Prediction methods of spatial distribution of aeolian sand in Ruyi River Basin of Bashang Plateau, Hebei Province

SHAO Hai; YIN Zhiqiang; WANG Yi; XING Bo; PENG Ling; WANG Ruifeng

doi:10.12097/j.issn.1671-2552.2022.12.006

2022 Vol. 41, No. 12

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SHAO Hai, YIN Zhiqiang, WANG Yi, XING Bo, PENG Ling, WANG Ruifeng. Prediction methods of spatial distribution of aeolian sand in Ruyi River Basin of Bashang Plateau, Hebei Province[J]. Geological Bulletin of China, 2022, 41(12): 2138-2145. doi: 10.12097/j.issn.1671-2552.2022.12.006

Citation:

SHAO Hai, YIN Zhiqiang, WANG Yi, XING Bo, PENG Ling, WANG Ruifeng. Prediction methods of spatial distribution of aeolian sand in Ruyi River Basin of Bashang Plateau, Hebei Province[J]. Geological Bulletin of China, 2022, 41(12): 2138-2145. doi: 10.12097/j.issn.1671-2552.2022.12.006

Prediction methods of spatial distribution of aeolian sand in Ruyi River Basin of Bashang Plateau, Hebei Province

1.
China Institute of Geo-Environment Monitoring, Beijing 100081, China
2.
Natural Resources Comprehensive Survey Command Center, China Geological Survey, Beijing 100055, China
3.
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Chengdu University of Technology), Chengdu 610059, Sichuan, China
4.
Hebei Key Laboratory of Mountain Geological Environment, Chengde 067000, Heibei, China

More Information

Corresponding author: YIN Zhiqiang, yinzhiqiang@mail.cgs.gov.cn

Received Date: 29 May 2022

Revised Date: 26 October 2022

Publish Date: 15 December 2022

Abstract

Abstract

Different spatial interpolation methods will have an important influence on the prediction accuracy of the spatial distribution of aeolian sand thickness.Based on the data of 152 groups of aeolian sand thickness in the middle reaches of Ruyi River Basin in the east of Bashang Plateau, Chengde, this paper used the Radial Basis Function-Artificial Neural Network(RBF-ANN)interpolation method to explore the spatial distribution characteristics of aeolian sand thickness in this area, and compared the prediction error and calculation results among different model functions in geostatistical analyst method and different interpolation methods in deterministic interpolation method.The results showed that among the geostatistical analyst methods, the classical EBK-Power has the best interpolation effect and among the deterministic interpolation methods the RBF interpolation is the best.Compared with EBK-Power and RBF interpolation, RBF-ANN interpolation improves the mean absolute error by more than 30%, and the improvement on the root mean square error was more than 20%, so it was concluded that RBF-ANN interpolation was more suitable for predicting the spatial distribution of aeolian sand thickness in Ruyi River Basin.
- aeolian sand /
- thickness /
- spatial interpolation /
- Radial Basis Function-Artificial Neural Network interpolation /
- Bashang plateau

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References

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