土壤2016，Vol.48Issue(1)：186-192,7.DOI:10.13758/j.cnki.tr.2016.01.028
基于时间稳定性和降维因子分析的土壤水分监测优化
Optimizing Soil Moisture Monitoring Based on Temporal Stability and Factor Analysis
摘要
Abstract
This paper armed to optimize soil moisture monitoring by taking hill slopes in a tea garden and a bamboo forest located in Gaochun district of Nanjing City as examples and monitoring soil moisture in long-term. Based on the temporal stability and factor analysis, representative sampling sites were selected to predict soil water contents for other sampling sites by building stepwise regression models, and then checked the predication accuracy. The results showed: when only monitoring soil water content at 7 representative sampling sites in tea garden,RMSE of prediction was≤1.5 cm3/cm3. In addition, while only monitoring soil water content at 5 representative sampling sites in bamboo forest,RMSE was≤1.7 cm3/cm3. This method can reduce the number of soil moisture monitoring sites in predicting soil water content on hill slopes with limit observations. In addition, land use type and soil depth can affect soil moisture characteristics. Bamboo forest had stronger temporal stability and higher spatial autocorrelation in soil moisture than tea garden, however, the performance of regression models for bamboo forest was worse than those for tea garden. It is noted that the spatial structure of soil moisture at 30 cm depth was more stable than that at 10 cm depth, implying the performance of regression models is better at 30 cm than at 10 cm depth.关键词
土壤水分/空间预测/时间稳定性/茶园/竹林Key words
Soil water content/Spatial prediction/Temporal stability/Tea garden/Bamboo forest分类
农业科学引用本文复制引用
刘玉娇,朱青,吕立刚,廖凯华,徐飞..基于时间稳定性和降维因子分析的土壤水分监测优化[J].土壤,2016,48(1):186-192,7.基金项目
国家自然科学基金项目(41271109 （）
41301234)和中国科学院南京地理与湖泊研究所"一三五"重点项目(NIGLAS2012135005)资助. （NIGLAS2012135005）
