Multivariate conditional stochastic simulation of soil heterotrophic respiration at plot scale

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Title:Main Title: Multivariate conditional stochastic simulation of soil heterotrophic respiration at plot scale
Description:Abstract: Soil heterotrophic respiration fluxes at plot scale exhibit substantial spatial and temporal variability. Within this study secondary information was used to spatially predict heterotrophic respiration. Chamber-based measurements of heterotrophic respiration fluxes were repeated for 15 measurement campaigns within a bare 13× ^ 14 m2 soil plot. Soil water contents and temperatures were measured simultaneously with the same spatial and temporal resolution. Further, we used measurements of soil organic carbon content and apparent electrical conductivity as well as the prior measurement of the target variable. The previous variables were used as co-variates in a stepwise multiple linear regression analysis to spatially predict bare soil respiration. In particular the prior measurement of the target variable, the soil water content and the apparent electrical conductivity, showed a certain, even though limited, predictive power. In the first step we applied external drift kriging and regression kriging to determine the improvement of using co-variates in an estimation procedure in comparison to ordinary kriging. The improvement using co-variates ranged between 40 and 1% for a single measurement campaign. The difference in improving the prediction of respiration fluxes between external drift kriging and regression kriging was marginal. In a second step we applied sequential Gaussian simulations conditioned with external drift kriging to generate more realistic spatial patterns of heterotrophic respiration at plot scale. Compared to the estimation approaches the conditional stochastic simulations revealed a significantly improved reproduction of the probability density function and the semi-variogram of the original point data.
Identifier:10.1016/j.geoderma.2009.11.018 (DOI)
Responsible Party
Creators:Michael Herbst (Author), Nils Prolingheuer (Author), Alexander Graf (Author), Johan A. Huisman (Author), Lutz Weihermüller (Author), Jan Vanderborght (Author), Harry Vereecken (Author)
Publisher:Elsevier
Publication Year:2013
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Filename:2010_Herbst_Geoderma.pdf
Data Type:Text - Article
Size:9 Pages
File Size:1.4 MB
Dates:Accepted: 21.11.2009
Available: 16.10.2009
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
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Download Permission:Only Project Members
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:[TR32DB] Data policy agreement
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Publication Status:Published
Review Status:Peer reviewed
Publication Type:Article
Article Type:Journal
Source:Geoderma
Source Website:www.elsevier.com/locate/geoderma
Volume:160
Number of Pages:9 (74 - 82)
Metadata Details
Metadata Creator:Nils Prolingheuer
Metadata Created:02.12.2013
Metadata Last Updated:02.12.2013
Subproject:B1
Funding Phase:1
Metadata Language:English
Metadata Version:V50
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