Exploratory data analysis and geospatial analysis with geostatistics after high-resolution site characterization

Published
2022-03-24
Keywords: Geospatial Analysis, High Resolution Tools, Site Investigation, Contaminated Sites, Geostatistics. Análise Espacial, Alta Resolução, Investigação Ambiental, Área Contaminada, Geoestatística.

    Authors

  • Guilherme Navarro Diogo Tavares Universidade de São Paulo (USP), São Paulo, SP, Brasil.
  • Raphael Martin Salaroli Universidade de São Paulo (USP), São Paulo, SP, Brasil.
  • Felipe Augusto Nascimento de Jesus Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG, Brasil
  • Marcos Tanaka Riyis Centro Universitário Senac, São Paulo, SP, Brasil

Abstract

The contaminant mass in the storage zone and their spatial distribution are relevant variables during the remediation stage. Exploratory Data Analysis in conjunction with geostatistics, approached through Ordinary Kriging (KO) and Radial Basis Function (RBF) were compared to traditional data processing techniques from low- and high-resolution environmental investigations to evaluate the difference in the estimation of contaminant mass, impacted soil volume and indicate improvements in the investigation strategy of contaminated areas. It was verified that the traditional criteria for investigating volatile organic compounds in retained phase promote the bias of the data and reduce the confidence of the estimation of the mass of contaminants and of impacted soil. The replacement of the traditional interpolation method (ABNT NBR 15515-3) by geostatistics resulted in a reduction in the mass of contaminants from 62.73 kg to 28.16 kg (KO) and 8.45 kg (RBF), and in the impacted volume of 1423.43 m³ to about 525 m³. It is recommended the adoption of techniques such as composite and the addition of random (simple or stratified) or systematic sampling criteria in combination with the traditional ones

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How to Cite
Tavares, G. N. D., Salaroli, R. M., Jesus, F. A. N. de, & Riyis, M. T. (2022). Exploratory data analysis and geospatial analysis with geostatistics after high-resolution site characterization. Águas Subterrâneas, 36(1), e–30083. https://doi.org/10.14295/ras.v36i1.30083