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Improve the prediction of soil bulk density by cokriging with predicted soil water content as auxiliary variable

  • Soils, Sec 1 • Soil Organic Matter Dynamics and Nutrient Cycling • Research Article
  • Published:
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Abstract

Purpose

Soil bulk density (SBD) is a key soil physical property affecting the transport of water and solutes, which is essential to estimating soil carbon and nutrient reserves. However, it is considered to be time consuming, labor intensive, and expensive to obtain in situ SBD data. Therefore, it is important to estimate SBD at an acceptable level of accuracy using auxiliary variables with limited field-measured data.

Materials and methods

The Heqing Dam agriculture area in Yunnan Province, Southwest China, was selected as the study area. Sampling points of 114 were obtained based on a uniform 1 km × 1 km grid methodology, which were broken into training data and test data using ArcGIS software. The training data (91 soil samples) were used for prediction and the test data (23 soil samples) were used for validation. Predicted soil water content (SWC) was estimated using kriging with high accuracy. The predicted SWC was used as auxiliary data to improve the prediction of SBD by cokriging. The correlation coefficient (r) between field-measured and predicted values, mean error (MAE), and root mean square error (RMSE) were used to validate the performance of the geostatistics.

Results and discussion

The SBD was highly correlated with measured (r = −0.73, p < 0.01) and predicted SWC (r = −0.73, p < 0.01). The two parameters MAE and RMSE showed an improvement after introducing the predicted SWC. The MAE and RMSE decreased from 0.111 and 0.032 g cm−3 by kriging to 0.070 and 0.018 g cm−3 by cokriging with predicted SWC, respectively. The r value increased from 0.449 by kriging to 0.852 by cokriging. Compared with kriging, the application of cokriging with predicted SWC resulted in a relative improvement of 45.5 %.

Conclusions

This study demonstrates that predicted SWC used as auxiliary data can improve the prediction of SBD. Therefore, when the predicted data have been demonstrated to be of high accuracy and are highly correlated with the dependent variable, they have the potential to be a good source of auxiliary data for cokriging.

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Acknowledgments

The authors sincerely thank the anonymous reviewers and the editors for their constructive comments and suggestions. This work was supported by the National Science and Technology Support Program (NO. 2011BAC09B02, NO. 2012BAC16B02) and the Dynamic Assess and Survey on Underground Stream in Representative Karst Area (NO. 1212011220959).

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Authors and Affiliations

  1. Institute of Karst Environment and Rock Desertification Control, School of Geographical Sciences, Southwest University, Chongqing, 400715, China

    Qiyong Yang & Daoxian Yuan

  2. Key Laboratory of Karst Ecosystem and Treatment of Rocky Desertification, Institute of Karst Geology, Chinese Academy of Geological Sciences, Guilin, 541004, China

    Qiyong Yang, Weiqun Luo, Zhongcheng Jiang & Daoxian Yuan

  3. College of Resources and Environment and Tourism, Hunan University of Arts and Science, Changde, 415000, China

    Wenjun Li

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  1. Qiyong Yang
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  2. Weiqun Luo
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  3. Zhongcheng Jiang
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  4. Wenjun Li
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  5. Daoxian Yuan
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Correspondence to Qiyong Yang or Weiqun Luo.

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Responsible editor: Gilbert C. Sigua

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Yang, Q., Luo, W., Jiang, Z. et al. Improve the prediction of soil bulk density by cokriging with predicted soil water content as auxiliary variable. J Soils Sediments 16, 77–84 (2016). https://doi.org/10.1007/s11368-015-1193-4

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  • DOI: https://doi.org/10.1007/s11368-015-1193-4

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