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Prediction of soil cadmium distribution across a typical area of Chengdu Plain, China
Li, Qiquan1; Wang, Changquan1; Dai, Tianfei1,2; Shi, Wenjiao3,4; Zhang, Xin1; Xiao, Yi1; Song, Weiping5; Li, Bing1; Wang, Yongdong1
2017-07-28
Source PublicationSCIENTIFIC REPORTS
ISSN2045-2322
Volume7Pages:12
Corresponding AuthorWang, Changquan(wchangquan@126.com)
AbstractA suitable method and appropriate environmental variables are important for accurately predicting heavy metal distribution in soils. However, the classical methods (e.g., ordinary kriging (OK)) have a smoothing effect that results in a tendency to neglect local variability, and the commonly used environmental variables (e.g., terrain factors) are ineffective for improving predictions across plains. Here, variables were derived from the obvious factors affecting soil cadmium (Cd), such as road traffic, and were used as auxiliary variables for a combined method (HASM_RBFNN) that was developed using high accuracy surface modelling (HASM) and radial basis function neural network (RBFNN) model. This combined method was then used to predict soil Cd distribution in a typical area of Chengdu Plain in China, considering the spatial non-stationarity of the relationships between soil Cd and the derived variables based on 339 surface soil samples. The results showed that HASM_RBFNN had lower prediction errors than OK, regression kriging (RK) and HASM_RBFNNs, which didn't consider the spatial non-stationarity of the soil Cd-derived variables relationships. Furthermore, HASM_RBFNN provided improved detail on local variations. The better performance suggested that the derived environmental variables were effective and HASM_RBFNN was appropriate for improving the prediction of soil Cd distribution across plains.
DOI10.1038/s41598-017-07690-y
WOS KeywordSPATIAL PREDICTION ; ORGANIC-MATTER ; AUXILIARY INFORMATION ; AGRICULTURAL SOILS ; ROADSIDE SOILS ; REGIONAL-SCALE ; PADDY SOILS ; CONTAMINATION ; MODEL ; IDENTIFICATION
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41201214] ; Science Fund of the Education Department of Sichuan Province, China[16ZB0048]
Funding OrganizationNational Natural Science Foundation of China ; Science Fund of the Education Department of Sichuan Province, China
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000406610800001
PublisherNATURE PUBLISHING GROUP
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/61505
Collection中国科学院地理科学与资源研究所
Corresponding AuthorWang, Changquan
Affiliation1.Sichuan Agr Univ, Coll Resources, Chengdu 611130, Sichuan, Peoples R China
2.Chengdu Testing Ctr Soil & Fertilizer, Chengdu 610041, Sichuan, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
5.Dept Transportat Sichuan Prov, Chengdu 610041, Sichuan, Peoples R China
Recommended Citation
GB/T 7714
Li, Qiquan,Wang, Changquan,Dai, Tianfei,et al. Prediction of soil cadmium distribution across a typical area of Chengdu Plain, China[J]. SCIENTIFIC REPORTS,2017,7:12.
APA Li, Qiquan.,Wang, Changquan.,Dai, Tianfei.,Shi, Wenjiao.,Zhang, Xin.,...&Wang, Yongdong.(2017).Prediction of soil cadmium distribution across a typical area of Chengdu Plain, China.SCIENTIFIC REPORTS,7,12.
MLA Li, Qiquan,et al."Prediction of soil cadmium distribution across a typical area of Chengdu Plain, China".SCIENTIFIC REPORTS 7(2017):12.
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