Teaching

Groundwater and Contamination Processes

Module 2 · International MSc in Civil Engineering · DICAM, University of Bologna

Simulated contaminant plume spreading in a heterogeneous aquifer

Quantitative modelling of groundwater contaminant transport, with particular emphasis on how geological heterogeneity affects plume dynamics and predictive uncertainty. Starting from mass conservation, students derive the advection–dispersion equation, examine its underlying assumptions, and apply one- and two-dimensional analytical solutions to interpret breakthrough curves, travel times, and plume evolution.

The module then addresses the representation of subsurface heterogeneity through spatial random functions, covariance, variograms, and geostatistical analysis carried out hands-on in MATLAB/Octave and Python, highlighting how spatial structure and scale influence effective transport behaviour.

Finally, Monte Carlo methods are introduced to propagate parameter uncertainty, assess numerical convergence, characterize predictive distributions, and estimate exceedance probabilities relevant to environmental risk assessment.

Lectures are complemented by practical sessions on analytical transport modelling, geostatistical characterization, and uncertainty propagation.

Course schedule — Module 2

Advection–dispersion equation

Mass conservation and flux decomposition
Advective, diffusive and dispersive transport
Derivation of the ADE and its underlying assumptions
Longitudinal and transverse dispersion

Analytical solutions

One-dimensional step and continuous injections
Two-dimensional continuous and pulse sources
Péclet number and limiting transport regimes
Laboratory column experiments and field applications
Case study

Heterogeneity and geostatistics

Scale dependence of hydraulic conductivity and dispersivity
Tracer tests and spatial variability
Spatial random functions and stationarity
Covariance and semivariograms
Experimental variogram estimation and standard models
Kriging, conditional simulation and validation on the Berea dataset

Uncertainty quantification

Sampling of uncertain hydrogeological parameters
Propagation of uncertainty through transport models
Convergence, response statistics and probability distributions
Exceedance probabilities and risk assessment
Computational application to a stratified aquifer

Calendar — autumn 2026

Eleven sessions, 3 November – 15 December 2026 · 24 hours in total: 16.5 of lectures and 7.5 of practical activities.

Date	Hours	Format	Topics and activities
3 Nov 2026	2	Lecture	Introduction to contaminant transport in porous media. Mass conservation; advective, diffusive and dispersive fluxes; derivation of the advection–dispersion equation and its underlying assumptions.
6 Nov 2026	2.5	Lecture	One-dimensional analytical solutions of the ADE. Initial and boundary conditions; pulse and continuous injection; constant-concentration inlet and Ogata–Banks solution; Péclet number and limiting regimes.
10 Nov 2026	2	Lecture	Two-dimensional solutions for continuous and instantaneous sources. Longitudinal and transverse dispersion; plume evolution; limitations of analytical models; the Borden aquifer case study.
13 Nov 2026	2.5	Practical session	Analytical transport modelling. Calculation and interpretation of breakthrough curves; effects of velocity, dispersivity and Péclet number; exact versus approximate solutions; parameter estimation from synthetic data.
17 Nov 2026	2	Lecture	Subsurface heterogeneity and scale effects. Measurement support; laboratory- and field-scale tracer tests; scale dependence of hydraulic conductivity and dispersivity.
20 Nov 2026	2.5	Lecture	Deterministic and stochastic representations of subsurface heterogeneity. Regionalized variables and spatial random functions; probability distributions, spatial dependence and second-order stationarity.
24 Nov 2026	2	Lecture	Spatial covariance and variograms. Experimental and theoretical variograms; nugget, sill and range; anisotropy; standard variogram models and parameter estimation.
27 Nov 2026	2.5	Computer practical	Geostatistical analysis of the Berea dataset in MATLAB/Octave and Python. Exploratory analysis and variogram estimation; interactive model fitting; ordinary kriging and collocated cokriging; sequential Gaussian simulation and validation against the exhaustive reference field.
1 Dec 2026	2	Lecture	Monte Carlo simulation. Sampling of uncertain parameters; uncertainty propagation; numerical convergence; response statistics and empirical probability distributions.
11 Dec 2026	2.5	Computer practical	Monte Carlo analysis of a stratified aquifer. Equivalent hydraulic conductivity; convergence of estimated statistical moments; probability-distribution fitting and exceedance probabilities.
15 Dec 2026	1.5	Lecture	Interpretation of uncertainty and risk. Empirical distributions, exceedance probabilities and sensitivity of model predictions. Module synthesis and presentation of the extended homework assignment.
Total	24	16.5 hours of lectures, 7.5 hours of practical activities

Course material

Lecture slides (PDF, 234 slides)

Lecture notes (PDF, book edition, 174 pages)

Codes (ZIP, MATLAB/Octave + Python)

Berea dataset (ZIP, GSLIB data for the practical)

Sample written test (PDF, Module 2: 10 questions, format and marking of the exam)

The slides cover all eleven sessions in one deck, from the derivation of the advection–dispersion equation to risk-informed decisions, closing with two optional blocks on non-Fickian transport and upscaling. The lecture notes develop the same material in full — derivations, worked examples, the field case studies and a step-by-step geostatistical practical — and every number in them is reproduced by the codes: MATLAB/Octave scripts for each practical session, with a README, no toolbox required, plus two small Python demos that make the maps flow: one compares their breakthrough curves, the other tracks a plume through time and follows its moments. The Berea dataset is the classical Berea sandstone teaching data of the geostatistical practical, in GSLIB format — 64 samples to work with, the 1600-value reference field they are validated against, and a README with the grid definition and how to load the files from the scripts.

Previous teaching

AY 2023/2024 — Fixed-term Researcher (RTD-A), Groundwater and Contamination Processes (Module 2).
MSc in Civil Engineering and MSc in Environmental Engineering, DICAM, University of Bologna.

AY 2023/2024 — Fixed-term Researcher (RTD-A), Hydraulics T (Module 3).
BSc in Civil Engineering, DICAM, University of Bologna.

AY 2023/2024 — Fixed-term Researcher (RTD-A), Modeling and Management of Natural Hydraulic Systems (Module 2).
MSc in Environmental Engineering, DICAM, University of Bologna.

AY 2022/2023 — Adjunct Professor, Groundwater and Contamination Processes.
3 ECTS, International MSc in Civil Engineering, DICAM, University of Bologna.

AY 2022/2023 — Adjunct Professor, Hydraulics.
2 ECTS, MSc in Building Engineering–Architecture, Department of Architecture, University of Bologna.

Students with questions about the course are welcome to get in touch.