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Predicting soil organic carbon stock using profile depth distribution functions and ordinary kriging

Umakant Mishra, Rattan Lal, Brian Slater, Frank Calhoun, Liu Desheng and Marc Van Meirvenne UGent (2009) SOIL SCIENCE SOCIETY OF AMERICA JOURNAL. 73(2). p.614-621
abstract
The objective of this study was to predict and map SOC stocks at different depth intervals within the upper I-in depth using profile depth distribution functions and ordinary kriging. These approaches were tested for the state of Indiana as a case study. A total of 464 pedons representing 204 soil series was obtained from the National Soil Survey Center database. Another 48 soil profile samples were collected to better represent the heterogeneity of the environmental variables. Two methods were used to model the depth distribution of the SOC stocks using negative exponential profile depth functions. In Procedure A, the functions to describe the depth distribution of volumetric C content for each soil profile were fitted using nonlinear least squares. In Procedure B, the exponential functions were fitted to describe the depth distribution of the cumulative SOC stocks. The parameters of the functions were interpolated for the entire study area using ordinary kriging on 81% of the data points (n = 414). The integral of the exponential function up to the desired depth was used to predict SOC stocks within the 0- to 1-, 0- to 0.5-, and 0.5- to 1-m depth intervals. These estimates were validated using the remaining 19% (n = 98) of the data. Procedure B showed a higher prediction accuracy for all depths, with higher rand lower RMSE values. The highest prediction accuracy (r = 0.75, RMSE = 2.89 kg m(-2)) was obtained for SOC stocks in the 0- to 0.5-m depth interval. Using Procedure B, SOC stocks within the top 1 m of Indiana soils were estimated to be 0.90 Pg C.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
ELEVATION, PATTERNS, AGRICULTURE, SEQUESTRATION, CONTERMINOUS UNITED-STATES, SPATIAL PREDICTION, TEXTURE, BELGIUM, CLIMATE, MATTER
journal title
SOIL SCIENCE SOCIETY OF AMERICA JOURNAL
volume
73
issue
2
pages
614 - 621
Web of Science type
Article
Web of Science id
000264089300032
JCR category
SOIL SCIENCE
JCR impact factor
2.179 (2009)
JCR rank
7/31 (2009)
JCR quartile
1 (2009)
ISSN
0361-5995
DOI
10.2136/sssaj2007.0410
language
English
UGent publication?
yes
classification
A1
id
742144
handle
http://hdl.handle.net/1854/LU-742144
date created
2009-09-08 14:41:09
date last changed
2009-11-23 11:38:28
@article{742144,
  abstract     = {The objective of this study was to predict and map SOC stocks at different depth intervals within the upper I-in depth using profile depth distribution functions and ordinary kriging. These approaches were tested for the state of Indiana as a case study. A total of 464 pedons representing 204 soil series was obtained from the National Soil Survey Center database. Another 48 soil profile samples were collected to better represent the heterogeneity of the environmental variables. Two methods were used to model the depth distribution of the SOC stocks using negative exponential profile depth functions. In Procedure A, the functions to describe the depth distribution of volumetric C content for each soil profile were fitted using nonlinear least squares. In Procedure B, the exponential functions were fitted to describe the depth distribution of the cumulative SOC stocks. The parameters of the functions were interpolated for the entire study area using ordinary kriging on 81\% of the data points (n = 414). The integral of the exponential function up to the desired depth was used to predict SOC stocks within the 0- to 1-, 0- to 0.5-, and 0.5- to 1-m depth intervals. These estimates were validated using the remaining 19\% (n = 98) of the data. Procedure B showed a higher prediction accuracy for all depths, with higher rand lower RMSE values. The highest prediction accuracy (r = 0.75, RMSE = 2.89 kg m(-2)) was obtained for SOC stocks in the 0- to 0.5-m depth interval. Using Procedure B, SOC stocks within the top 1 m of Indiana soils were estimated to be 0.90 Pg C.},
  author       = {Mishra, Umakant and Lal, Rattan and Slater, Brian and Calhoun, Frank and Desheng, Liu and Van Meirvenne, Marc},
  issn         = {0361-5995},
  journal      = {SOIL SCIENCE SOCIETY OF AMERICA JOURNAL},
  keyword      = {ELEVATION,PATTERNS,AGRICULTURE,SEQUESTRATION,CONTERMINOUS UNITED-STATES,SPATIAL PREDICTION,TEXTURE,BELGIUM,CLIMATE,MATTER},
  language     = {eng},
  number       = {2},
  pages        = {614--621},
  title        = {Predicting soil organic carbon stock using profile depth distribution functions and ordinary kriging},
  url          = {http://dx.doi.org/10.2136/sssaj2007.0410},
  volume       = {73},
  year         = {2009},
}

Chicago
Mishra, Umakant, Rattan Lal, Brian Slater, Frank Calhoun, Liu Desheng, and Marc Van Meirvenne. 2009. “Predicting Soil Organic Carbon Stock Using Profile Depth Distribution Functions and Ordinary Kriging.” Soil Science Society of America Journal 73 (2): 614–621.
APA
Mishra, U., Lal, R., Slater, B., Calhoun, F., Desheng, L., & Van Meirvenne, M. (2009). Predicting soil organic carbon stock using profile depth distribution functions and ordinary kriging. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 73(2), 614–621.
Vancouver
1.
Mishra U, Lal R, Slater B, Calhoun F, Desheng L, Van Meirvenne M. Predicting soil organic carbon stock using profile depth distribution functions and ordinary kriging. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL. 2009;73(2):614–21.
MLA
Mishra, Umakant, Rattan Lal, Brian Slater, et al. “Predicting Soil Organic Carbon Stock Using Profile Depth Distribution Functions and Ordinary Kriging.” SOIL SCIENCE SOCIETY OF AMERICA JOURNAL 73.2 (2009): 614–621. Print.