlation coefficients were larger than 0.5, also the forecasting precision of model was basically more than 80% with rather high accurac y.
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