基于主成分的协克里金法对地下水砷空间分布预测

张洁; 梁杏; 刘延锋; 张鑫; 孙立群; 赵枫; 付鹏宇

doi:10.3799/dqkx.2021.180

Volume 48 Issue 10

Oct. 2023

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Article Navigation > Earth Science > 2023 > 48(10): 3820-3831

Zhang Jie, Liang Xing, Liu Yanfeng, Zhang Xin, Sun Liqun, Zhao Feng, Fu Pengyu, 2023. CoKriging Method Based on Principal Components to Predict Spatial Distribution of Arsenic in Groundwater. Earth Science, 48(10): 3820-3831. doi: 10.3799/dqkx.2021.180

Citation:

Zhang Jie, Liang Xing, Liu Yanfeng, Zhang Xin, Sun Liqun, Zhao Feng, Fu Pengyu, 2023. CoKriging Method Based on Principal Components to Predict Spatial Distribution of Arsenic in Groundwater. Earth Science, 48(10): 3820-3831. doi: 10.3799/dqkx.2021.180

Citation:

Zhang Jie, Liang Xing, Liu Yanfeng, Zhang Xin, Sun Liqun, Zhao Feng, Fu Pengyu, 2023. CoKriging Method Based on Principal Components to Predict Spatial Distribution of Arsenic in Groundwater. Earth Science, 48(10): 3820-3831. doi: 10.3799/dqkx.2021.180

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CoKriging Method Based on Principal Components to Predict Spatial Distribution of Arsenic in Groundwater

doi: 10.3799/dqkx.2021.180

School of Environmental Studies, China University of Geosciences, Wuhan 430078, China

Received Date: 2021-06-30
Available Online: 2023-10-31
Publish Date: 2023-10-25

Abstract

Abstract

Few factors are considered in the current spatial simulation of arsenic content in groundwater, resulting in low prediction accuracy. To the east of Jianghan Plain as an example, considering the effects of all groundwater chemical components on arsenic, ordinary kriging (OK), traditional CoKriging (COK) and CoKriging based on principal component (COK-Y, where Y is a comprehensive factor obtained by principal component analysis) were used to simulate the spatial distribution of arsenic in groundwater. The results show that the semi-variogram fitting of COK-Y is the best, and the mean square error and mean absolute error for arsenic prediction in groundwater are 21.7% and 21.3% lower than OK, respectively. Compared with COK, the evaluation indexes decrease by 3.5% and 3.4%, severally. The accuracy of COK-Y is improved slightly, and the spatiacl distribution map of arsenic in groundwater can better reflect the high heterogeneity of arsenic, which is more realistic. COK-Y improve the dampening effect of kriging method to the grestest extent. The comprehensive factor Y indicates the contribution of each component on the simulation of arsenic. The reductive dissolution of iron oxide and hydroxide was the main factor for the formation and distribution of high arsenic in groundwater. The weathering, dissolution and analytical adsorption of polymetallic minerals, such as barite, magnetite and ilmenite also contributed part of it.
- groundwater,
- arsenic,
- spatial distribution,
- CoKriging method,
- principal component analysis,
- Jianghan plain,
- environmental geology

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References(55)

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CoKriging Method Based on Principal Components to Predict Spatial Distribution of Arsenic in Groundwater

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