统计法土壤墒情诊断模型

Statistical diagnostic model of soil moisture

本文介绍了统计法土壤墒情诊断模型的原理和建模方法,该模型是基于时段降水量和土壤初始含水量以及二者的交互作用项建立的,并应用7个省23个县87个监测点2012—2014年的数据建模,以及2015年的数据进行验证。结果表明:统计法模型诊断和预测合格率较高,合格率达到85%以上;相邻墒情监测日的时间间隔有时不固定将导致异常值的出现,这是影响模型预测合格率的主要原因;逐日模型法可以实现逐日土壤墒情的预测。本研究表明,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 statistical diagnostic model were introduced. The model is based on precipitation in different periods, soil initial water content and their interaction. Models were established by the data of 87 monitoring sites in 23 counties of 7 provinces during 2012-2014, and were validated by the data of 2015. The results showed that the statistical diagnostic model had high qualification rates （more than 85%） in diagnosis and prediction. The non-fixed time interval of the adjacent soil moisture monitoring date would lead to the emergence of outliers, which was the main reason affecting the qualification rate of model prediction. Statisti- cal diagnostic model based on daily time series data can predict daily soil water content. In conclusion, statistical diagnostic model can be used alone as a soil moisture diagnosis model.