MULTIVARIATE SIMULATION AND ASSESSMENT OF THREE DIMENSIONAL SPATIAL PATTERNS OF COASTAL SOIL SALINITY USING ANCILLARY VARIABLES
Yao, Rongjiang1,2; Yang, Jingsong1,2; Gao, Peng3; Shao, Hongbo4; Chen, Xiaobing4; Yu, Shipeng1
发表期刊FRESENIUS ENVIRONMENTAL BULLETIN
2013
卷号22期号:1页码:39-52
关键词Multivariate Coastal Zone Uncertainty Assessment Soil Salinity Electromagnetic Induction
英文摘要Rapid and reliable spatial estimates of field soil salinity aid farmers and researchers in understanding the development of salinization and identifying areas in the field where special management practices are required to control its speed. Apparent soil electrical conductivity, measured by electromagnetic induction instruments, has been widely used as an auxiliary variable to estimate spatial distribution of field soil salinity owing to the high-efficient and non-invasive nature. Methods used for this purpose are mostly a series of kriging-based algorithms. This study adopted stochastic simulation algorithms, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS), to generate equiprobable realizations of soil salinity patterns, to evaluate the uncertainty associated with those patterns, and to determine which algorithm is more reliable for the local and spatial uncertainty assessment. Results showed that experimental semivariograms were generally isotropic at all directions with the identical nugget, sill and range parameters despite the limited data in X and Z directions. Nugget contributions comprised from 19.5 to 40.1% of model sill values at the horizontal orientation, which negligibly ranged from 2.1 to 6.0% at the vertical orientation. The spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the actual values. It was found that the distribution of soil salinity was generally normal and there existed the probability of secondary salinization across the spatial domain. The estimation precision of SGS algorithm was superior to that of SGCS algorithm. In addition, accuracy plots and standard deviation maps both indicated that SGS approach performed better in terms of modelling local uncertainty and propagating the spatial uncertainty. Thus, the SGS method was suitable for the spatial estimation of the soil property, distribution type and data arrangement in our study. We concluded that the SGS algorithm with data conversion (converting EM measurements at unsampled sites to soil salinity values) prior to simulation modeled the uncertainty better than the SGCS algorithm (soil salinity as primary variate and EM measurements as covariate).
文章类型Article
收录类别SCI
语种英语
关键词[WOS]GEOSTATISTICAL STOCHASTIC SIMULATION ; ELECTROMAGNETIC INDUCTION TECHNIQUES ; ELECTRICAL-CONDUCTIVITY ; UNCERTAINTY ASSESSMENT ; PRECISION AGRICULTURE ; IRRIGATED COTTON ; WATER CONTENT ; CORN YIELD ; VARIABILITY ; PROFILES
研究领域[WOS]Environmental Sciences & Ecology
WOS记录号WOS:000321723100005
引用统计
被引频次:5[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.yic.ac.cn/handle/133337/9042
专题海岸带生物学与生物资源利用重点实验室_海岸带生物学与生物资源保护实验室
作者单位1.Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Jiangsu, Peoples R China
2.Chinese Acad Sci, Dongtai Inst Tidal Flat Res, Nanjing Branch, Dongtai 224200, Peoples R China
3.Univ S Carolina, Dept Geog, Columbia, SC 29208 USA
4.Chinese Acad Sci, Yantai Inst Coastal Zone Res, CAS Shandong Prov Key Lab Coastal Environm Proc, Yantai 264003, Peoples R China
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Yao, Rongjiang,Yang, Jingsong,Gao, Peng,et al. MULTIVARIATE SIMULATION AND ASSESSMENT OF THREE DIMENSIONAL SPATIAL PATTERNS OF COASTAL SOIL SALINITY USING ANCILLARY VARIABLES[J]. FRESENIUS ENVIRONMENTAL BULLETIN,2013,22(1):39-52.
APA Yao, Rongjiang,Yang, Jingsong,Gao, Peng,Shao, Hongbo,Chen, Xiaobing,&Yu, Shipeng.(2013).MULTIVARIATE SIMULATION AND ASSESSMENT OF THREE DIMENSIONAL SPATIAL PATTERNS OF COASTAL SOIL SALINITY USING ANCILLARY VARIABLES.FRESENIUS ENVIRONMENTAL BULLETIN,22(1),39-52.
MLA Yao, Rongjiang,et al."MULTIVARIATE SIMULATION AND ASSESSMENT OF THREE DIMENSIONAL SPATIAL PATTERNS OF COASTAL SOIL SALINITY USING ANCILLARY VARIABLES".FRESENIUS ENVIRONMENTAL BULLETIN 22.1(2013):39-52.
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