| 基于历史产量丰歉影响指数的黑龙江省水稻产量动态预报 |
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| 引用本文： | 杜春英,李帅,王晾晾,朱海霞,王秋京,宫丽娟,王萍.基于历史产量丰歉影响指数的黑龙江省水稻产量动态预报[J].中国农业气象,2010,31(3):427-430. |
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| 作者姓名： | 杜春英 李帅 王晾晾 朱海霞 王秋京 宫丽娟 王萍 |
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| 作者单位： | 黑龙江省气象科学研究所,哈尔滨,150030 |
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| 基金项目： | 国家自然科学基金项目，中国气象局业务建设项目，黑龙江省气象局重点项目，中国气象局气候变化专项 |
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| 摘 要： | 水稻是黑龙江省主栽作物之一,开展水稻产量动态预报对黑龙江省粮食生产具有重要意义。利用黑龙江省水稻主产区产量资料、发育期资料、日最高气温、日最低气温、日降水量和日照时数等资料,根据历史年水稻产量丰歉气象影响指数,建立黑龙江省水稻产量丰歉趋势动态预报模型。另外,采用相关分析的方法,确定影响产量的关键气象因子,建立相应的产量预报模型,对产量丰歉趋势动态预报模型进行修订。通过对1997-2006年水稻产量进行动态预报,结果表明,5月31日、6月30日、7月31日和8月31日预报的水稻产量增减趋势的预报正确率平均为90%、70%、90%和80%,产量预报准确率为84%、90%、94%和93%,预报准确率较高,能够满足业务服务的需要。
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| 关 键 词： | 水稻 产量丰歉趋势动态预报 关键气象因子 产量预报 |
Dynamic Prediction Method for Rice Yield Based on Influence Index for Bumper or Poor Harvest from Historic Yield in Heilongjiang Province |
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| DU Chun-ying,LI Shuai,WANG Liang-liang,ZHU Hai-xia,WANG Qiu-jing,GONG LI-juan,WANG Ping.Dynamic Prediction Method for Rice Yield Based on Influence Index for Bumper or Poor Harvest from Historic Yield in Heilongjiang Province[J].Chinese Journal of Agrometeorology,2010,31(3):427-430. |
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| Authors: | DU Chun-ying LI Shuai WANG Liang-liang ZHU Hai-xia WANG Qiu-jing GONG LI-juan WANG Ping |
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| Institution: | (Heilongjiang Institute of Meteorological Science,Harbin 150030,China) |
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| Abstract: | Rice is one of the most important crops in Heilongjiang province.It is significant to study rice yield prediction method for food production in this region.Based on historic meteorological influence index for bumper or poor harvest of rice,a dynamic prediction model was established for region-specific rice yield,by using the data of rape yield,development stage,daily maximum and minimum temperature,daily precipitation and daily sunshine duration from individual main producing region.The key meteorological factors,which affected the rice yield,were determined by using correlation analysis method,and the corresponding yield prediction model was established.The dynamic prediction model for the trend of bumper or poor harvest was revised.Rice yield was predicted dynamically with the model from 1997 to 2006,which showed that the average accuracy of the increase or decrease trend for rice yield was 90%,70%,90% and 80% for May 31,June 30,July 31 and August 31 respectively.The dynamic prediction model realized a successive dynamic quantitative prediction of rice. |
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| Keywords: | Rice Dynamic prediction for the trend of bumper or poor harvest Key meteorological factors Yield prediction |
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