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Dealing with soil organic carbon modeling: some insights from an agro-ecosystem in Northeast Iran

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Abstract

Mapping soil organic carbon (SOC) and its uncertainty are essential for agricultural soil management. The current study was carried out to quantify and map the spatial variability of SOC in an Agro-Ecosystem region (~ 170 km2) in Northeast Iran using Ordinary Kriging (OK), Empirical Bayesian Kriging (EBK), and Inverse Distance Weighting (IDW) techniques. In the study area, a total of 288 soil surface samples (0–20 cm depth) were collected. Results showed that the mean SOC was 0.728% with high variability (CV = 44.78%), and also SOC was found to be deviant from a normal distribution as revealed by Kolmogorov–Smirnov (K-S) test, with positive skewness. Due to the deviation from the normal distribution, and for the purpose of modeling, the data were log-transformed to approximate a normal distribution. The best fit empirical variogram was the Exponential model. Among the various interpolation techniques, estimation with EBK approach was the fairly reliable (RMSE = 0.3156; ME = 0.004), followed by OK (RMSE = 0.3162; ME = 0.003), and IDW (RMSE = 0.3199; ME = 0.005). Moreover, results showed that the spatial analysis of SOC had a strong spatial dependency for this study. Thus, the results revealed that the simple interpolation approach was a fast method and highly suitable for the spatial prediction of SOC in this study.

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Abbreviations

C:

Carbon

SOC:

Soil organic carbon

EBK:

Empirical Bayesian Kriging

IDW:

Inverse Distance Weighting

RBF:

Radial Basis Function

OK:

Ordinary Kriging

CK:

Co-Kriging

TDS:

Total dissolved solids

SpD:

Spatial dependence

RMSE:

Root mean square error

ME:

Mean error

GPS:

Global Positioning System

SD:

Standard deviation

CV:

Coefficient of variation

Kurt:

Kurtosis

Skew:

Skewness

K-S:

Kolmogorov–Smirnov

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Acknowledgements

We would like to thank the reviewers and editor for their critical comments that helped to improve the paper. The authors gratefully acknowledge the financial support provided by the Department of Soil Science, University of Tehran, Iran (research project no. 4886791).

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Authors and Affiliations

  1. Laboratory of Remote Sensing and GIS, Department of Soil Science, University of Tehran, P.O. Box: 4111, 31587-77871, Karaj, Iran

    Ali Keshavarzi

  2. Department of Crop and Soil Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    Henry Oppong Tuffour

  3. Institute of Environmental and Sanitation Studies, University of Ghana, Legon, Accra, Ghana

    Jimmy Clifford Oppong

  4. Henan Key Laboratory of Earth System Observation and Modeling, Henan University, Kaifeng, 475004, China

    Mojtaba Zeraatpisheh

  5. College of Environment and Planning, Henan University, Kaifeng, 475004, China

    Mojtaba Zeraatpisheh

  6. Government Degree College Ramban, 182144, Ramban, Jammu and Kashmir, India

    Vinod Kumar

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  1. Ali Keshavarzi
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Keshavarzi, A., Tuffour, H.O., Oppong, J.C. et al. Dealing with soil organic carbon modeling: some insights from an agro-ecosystem in Northeast Iran. Earth Sci Inform 14, 1833–1845 (2021). https://doi.org/10.1007/s12145-021-00638-x

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