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Uncertainty assessment of heavy metal soil contamination mapping using spatiotemporal sequential indicator simulation with multi-temporal sampling points

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Abstract

Mapping the space–time distribution of heavy metals in soils plays a key role in contaminated site classification under conditions of in situ uncertainty, whereas uncertainty assessment is based on the quantification of the specific uncertainties in terms of exceedance probabilities. Geostatistical space-time kriging (STK) is increasingly used to estimate pollutant concentrations in soils. Sequential indicator simulation (SIS) technique is popular in uncertainty assessment of heavy metal contamination of soils. However, these techniques cannot handle multi-temporal data. In this work, spatiotemporal sequential indicator simulation (STSIS) based on an additive space–time semivariogram model (STSIS_A) and on a non-separable space–time semivariogram model (STSIS_NS) was used to assimilate multi-temporal data in the mapping and uncertainty assessment of heavy metal distributions in contaminated soils. Cu concentrations in soils sampled during the period 2010–2014 in the Qingshan district (Wuhan City, Hubei Province, China) were used as the experimental data set. Based on a number of STSIS realizations, we assessed different kinds of mapping uncertainty, including single-location uncertainty during 1 year and during multiple years, multi-location uncertainty during 1 year, and during multiple years. The comparison of the STSIS technique vs. SIS and STK techniques showed that STSIS performs better than both STK and SIS.

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Acknowledgments

The research was supported by National Natural Science Foundation of China (Grant No. 41101193), the Fundamental Research Funds for the Central Universities (Grant No. 2662014PY062), and China Scholarship Council. Opinions in the paper do not constitute an endorsement or approval by the funding agencies and only reflect the personal views of the authors.

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Authors and Affiliations

  1. Department of Resources and Environmental Information, College of Resources and Environment, Huazhong Agricultural University, Wuhan, 430070, China

    Yong Yang

  2. Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtse River), Ministry of Agriculture, Wuhan, 430070, China

    Yong Yang

  3. Ocean College, Zhejiang University, Hangzhou, Zhejiang, China

    George Christakos

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  1. Yong Yang
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  2. George Christakos
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Correspondence to Yong Yang.

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Yang, Y., Christakos, G. Uncertainty assessment of heavy metal soil contamination mapping using spatiotemporal sequential indicator simulation with multi-temporal sampling points. Environ Monit Assess 187, 571 (2015). https://doi.org/10.1007/s10661-015-4785-y

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  • DOI: https://doi.org/10.1007/s10661-015-4785-y

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