Sciences in Cold and Arid Regions ›› 2020, Vol. 12 ›› Issue (4): 200–216.doi: 10.3724/SP.J.1226.2020.00217.

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  • 收稿日期:2020-05-15 接受日期:2020-07-20 出版日期:2020-08-31 发布日期:2020-09-04

Comparison of sampling schemes for spatial prediction of soil organic carbon in Northern China

XuYang Wang1,2,YuQiang Li1,2,3(),YuLin Li1,2,3,YinPing Chen4,Jie Lian1,2,WenJie Cao4   

  1. 1.Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
    2.University of Chinese Academy of Sciences, Beijing 100049, China
    3.Naiman Desertification Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Tongliao, Inner Mongolia 028300, China
    4.School of Environmental and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China
  • Received:2020-05-15 Accepted:2020-07-20 Online:2020-08-31 Published:2020-09-04
  • Contact: YuQiang Li E-mail:liyq@lzb.ac.cn

Abstract:

Determining an optimal sample size is a key step in designing field surveys, and is particularly important for detecting the spatial pattern of highly variable properties such as soil organic carbon (SOC). Based on 550 soil sampling points in the near-surface layer (0 to 20 cm) in a representative region of northern China’s agro-pastoral ecotone, we studied effects of four interpolation methods such as ordinary kriging (OK), universal kriging (UK), inverse distance weighting (IDW) and radial basis function (RBF) and random subsampling (50, 100, 200, 300, 400, and 500) on the prediction accuracy of SOC estimation. When the Shannon's Diversity Index (SHDI) and Shannon's Evenness Index (SHEI) was 2.01 and 0.67, the OK method appeared to be a superior method, which had the smallest root mean square error (RMSE) and the mean error (ME) nearest to zero. On the contrary, the UK method performed poorly for the interpolation of SOC in the present study. The sample size of 200 had the most accurate prediction; 50 sampling points produced the worst prediction accuracy. Thus, we used 200 samples to estimate the study area's soil organic carbon density (SOCD) by the OK method. The total SOC storage to a depth of 20 cm in the study area was 117.94 Mt, and its mean SOCD was 2.40 kg/m2. The SOCD kg/(C?m2) of different land use types were in the following order: woodland (3.29) > grassland (2.35) > cropland (2.19) > sandy land (1.55).

Key words: soil organic carbon, sample size, geostatistics, kriging, prediction accuracy

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CountyArea (km2)Proportion of total areaSample size (No. of sites)Sample proportion
Ar Horqin12,76225.94%13925.27%
Balinzuo6,46013.13%6311.45%
Balinyou9,82619.97%10819.64%
Wengniute11,86124.11%12522.73%
Aohan8,28916.85%11520.91%
Total49,201100.00%550100.00%

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ParameterNRangeMinimumMaximumMeanStandard deviation
SOCD (kg/m2)55011.180.0511.242.241.48
BD (g/cm3)5500.850.781.631.310.14
Stoniness (vol%)306.530.196.721.971.32

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Sample sizeMinimumMaximumMean (kg/m2)SDSkewnessKurtosisCV
500.447.412.411.461.361.8360.79%
1000.447.412.371.371.181.1357.84%
2000.1110.122.381.581.704.1266.68%
3000.1110.122.351.541.563.5265.37%
4000.0510.122.291.491.453.1565.27%
5000.0510.122.211.431.563.7264.60%
5500.0511.242.241.481.825.5466.00%

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Soil layer (cm)Sample sizeNuggetPartial sillSillNugget/sill ratioRange (km)
0-10500.080.200.2829.24%64.81
1000.010.240.242.12%42.38
2000.090.240.3427.96%27.96
3000.220.250.4647.18%74.44
4000.190.180.3751.16%14.14
5000.080.280.3621.83%12.86
10-20500.170.060.2274.05%165.91
1000.170.080.2568.12%34.98
2000.150.280.4334.49%77.15
3000.080.240.3224.34%16.32
4000.080.280.3621.54%13.49
5000.020.310.347.12%14.01
0-20500.070.130.2033.00%56.33
1000.080.140.2238.00%60.46
2000.070.230.3124.00%32.08
3000.100.190.2934.00%17.11
4000.110.220.3334.00%14.14
5000.040.270.3113.00%13.72

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CountyArea (km2)MinimumMaximumMean (kg/m2)SDStorage (Mt)
Ar Horqin12,7621.247.703.211.0441.02
Balinzuo6,4601.317.613.291.3221.28
Balinyou9,8290.927.092.410.9123.70
Wengniute11,8610.194.761.570.7318.59
Aohan8,2890.653.011.610.4113.35

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CountyProportion of total area
CroplandWoodlandGrasslandSandy land
Ar Horqin24.10%19.32%41.75%7.52%
Balinzuo30.62%36.19%28.86%0.75%
Balinyou14.29%16.00%54.93%8.08%
Wengniute24.07%9.36%40.07%19.66%
Aohan47.36%16.47%27.09%1.83%

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CountyLand use/coverArea (km2)SOCD (kg/(C·m2))SOC storage (Mt·C)
Ar HorqinCropland3,1172.79 ± 0.748.70
Woodland2,4714.21 ± 1.1310.41
Grassland5,3103.09 ± 0.9116.43
Sandy land9372.91 ± 0.712.72
BalinzuoCropland2,0182.70 ± 0.855.45
Woodland2,3173.93 ± 1.409.11
Grassland1,8773.18 ± 1.245.97
Sandy land471.82 ± 0.330.09
BalinyouCropland1,3762.41 ± 0.663.32
Woodland1,5943.08 ± 1.204.92
Grassland5,3482.28 ± 0.8212.22
Sandy land7922.04 ± 0.541.62
WengniuteCropland2,8051.88 ± 0.525.26
Woodland1,0862.00 ± 0.652.17
Grassland4,7191.61 ± 0.767.58
Sandy land2,3540.86 ± 0.392.03
AohanCropland3,9261.59 ± 0.376.26
Woodland1,3331.70 ± 0.422.27
Grassland2,2631.61 ± 0.443.65
Sandy land1471.06 ± 0.220.16
Total study areaCropland13,2472.19 ± 0.8029.02
Woodland8,8223.29 ± 1.4829.02
Grassland19,5372.35 ± 1.0745.94
Sandy land4,2791.55 ± 0.996.61
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