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移动统计法土壤墒情诊断模型

发布时间:2018-11-26 19:20
【摘要】:本文介绍了基于土壤初始含水量和时段每日平均降水量所建立的移动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。移动统计法墒情诊断模型分为时段模型和逐日模型。结果表明:时段模型预测的合格率为90%左右,逐日模型预测的合格率为70%左右;时段模型优于逐日模型。移动统计法模型单独作为墒情诊断模型,使用时需要进一步完善,可以在土壤初始含水量分段的基础上应用其他5个独立模型进行尝试。
[Abstract]:In this paper, the principle and modeling method of moving statistical soil moisture diagnostic model based on initial soil moisture content and average daily precipitation in time period are introduced, and the data modeling of 87 monitoring points in 23 counties of 7 provinces from 2012 to 2014 is applied. The data for 2015 were applied to verify. The moisture diagnosis model of moving statistical method is divided into time period model and daily model. The results show that the qualified rate of the model is about 90% and that of the daily model is about 70%, and the model is superior to the daily model. The model of moving statistical method is used as the diagnosis model of soil moisture, which needs to be further improved, and the other five independent models can be used on the basis of the initial soil moisture content segmentation.
【作者单位】: 农业部环境保护科研监测所;北部湾环境演变与资源利用教育部重点实验室(广西师范学院)广西地表过程与智能模拟重点实验室(广西师范学院);
【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
【分类号】:S152.7


本文编号:2359400

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