Contamination characterization with multivariate geostatistics and sampling optimization| Training course

Learn how to integrate secondary pollutants or contaminants and semi-quantitative measures in the mapping of the pollutant of interest to reduce map uncertainty using a multivariate geostatistical approach.

Objectives

  • Understand and implement multivariate geostatistics to reduce estimation uncertainty by taking advantage of the correlation between pollutants/contaminants.
  • Make the best use of all available data, quantitative and/or semi-quantitative.
  • Perform coherent and simultaneous characterizations for several contaminations on the same site.

Outlines

  • Half of the course is devoted to methodological presentations, the second half to practical exercises on real-life cases to deepen the understanding of concepts. Focus is on illustrations and practical contribution of the covered concepts.
  • Computer exercises with Kartotrak.
  • Course material provided.

Who should attend

Engineers, technicians, consultancies, project owners, prime contractors, public bodies, industrial operators who wish to go further with geostatistics.

Course content

Part 1: Map the pollution/contamination of interest taking into account other pollutants/secondary variables

  • Analyze the correlations between the different types of available measurements, quantitative and semi-quantitative: other pollutants, DEM, soil occupation, physicochemical models, indirect indices of pollution, lithology, etc.: calculation of scatter plots and coefficients of correlation.
  • Highlight the spatial relationships between pollutants: multivariate variogram calculation and modeling.
  • Integrate one or several secondary variables in the interpolation: find out more about the co-kriging principles and implement the methodology.
  • Analyze the inputs of cokriging compared to kriging.

Part 2: Optimize the density and location of sampling points

  • Design the initial sampling plan.
  • Compute the probability to reach a hot spot according to the sample size and the studied contamination size.
  • Optimize the number and location of new sampling spots to improve the initial characterization.
  • Reduce false-negative risks.

To have attended the course 2D mapping of radiological contaminations using geostatistics or have good basic knowledge in geostatistics (variography, kriging).


Registered professional members of AusIMM are eligible to claim 8 PD Hours when attending this short course IN-PERSON.
Registered professional members of AusIMM are eligible to claim 8 PD Hours when attending this short course IN-PERSON.

 

Registered professional members of AusIMM are eligible to claim 6 PD Hours when attending this short course ONLINE.
Registered professional members of AusIMM are eligible to claim 6 PD Hours when attending this short course ONLINE.

Prerequisites