农田土壤墒情监测与预报系统研发

为了定量预报农田未来7 d土壤墒情变化特征,提升农业气象服务工作质量与效率,该文旨在研发基于网络化的辽宁省农田土壤墒情监测与预报系统。该系统基于VC＋＋及Fortran程序语言设计,以改进的CERES-MAIZE模型中的土壤水分子模型为基础,通过程序设计及各接口功能的实现,自动调用辽宁省自动土壤水分观测站的监测当日土壤含水量数据和中央气象台预报指导产品,实现数据的网络化获取和业务模型的实时运行,提升土壤墒情模拟的准确性、时效性和便利性。结果表明,预报准确率随预报日期增加而呈现降低的趋势,越临近实际监测日期土壤墒情预报情况与实际情况拟合越好;等级干旱预报准确率最低值为70.1%,最高值为81.9...

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Bibliographic Details
Published in农业工程学报 Vol. 32; no. 18; pp. 140 - 146
Main Author 张晓月 李荣平 焦敏 张琪 王莹 李辑
Format Journal Article
LanguageChinese
Published 辽宁省气象科学研究所,沈阳,110166 2016
Subjects
土壤
墒情
干旱
模型
网络化
预报系统
forecast system
models
预报系统
干旱
drought
网络化
模型
墒情
moisture
soils
土壤
web-based
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ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2016.18.019

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Summary:为了定量预报农田未来7 d土壤墒情变化特征,提升农业气象服务工作质量与效率,该文旨在研发基于网络化的辽宁省农田土壤墒情监测与预报系统。该系统基于VC＋＋及Fortran程序语言设计,以改进的CERES-MAIZE模型中的土壤水分子模型为基础,通过程序设计及各接口功能的实现,自动调用辽宁省自动土壤水分观测站的监测当日土壤含水量数据和中央气象台预报指导产品,实现数据的网络化获取和业务模型的实时运行,提升土壤墒情模拟的准确性、时效性和便利性。结果表明,预报准确率随预报日期增加而呈现降低的趋势,越临近实际监测日期土壤墒情预报情况与实际情况拟合越好;等级干旱预报准确率最低值为70.1%,最高值为81.9%,系统对于辽宁省农田土壤干旱级别的预报具有较高准确率。
Bibliography:11-2047/S
Zhang Xiaoyue, Li Rongping, Jiao Min, Zhang Qi, wang Ying, Li Ji （Liaoning Institute of Meteorological Science, Shenyang 110166, China）
A system was designed for monitoring current soil moisture and predicting soil moisture changes in the next 1-7 days in Liaoning province. In this system, data of soil volumetric water content from 54 automatic observation stations and weather forecast data from Central Meteorological Observatory in Liaoning were used. The soil moisture data of 8 soil layers was included, and they were different among different stations. The parameters of stations like longitude, latitude, altitude, etc were obtained from the observation stations. The soil parameters like field capacity, soil bulk density, wilting humidity were obtained by measuring soil samples when the stations were established. The next 7 days weather forecast data from the National Meteorological Center of CMA included daily maximum temperature, minimum temperature, precipitation, and cloudiness. A regression mode
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2016.18.019