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山西省代表站不同土层逐旬土壤相对湿度预报模型
引用本文:李润春,张秀芝,高俊寿,刘文平,姚彩霞.山西省代表站不同土层逐旬土壤相对湿度预报模型[J].中国农业气象,2009,30(3):354-359.
作者姓名:李润春  张秀芝  高俊寿  刘文平  姚彩霞
作者单位:1. 山西省阳泉市气象局,阳泉,045000
2. 国家气候中心,北京,100081
3. 山西省气候中心,太原,030002
4. 山西省气象台,太原,030002
基金项目:2007年度山西省气象局气象科研一般课题 
摘    要:以改进本地农业气象服务为目的,使用山西省3个代表站的土壤湿度资料和旬气象资料,根据土壤水分平衡方程,从影响土壤湿度变化的因素出发,分析和筛选了预报因子;应用SPSS统计分析软件,用线性回归方法得到代表站不同土层旬相对湿度的预报模型,经对历史资料回代和2007年各土层进行预报检验,除10cm土层外,相对误差都在30%以下;此方法简单易行,对半干旱半湿润气候区雨养田土壤相对湿度的预报具有一定的参考价值。

关 键 词:统计方法  土壤相对湿度  预报

Forecast Model for Soil Relative Moisture of Ten Days in Different Soil Layers in Shanxi Province
LI Run-chun,ZHANG Xiu-zhi,GAO Jun-shou,LIU Wen-ping,YAO Cai-xia.Forecast Model for Soil Relative Moisture of Ten Days in Different Soil Layers in Shanxi Province[J].Chinese Journal of Agrometeorology,2009,30(3):354-359.
Authors:LI Run-chun  ZHANG Xiu-zhi  GAO Jun-shou  LIU Wen-ping  YAO Cai-xia
Institution:LI Run-chun, ZHANG Xiu-zhi, GAO Jun-shou, LIU Wen-ping, YAO Cai-xia (1. Yangquan Meteorological Bureau, Yangquan 045000, Shanxi, China;2. National Climate Center, Beijing 100081 ; 3. Climate Center of Shanxi Meteorological Bureau,Taiyuan 030002; 4. Shanxi Meteorological Observatory, Taiyuan 030002)
Abstract:Based on the meteorological data of ten days and soil moisture data in three representative stations in Shanxi Province, the linear regression prediction equations of ten days for soil relative moisture in the different soil layers were built by using the statistical software SPSS, to improve the local agricultural meteorological services. According to the soil moisture balance equation, the prediction factors were filtered by analyzing the factor affected the soil moisture variability. The forecast model was validated by the historical data and data in 2007 for the different soil layers with the relative error under 30%. It was showed that physical statistics was a simple and easy method to forecast the soil moisture in semi-arid and semi-humid climate zones for the rain-fed farmland.
Keywords:Statistical method  Soil relative moisture  Forecast
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