• DocumentCode
    3572173
  • Title

    Comparison analysis of stochastic simulation for the spatial distribution of heavy metal pollution of soil

  • Author

    Zehua Chen ; Shouzhi Xu ; Kai Ma ; Xiaobo Zhu ; Qing Wang

  • Author_Institution
    Collaborative Innovation Center for Key Technol. of Smart Irrigation District in Hubei, China Three Gorges Univ., Yichang, China
  • fYear
    2014
  • Firstpage
    124
  • Lastpage
    129
  • Abstract
    Semivariograms and its parameters have a significant impact on Kriging interpolation and stochastic simulation. This paper used GS+ and ArcGIS to research the heavy metal of Yichang citrus orchard, which used spherical model, Gaussian model, exponential model and linear model to fit the experimental semivariograms and applied these models in the Sequential Gaussian Simulation. The stochastic simulation results of different models show that the average of Hg is over the national standard of soil quality, so there are some pollution. The best model is exponential model which can keep semivariograms isomorphic before and after the simulation, which is different from the model selected by the largest coefficient of determination, so during stochastic simulation, the appropriate model should be selected by the comparison of the simulation results of various model.
  • Keywords
    Gaussian processes; environmental science computing; soil pollution; statistical analysis; ArcGIS software; GS+ software; Gaussian model; Yichang citrus orchard; comparison analysis; determination coefficient; exponential model; heavy metal pollution; kriging interpolation; linear model; semivariograms; sequential Gaussian simulation; soil pollution; spherical model; stochastic simulation; Analytical models; Computational modeling; Educational institutions; Mercury (metals); Soil; Stochastic processes; Semivariograms; Sequential Gaussian Simulation; The heavy metal of soil; stochastic simulation; the spatial distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2014 11th World Congress on
  • Type

    conf

  • DOI
    10.1109/WCICA.2014.7052699
  • Filename
    7052699