Mapping soil organic carbon using auxiliary environmentalcovariates in a typical watershed in the Loess Plateau of China:a comparative study based on three kriging methods and a soilland inference model (SoLIM)
Wen,W(Wen,Wen)[1,2]; Wang,YF(Wang,Yafeng)[1,3]; Yang,L(Yang,Lin)[4]; Liang,D(Liang,Di)[5]; Chen,LD(Chen,Liding)[1]; Liu,J(Liu,Jing)[6]; Zhu,AX(Zhu,Axing)[4,6,7]
2014-07-26
发表期刊Environ Earth Sci
卷号73期号:2015页码:239-251
文章类型期刊论文
摘要

Detailed maps of regional spatial distribution of soil organic carbon (SOC) are needed to guide sustainable soil uses and management decisions. Interpolation methods based on spatial auto-correlations, environmental covariates, or hybrid methods are commonly used to predict SOC maps. Many of these methods perform well for gentle terrains. However, it is unknown how these methods perform to capture SOC variations in complex terrains, especially areas of which land uses are interrupted by human activities, such as the Loess Plateau of China. This study compared four interpolations or predictive methods including ordinary kriging (OK), regression kriging, ordinary kriging integrated with land-use type (OK_LU) and a soil land inference model (SoLIM). The purpose of this study is to find appropriate methods, which are suitable to the complex terrain in Loess Plateau region of China. The study area was a typical watershed in Loess Plateau with complex hilly–gully terrain and various land-use types. A field sampling dataset of 200 points was partitioned into 1/2 for model building and 1/2 for accuracy validation in a random way. Nine environmental covariates were selected: land-use types, digital elevation model, solar radiation, slope degree, slope aspect, plan curvature, profile curvature, surface area ratio, and topographic wetness index. The mean absolute percentage error, root mean square error, and goodness-of-prediction statistic value were selected to evaluate mapping results. The results showed that the use of easily obtained environmental covariates, land-use types and terrain variables improved accuracies of SOC interpolation, which will be of interests for related research of similar environments in the Loess Plateau. SoLIM and OK_LU can be two suitable and efficient methods, which produced detailed, reasonable maps with higher accuracy and prediction effectiveness, for the study area and similar areas in the Loess Plateau.

关键词Spatial Interpolation Method Soil Organiccarbon Auxiliary Environmental Variables The Loessplateau Regions
DOI10.1007/s12665-014-3518-9
收录类别SCI
语种英语
引用统计
文献类型期刊论文
条目标识符http://ir.ieecas.cn/handle/361006/9487
专题黄土与第四纪地质国家重点实验室(2010~)
作者单位1.State Key Laboratory of Urban and Regional Ecology,Research Center for Eco- Environmental Sciences,Chinese Academy of Sciences, P. O. Box 2871, Beijing 100085,People’s Republic of China;
2.College of Environmental Sciences and Engineering, PekingUniversity, Beijing 100871, People’s Republic of China;
3.State Key Laboratory of Loess and Quaternary Geology,Institute of Earth Environment, Chinese Academy of Sciences,Xi’an 710075, People’s Republic of China;
4.State Key Laboratory of Resources and EnvironmentInformation System, Institute of Geographical Sciences andNatural Resources Research, Chinese Academy of Sciences,Beijing 100101, People’s Republic of China;
5.Department of Plant, Soil and Microbial Sciences, MichiganState University, East Lansing, MI 48824, USA;
6.Department of Geography, University of Wisconsin-Madison,Madison, WI 53706, USA;
7.School of Geography, Nanjing Normal University,Nanjing 210023, People’s Republic of China
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GB/T 7714
Wen,W,Wang,YF,Yang,L,et al. Mapping soil organic carbon using auxiliary environmentalcovariates in a typical watershed in the Loess Plateau of China:a comparative study based on three kriging methods and a soilland inference model (SoLIM)[J]. Environ Earth Sci,2014,73(2015):239-251.
APA Wen,W.,Wang,YF.,Yang,L.,Liang,D.,Chen,LD.,...&Zhu,AX.(2014).Mapping soil organic carbon using auxiliary environmentalcovariates in a typical watershed in the Loess Plateau of China:a comparative study based on three kriging methods and a soilland inference model (SoLIM).Environ Earth Sci,73(2015),239-251.
MLA Wen,W,et al."Mapping soil organic carbon using auxiliary environmentalcovariates in a typical watershed in the Loess Plateau of China:a comparative study based on three kriging methods and a soilland inference model (SoLIM)".Environ Earth Sci 73.2015(2014):239-251.
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