JOURNAL OF NATURAL RESOURCES ›› 2016, Vol. 31 ›› Issue (5): 855-863.

• Resource Evaluation •

### Spatial Variability of Soil Organic Matter and Appropriate Number of Samples on County Scale in Jianghan Plain

YU Lei, WEI Dong, WANG Hui-xia, HUANG Qun, PENG Yan, XU Yuan-yuan

1. a. College of City and Environmental Science, b. Key Laboratory for Geographical Process Analysis & Simulation, Hubei Province, Central China Normal University, Wuhan 430079, China
• Received:2015-06-02 Revised:2015-11-30 Online:2016-05-20 Published:2016-05-19
• Supported by:
National Natural Science Foundation of China, No.41401232 and 41271534; Fundamental Research Funds for the Central Universities, No.CCNU15A05006 and CCNU15ZD001

Abstract: Soil organic matter (SOM) is a key index to estimate soil fertility and quality of cultivated land. Finding an appropriate number of samples on county scale is very important in saving costs while accurately expressing the spatial variability of SOM. In this research, Gong’an County, with an area of 2 258 km2, locating in the hinterland of Jianghan Plain (111°25′-111°48′E, 29°37′-30°19′N), was chosen as a typical case. A total of 4 045 soil samples were collected for analysis of SOM content. After the rejection of outliers, 3 950 sample sites were retained for further analysis. First, semi-variance function was used to explore the whole spatial variability. Then, a gradient template was defined to calculate the gradient vector, and the area was devided into seven parts based on the density of the pixels which had high gradient values. Moran’s I was used to describe the spatial variability of each part. In order to determine the appropriate number of samples, 100 points were randomly sampled and independent verification was used to validate the precision of Kriging interpolation result under different number of sample sites, i.e., 3 850, 2 695, 1 886, 1 320, 924, 647, 452 and 317. In order to improve the accuracy of sampling, a simple dichotomy method was employed to find the most appropriate number of samples. Geostatistical analysis suggested that the spatial variability of SOM distribution was moderate, and structural factors showed that SOM was affected by human activities in the research region. Six high spatially variated areas were found by gradient calculation on the basis of Kriging interpolation, and the local Moran’s I showed great anisotropy of SOM distribution and significant spatial variability in these regions, which suggested that more sampling sites are needed in these regions to obtain accurate spatial interpolation. Independent verification showed that the number of sampling points was positively correlated with the modeling accuracy and the reasonable number wasl was between 452 and 657 in this area. Finally, the appropriate sampling number was determined as 598 by dichotomy method. The results can provide guidance for monitoring and controling farmland quality in Jianghan Plain.

CLC Number:

• S158