摘要
本文介绍所建立的基于时段降水量、土壤初始含水量和两次监测时段天数的间隔天数统计法土壤墒情诊断模型的原理和建模方法,并应用7个省23个县87个监测点2012—2014年的数据建模,应用2015年的数据进行了验证。结果表明:间隔天数统计法模型诊断和预测精度高达到90%以上;间隔天数统计法模型诊断和预测合格率高,其原因是增加了间隔天数变量,有效地解决了测定间隔天数不固定的问题;逐日模型法可以实现逐日土壤墒情的预测。初步结论是:间隔天数统计法模型可以单独作为墒情诊断模型使用。
The principle and modeling method of the interval days statistical diagnostic model of soil moisture were introduced. Models were established by the data of 87 monitoring sites in 23 counties from 7 provinces during the period of 2012-2014, and validated by the data of 2015. The results showed that the accuracy of diagnosis and prediction of the interval days statistical di- agnostic model was high, reaching up to 90%. Interval days statistics diagnostic model had a high diagnosis and prediction rate because of the addition of the interval days variable, which effec- tively solved the problem of unfixed interval. The daily time series model could achieve daily pre- diction of soil moisture. In conclusion, the interval days statistical diagnostic model can be used alone as a soil moisture diagnosis model.
出处
《生态学杂志》
CAS
CSCD
北大核心
2017年第12期3365-3371,共7页
Chinese Journal of Ecology
基金
天津市科技支撑计划(15ZCZDNC00700)
“中国农业科学院科技创新工程”(2016-cxgc-hyl)
广西科技开发项目(14125008-2-24)
全国农业技术推广中心节水处项目(2016-hx-hyl-5)资助
关键词
土壤含水量
降水量
时段模型
逐日模型
验证
soil water content
precipitation
time interval model
daily time series model
veri- fication.
