JOURNAL OF NATURAL RESOURCES ›› 2010, Vol. 25 ›› Issue (8): 1385-1399.doi: 10.11849/zrzyxb.2010.08.015

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Study on Method for Spatial Simulation of Topsoil SOM at National Scale in China

LI Qi-quan1,2, YUE Tian-xiang1, FAN Ze-meng1, DU Zheng-ping1   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2010-02-28 Revised:2010-04-30 Online:2010-08-20 Published:2010-08-20

Abstract: Given the importance of soil organic carbon (SOC) as a pool in the global carbon cycle and an indicator for soil quality, there exits a need to simulate this soil property at large scale (regional or national). However, few researches focus on simulating spatial distribution of SOC at national scale in China by using model and samples. In this paper, based on 5374 typical soil profiles collected during the second national soil survey period (1979-1994), correlation between topsoil organic matter content (20 cm) and 11 environmental factors were analyzed, spatial distribution of topsoil organic matter (SOM) at national scale in China was simulated with the combination of multiple regression model and HASM model, and prediction error of this method was discussed, in order to provide a new method for spatial simulation of soil organic carbon. Results indicated that, mean absolute error and mean relative error of the predicted value for 350 validation points were 15.61g·kg-1 and 56. 59%; compared with ordinary Kriging method, the two errors were reduced by 1.61g·kg-1 and 20.84% respectively. Besides, simulation result for Northwest China and Taiwan Province, where the density of sample points was much smaller and even no samples distributed, was much closer to the actual situation. When the samples were cut by half, the two errors were only increased by 0.14 g·kg-1 and 1.07% respectively. Consequently, the method in this paper can be used as a relatively effective method for simulating spatial distribution of SOM at national scale, and attaining higher levels of precision largely depend on making the model explain much more spatial variability of SOM as well as increasing the number of sampling sites used to establish the model.

Key words: HASM method, soil organic matter, national scale, sampling density, spatial simulation

CLC Number: 

  • S153.6+21