Mapping Soil Texture Based on Field Soil Moisture Observations at a High Temporal Resolution in an Oasis Agricultural Area

查看全文 作　　者：YANG [1,2]Renmin;LIU [1]Feng;ZHANG [1]Ganlin;ZHAO [1]Yuguo;LI [1]Decheng;YANG [1]Jinling;YANG [1,2]Fei;YANG [1,2]Fan

机构地区：[1]State Key Laboratory of Soil and Sustainable Agriculture,Institute of Soil Science,Chinese Academy of Sciences,Nanjing 210008(China);[2]University of Chinese Academy of Sciences,Beijing 100049(China)

出　　处：《Pedosphere》索引2016年第26卷第5期,共10页

基　　金：supported by the National Natural Science Foundation of China(Nos.41130530,91325301,41201207 and 41571212);the Project of Frontier Fields during the Thirteenth Five-Year Plan Period of the Institute of Soil Science,Chinese Academy of Sciences(ISSASIP1622) 摘　　要：Due to the almost homogeneous topography in low relief areas, it is usually difficult to make accurate predictions of soil properties using topographic covariates. In this study, we examined how time series of field soil moisture observations can be used to estimate soil texture in an oasis agricultural area with low relief in the semi-arid region of northwest China. Time series of field-observed soil moisture variations were recorded for 132 h beginning at the end of an irrigation event during which the surface soil was saturated.Spatial correlation between two time-adjacent soil moisture conditions was used to select the factors for fuzzy c-means clustering. In each of the ten generated clusters, soil texture of the soil sample with the maximum fuzzy membership value was taken as the cluster centroid. Finally, a linearly weighted average was used to predict soil texture from the centroids. The results showed that soil moisture increased with the increase of clay and silt contents, but decreased with the increase of sand content. The spatial patterns of soil moisture changed during the entire soil drying phase. We assumed that these changes were mainly caused by spatial heterogeneity of soil texture. A total of 64 independent samples were used to evaluate the prediction accuracy. The root mean square error(RMSE)values of clay, silt and sand were 1.63, 2.81 and 3.71, respectively. The mean relative error(RE) values were 9.57% for clay, 3.77% for silt and 12.83% for sand. It could be concluded that the method used in this study was effective for soil texture mapping in the low-relief oasis agricultural area and could be applicable in other similar irrigation agricultural areas. 关键词：土壤水分变化土壤质地农业区时空分辨率绿洲观测模糊C均值聚类制图

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Mapping Soil Texture Based on Field Soil Moisture Observations at a High Temporal Resolution in an Oasis Agricultural Area

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