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墒情诊断模型的应用条件

李敬亚1,黄治平1,刘书田1,2,侯彦林1,2*,郑宏艳1,米长虹1,丁健1,王铄今2   

  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

Application conditions of soil moisture diagnostic models.

LI Jing-ya1, HUANG Zhi-ping1, LIU Shu-tian1,2, HOU Yan-lin1,2*, ZHENG Hong-yan1, MI Chang-hong1, DING Jian1, WANG Shuo-jin2#br#   

  1. (1Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China; Key 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: 对墒情诊断模型应用的下垫面条件进行了综合分析,这些条件包括气候区、监测点距气象站距离、土壤质地、监测时间、熟制、作物种类和模型参数。结果表明:平衡法、统计法、差减统计法、比值统计法、间隔天数统计法、移动统计法6个独立诊断模型和综合模型具有普遍适应性;模型普遍适应性的外在原因是建模时只考虑3个独立的具有普遍性的变量(土壤含水量、时段降水量、2次土壤含水量测定的间隔天数),模型普遍适应性的内在原因是按监测点建模和确定参数;多年平均降水量是影响模型预测合格率的主要因素之一,其值越小模型预测合格率越高。6个独立诊断模型和综合模型的应用不受下垫面因素影响,模型通用变量为3个独立变量。

关键词: 海绵城市, 暴雨径流管理模型, 低影响开发, 景观格局优化

Abstract: The application conditions of moisture diagnostic models were analyzed. These conditions include climate zoning, distance from monitoring site to meteorological station, soil texture, monitoring time, cropping system, crop type, and model parameters. The results showed that six independent diagnostic models (i.e., balance diagnostic model, statistical diagnostic model, subtractive statistical diagnostic model, ratio statistical diagnostic model, interval days statistical diagnostic model, movable statistical diagnostic model) and integrated diagnostic model had universal adaptability. The external reason of the models’ universal applicability was that these models considered only three independent variables (soil water content, period precipitation, and interval days of two monitoring times of soil moisture); the inherent reason for the general applicability of models was that modeling and determining parameters were based on monitoring sites. The average annual precipitation was one of the major factors affecting the qualified rate of model prediction; the smaller the value was, the higher the qualified rate was. In conclusion, the applications of the six independent diagnostic models and the integrated diagnostic model were not affected by underlying surface factors, and these models included three independent variables.

Key words: sponge city, low impact development., landscape pattern optimization, storm water management model