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基于东北区吉林省监测数据的土壤墒情综合诊断模型验证

米长虹1,王铄今2,侯显达2,侯彦林1,2*,刘书田1,2,郑宏艳1,黄治平1,丁健1#br#   

  1. (1农业部环境保护科研监测所, 天津 300191; 2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), 南宁 530001)
  • 出版日期:2017-12-10 发布日期:2017-12-10

Verification of integrated diagnostic model of soil moisture based on the monitoring data in Jilin Province.

MI Chang-hong1, WANG Shuo-jin2, HOU Xian-da2, HOU Yan-lin1,2*, LIU Shu-tian1,2, ZHENG Hong-yan1, HUANG Zhi-ping1, DING Jian1#br#   

  1. (1Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China; 2Key Laboratory of Environment Change and Resources Use in Beibu Gulf (Guangxi Teachers Education University); Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation (Guangxi Teachers Education University), Nanning 530001, China).
  • Online:2017-12-10 Published:2017-12-10

摘要: 综合诊断模型是土壤墒情监测、诊断与预报的新方法,它包括6个独立模型和基于水分来源数量对土壤含水量判断的一些逻辑关系,6个独立模型分别基于墒情监测数据与邻近气象站降水量之间的定量关系诊断或预报土壤含水量。本文应用吉林省4个县/市的6个墒情监测点的数据验证综合诊断模型在东北半干旱和半湿润地区的应用精度和适应性,建模使用2013—2014年的数据,模型验证使用2015年的数据。为了模型更好地应用于实际,本文对每个监测点的模型参数均进行了校正。结果表明:按监测点建模情况下,不同气候和下垫面条件下的模型和参数不同;模型在东北区吉林省半干旱和半湿润地区具有较好的适应性,验证合格率为88%以上;降水量少的监测点的模型预测合格率高。墒情综合诊断模型在吉林省半干旱和半湿润地区应用精度较高,为模型在该地区应用提供了研究案例。

关键词: 羽茅, 香柱菌属内生真菌, 浸提液, 孢子萌发, 丛枝菌根真菌

Abstract:

Integrated diagnosis model is a new method of soil moisture monitoring, diagnosis and forecast. It includes six independent models and some logical relationships, which is determined based on relationships between the sum of water income and soil water content. The six independent models were based on the quantitative relationship between the monitoring data of soil water content and the precipitation of the nearest weather station to diagnose or forecast the soil water content. In this paper, the application accuracy and adaptability of the integrated diagnosis model in the semiarid and semihumid regions of Northeast China were validated by the data of 6 soil moisture monitoring sites in 4 counties in Jilin Province. The model was established by the data during the period of 2013-2014, and validated by the data of 2015. For a better application of the model, the model parameters of each monitoring point were corrected. The results showed that in the case of monitoring point modeling, the models and parameters under different climates and the surface conditions were different. The model had good adaptability in semi-arid and semi-humid regions in Jilin Province, and the qualification rate was above 88%. The model for low rainfall monitoring sites had higher qualification rate. Integrated diagnosis model of soil moisture in the semi-arid and semi-humid regions of Jilin Province had high application accuracy, which provides a case study for the application of the model in this area.
 

Key words: Achnatherum sibiricum, arbuscular mycorrhizal fungi, spore germination, Epichlo endophytes, extraction.