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Alternative TitleSpatial distribution of ~(137)Cs reference inventory in Sichuan province using geographically weighted regression Kriging combined with ~(137)Cs reference inventory mathematical model
李豪1; 文安邦2; 李婷1
Source Publication中国水土保持科学
Contribution Rank2
Abstract~(137)Cs示踪技术是土壤侵蚀研究的一种重要方法,目前已得到广泛应用。准确的~(137)Cs本底值是运用该技术开展研究的基础。为了获取区域高空间分辨率~(137)Cs本底值数据,作者基于147个气象站点的实测数据和Walling & He的~(137)Cs本底值计算模型,运用主成分分析(PCA)和地理加权回归克里格(GWRK)相结合的方法,预测四川省~(137)Cs本底值的空间分布。结果表明: 1)应用PCA法可在保留大部分原始信息的同时,有效地消除变量间的多重共线性,为后续的回归分析与空间插值奠定基础; 2) GWRK插值法综合考虑了降水、空间位置等多个影响因素及其对~(137)Cs本底值影响的空间非平稳性,相对于传统的普通克里格和全局回归克里格插值法具有更高的预测精度,且较准确地表达局部区域~(137)Cs本底值空间分布的细节信息; 3)以实测数据为基础、基于GIS技术的空间插值方法是获取区域高分辨率~(137)Cs本底值空间数据的可行途径。本研究有效地揭示~(137)Cs本底值的空间分布规律及不同因素对其影响,为运用~(137)Cs示踪技术开展土壤侵蚀研究、水土流失治理等工作提供基础数据和技术支持。
Other Abstract[Background] Use of the fallout radionuclide ~(137)Cs as a tracer recently has been widely employed for the assessment of soil erosion. In the ~(137)Cs method,the magnitude of the rate of soil erosion is estimated by comparing the ~(137)Cs inventory of the sampling points with the local reference inventory, therefore,it is of extreme importance to determine the ~(137)Cs reference inventory obtained from a local stable site neither erosion nor deposition occurred while studying soil erosion using this tracing technique. [Methods] Based on the measured data from 147 meteorology stations and the ~(137)Cs fallout model derived by Walling & He,a case study on the application of geographically weighted regression Kriging interpolation (GWRK) combined with principal component analysis (PCA) for the assessment of the spatial distribution of the ~(137)Cs reference inventories was undertaken at Sichuan province,Southwest China. [Results]1) Using PCA,the transformation process to turn the influence factors of longitude, latitude and precipitation into 2 principal component variables were educed. This measure not only maintained the 90% information of original data,but also decreased the multicollinearity among the variables significantly. It was the basis for the further interpolation of ~(137)Cs reference inventory. 2) With the principal components as input variables,the spatial distribution of the ~(137)Cs reference inventories at Sichuan province were obtained by 3 different methods: the GWRK method,the ordinary Kriging (OK) method and global regression Kriging method (GRK) . In the meantime,some indicators such as Mean Absolute Error (MAE),Root Mean Square Error (RMSE),Mean Absolute Relative Error (MARE) were calculated for evaluating the accuracy of different interpolation results. In terms of the interpolation results,taking into consideration of various influence factors and their spatial non-stationarity,the GWRK method had better accuracy compared with the other methods. Furthermore,this simulation result is in exactly agreement with those of the measurement. [Conclusions]This study reveals the regulars of space distribution of ~(137)Cs reference inventory and the effect of different factors. Additionally,the results of this study also demonstrate that it is obviously an approach available for obtaining the spatial distribution of ~(137)Cs reference inventory with high resolution and accuracy to adopt the GIS interpolation on the basis of the measured data,which is referential for the study of soil erosion using ~(137)Cs tracing technique.
Keyword~(137)Cs本底值 地理加权回归克里格 ~(137)Cs本底值计算模型 四川省
Indexed ByCSCD
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Document Type期刊论文
Corresponding Author李豪
2.中国科学院水利部成都山地灾害与环境研究所, 610041,成都)
Recommended Citation
GB/T 7714
李豪,文安邦,李婷. 基于~(137)Cs本底值计算模型和地理加权回归克里格对~(137)Cs本底值空间分布的预测[J]. 中国水土保持科学,2018,16(5):57-66.
APA 李豪,文安邦,&李婷.(2018).基于~(137)Cs本底值计算模型和地理加权回归克里格对~(137)Cs本底值空间分布的预测.中国水土保持科学,16(5),57-66.
MLA 李豪,et al."基于~(137)Cs本底值计算模型和地理加权回归克里格对~(137)Cs本底值空间分布的预测".中国水土保持科学 16.5(2018):57-66.
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