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Quantitative Analysis of the Factors Influencing Soil Heavy Metal Lateral Migration in Rainfalls Based on Geographical Detector Software: A Case Study in Huanjiang County, China

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  • Pengwei Qiao

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China
    Environmental Protection Research Institute of Light Industry, Beijing 100048, China)

  • Mei Lei

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Guanghui Guo

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Jun Yang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Xiaoyong Zhou

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Tongbin Chen

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

Abstract

Quantitative analysis of the factors influencing heavy metal migration could be useful for controlling heavy metal migration. In this paper, a geographical detector was used to calculate the contributions of and interactions among factors in Huanjiang County, South China, covering an area of 273 km 2 . In this paper, nine factors were analyzed. The results showed that, among these factors, soil type was the main factor influencing the migration of As, Pb and Cd; the other eight factors did not have big differences and were lower than soil type. In addition, there were obvious synergistic effects between the soil type and concentration of water-soluble heavy metals (CWS) and the concentration of water-insoluble heavy metals (CWI) and NDVI. Therefore, these factors of the study area were especially focused on. Furthermore, the results of the key factor identification and the high-risk region identification in the nine factors were reliable, based on the geographical detector software. Therefore, the geographical detector software could be used as an effective tool to quantitatively analyze the contribution of the factors, and identify the high-risk regions for the factors influencing soil heavy metal lateral migration in rainfalls.

Suggested Citation

  • Pengwei Qiao & Mei Lei & Guanghui Guo & Jun Yang & Xiaoyong Zhou & Tongbin Chen, 2017. "Quantitative Analysis of the Factors Influencing Soil Heavy Metal Lateral Migration in Rainfalls Based on Geographical Detector Software: A Case Study in Huanjiang County, China," Sustainability, MDPI, vol. 9(7), pages 1-13, July.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:7:p:1227-:d:104572
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    References listed on IDEAS

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    1. Manoj Jha & Philip W. Gassman & Silvia Secchi & Roy Gu & Jeffrey G. Arnold, 2002. "Effect of Watershed Subdivision on SWAT Flow, Sediment, and Nutrient Predictions," Center for Agricultural and Rural Development (CARD) Publications 02-wp315, Center for Agricultural and Rural Development (CARD) at Iowa State University.
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    Cited by:

    1. Shiwei Dong & Yuchun Pan & Hui Guo & Bingbo Gao & Mengmeng Li, 2021. "Identifying Influencing Factors of Agricultural Soil Heavy Metals Using a Geographical Detector: A Case Study in Shunyi District, China," Land, MDPI, vol. 10(10), pages 1-15, September.
    2. Shudi Zuo & Shaoqing Dai & Yaying Li & Jianfeng Tang & Yin Ren, 2018. "Analysis of Heavy Metal Sources in the Soil of Riverbanks Across an Urbanization Gradient," IJERPH, MDPI, vol. 15(10), pages 1-23, October.
    3. Binh Nguyen Thi Lan & Takeshi Kobayashi & Atsushi Suetsugu & Xiaowei Tian & Takashi Kameya, 2018. "Estimating the Possibility of Surface Soil Pollution with Atmospheric Lead Deposits Using the ADMER Model," Sustainability, MDPI, vol. 10(3), pages 1-12, March.
    4. Liang Cheng & Long Li & Longqian Chen & Sai Hu & Lina Yuan & Yunqiang Liu & Yifan Cui & Ting Zhang, 2019. "Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period," IJERPH, MDPI, vol. 16(19), pages 1-25, September.
    5. Dingxuan Yan & Zhongke Bai & Xiaoyang Liu, 2020. "Heavy-Metal Pollution Characteristics and Influencing Factors in Agricultural Soils: Evidence from Shuozhou City, Shanxi Province, China," Sustainability, MDPI, vol. 12(5), pages 1-13, March.

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