Learning

Kataclima organizza corsi a livello universitario o a livello aziendale.
Le attività sono strutturate attraverso l’integrazione di:

  • K-learning, la piattaforma e-learning di Kataclima basata su Moodle (accesso con username e password);
  • lezioni in aula all’interno della sala multimediale di kataclima;
  • corsi presso le sedi dei commitenti.

Docente dei corsi: Dr. Francesca Lotti, PhD in Idrogeologia, docente presso Università degli Studi di Camerino.

 

Alcuni dei corsi disponibili (in italiano e inglese)

Model Calibration and Predictive Uncertainty Analysis using PEST

(Civitavecchia, Italy, 11-15 September 2017)

Intensive Training Course held by John Doherty (author of the code), Francesca Lotti (Kataclima) and Giovanni Formentin (Tethys).

Course venue: Università degli Studi della Tuscia, Polo Universitario Civitavecchia – P.zza Verdi 1, Civitavecchia

PEST (Parameter ESTimation) is an open-source, public domain software suite for the calibration and uncertainty analysis of environmental models. The aim of the course is to provide a comprehensive theoretical and practical background for parameter estimation and uncertainty analysis in groundwater modelling, through the use of PEST.

On-line sessions will be held in the k-learning platform and will be provided after a few days of “ideas settlement”. Instructions and credential for the access to the platform will be provided during the last course session. All on-line sessions will be recorded and available at a later time.

For further information and to register, please download the Brochure.

Contacts: Francesca Lotti (f.lotti@kataclima.com; Tel. +39.338.4624787)

 

Model Calibration and Predictive Uncertainty Analysis using PEST

(Southampton, UK, 04-08 September 2017)

Intensive Training Course held by John Doherty (author of the code), Alastair Black (Groundwater Science ldt) and Francesca Lotti (Kataclima)

Course venue: Room 2040 in Building 45 - The University of Southampton, Highfield campus, Southampton, UK

PEST (Parameter ESTimation) is an open-source, public domain software suite for the calibration and uncertainty analysis of environmental models. The aim of the course is to provide a comprehensive theoretical and practical background for parameter estimation and uncertainty analysis in groundwater modelling, through the use of PEST.

On-line sessions will be held in the k-learning platform and will be provided after a few days of “ideas settlement”. All on-line sessions will be recorded and available at a later time.

For further information and to register, please download the Brochure (UK).

Contacts: Oleksandra Pedchenko (oop1g10@soton.ac.uk)

 

Basics of Hydrogeology

This course covers fundamentals of subsurface flow and transport, emphasizing the role of groundwater in the hydrologic cycle, the relation of groundwater flow to geologic structure, and the management of contaminated groundwater. Every topic is explained from a theoretical point of view followed by practical application with computer exercises.

Advanced Hydrogeology

The course focuses on advanced hydrogeology topics such as groundwater contamination and remediation, processing of spatial and temporal data, basics of numerical modelling. Prerequisites are: basics of Hydrogeology, GIS, basics of statistics, basic calculations and working with spreadsheets.

Groundwater Flow Dynamics and Contaminant Transport

The course gives insights on the advanced concepts and principles of groundwater Flow, Fate and Transport and Natural Attenuation (mass flux, mass discharge, horizontal and vertical anisotropy effects on contaminant flow directions, effects of heterogeneity, non-horizontal flow, hydrodynamic conditions, multi-phase partitioning, dispersion, retardation). The course includes description of illustrative case histories and application of software.

Field Hydrogeology

The most important step in hydrogeological site characterization is to plan and execute effective field investigation. This course provide insights on how to plan and carry out time/cost-effective measurements.

Pumping test analysis

The course introduces the basic equation of groundwater flow, the different analytical techniques developed to solve the equations and their practical application. Classical solution methods are then compared to computed parameter optimization. During the course different open-source softwares will be used for exercises.

Numerical Modelling

The aim of the course is to provide a comprehensive training in the fundamentals of groundwater flow modeling, together with considerable practical experience. The course program is listed below.

Section A: Review and/or insights of key topics Starting test. Review of fundamental concepts of groundwater flow and transport: Darcy law, hydraulic head, flow equations, pumping tests interpretation.

Section B: GIS data processing Introduction to applied geostatistics: analysis and processing of hydrogeological data-sets, experimental variogram, regionalization of field data, evaluation of the uncertainty of spatial distributions.

Section C: Numerical Modeling Introduction to numerical modeling in groundwater: finite differences and finite elements models, groundwater flow modeling; application of groundwater models. Creation of a numerical model with FEFLOW/MODFLOW: setting of the grid, boundary conditions, properties, observation points. Sensitivity analysis and calibration of parameters according to different techniques (zone calibration and pilot point calibration). Critical evaluation of results and uncertainty analysis.

During the course Hands-on exercises concerning geostatistics and modeling through the use of different softwares (i.e. Aquachem, Aquifer Test, MLU, Surfer, ArcGIS, Excel).

Numerical Model Calibration

The aim of the course is to provide insights on the calibration process of groundwater numerical models. Different calibration techniques are explained and compared, focusing on the uncertainty analysis of model results and predictions. The course includes practical exercises with PEST (associated to Feflow or Modflow models).

Groundwater Contamination and Remediation

Aim of the course is the understanding and definition of the conceptual model of the contaminated site, the definition of the contaminant distribution in space and time and the assessment of possible remediation through different techniques.

Basics of Statistics and Probability

Statistical tools essential in the environmental sciences are explained through comprehensible practical examples.

Basic use of GIS

Introduction to the Geographical Information Systems and practical exercises with different softwares (open-source and commercial).

Advanced use of GIS

Advanced tools and data processing with open-source and commercial GIS explained with comprehensible practical exercises. Basic use of GIS required.

Geostatistics

Aim of the course is to provide students the skill to handle spatial data and gain the most of information hidden in wide datasets. Main contents include: Review of basic concepts of statistics and probability. From point data to surfaces, what can we infer? What is Geostatistics and when it should be applied. Geostatistics versus deterministic interpolation. Spatial analysis (geo and nongeo-statistical). Semivariogram modeling. Estimation theory. Ordinary Kriging and other estimators. Cross-validation. Accuracy of the estimate as a function of the spatial variability. Application of geostatistical methods to different datasets (precipitations, air temperatures, chemicals in groundwater, potentiometric levels, etc.) using different softwares.

Spatial analysis of data

The course concentrates on the application of geostatistical techniques to wide datasets in order to get the most of the information out of spatial data. Basics of statistics, comfortable use of worksheet and GIS required.