An overview of geostatistics for contaminated site characterization | Training course
Find out why the geostatistical approach is relevant for contaminated site characterization, what its added value and application conditions are.
As an actor involved in the diagnosis or remediation of polluted sites and soils, you frequently face these questions:
- How to optimize an investigation plan and assess sample representativeness?
- How to model the change of scale between samples and mesh of decontamination?
- How to integrate all available data to better understand the spatial distribution of pollution?
- How to locate precisely a volume of impacted soil or a mass of pollutants?
- How to quantify the uncertainties associated with the delimitation of impacted zones while integrating subsoil heterogeneities?
During this seminar, you will understand why geostatistics is the appropriate solution to answer these questions and how it can be implemented operationally.
Who should attend?
Decision-makers, engineers and technicians involved in the characterization or remediation of potentially contaminated sites.
Methodological presentations illustrated with practical examples from real cases involving different types of pollution: chemical or radiological, leakage from a source, disturbed embankments, etc. These examples relate to several media: soil, sediment, installations (concretes).
Ample time is provided to discuss with the participants the relevance of these approaches in the contexts they face.
Understand and assess the spatial heterogeneity of pollution
- Presentation of the classical approaches implemented for characterizing potentially polluted sites and for predicting contaminated soil volumes, as well as assessing their compatibility for future use.
- Pros/Cons and underlying assumptions of these approaches.
- A practical introduction to the concepts of heterogeneity and spatial variability of pollutants. Operational consequences on the feasibility of given remediation techniques.
- Recommendation for the sampling of potentially polluted sites.
Predict and map in-situ pollution
- Presentation of common deterministic interpolation methods.
- Introduction to the kriging and its advantages: integration of the spatial variability, quantification of the attached uncertainty.
- Taking into account auxiliary information: site history, qualitative observations and quantitative measurements.
Quantify and locate contaminated volumes
- Risks attached to the use of interpolation methods for estimating contaminated volumes.
- A practical introduction to stochastic simulations.
- Presentation of results: global estimation of contaminated volumes and attached uncertainty, local risk of exceeding cleanup levels.
No prior knowledge of geostatistics is required.