teaching innovation project modelling in the environmental sciences -

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Teaching Innovation Project Modelling in the environmental sciences - Enhancing employability for the environmental sector Stefan Krause, Zoe Robinson School of Physical and Geographical Sciences

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Teaching Innovation Project Modelling in the environmental sciences - Enhancing employability for the environmental sector Stefan Krause, Zoe Robinson School of Physical and Geographical Sciences. Modelling in Environmental Sciences. Modelling in Environmental Sciences. Rf. A. Int. - PowerPoint PPT Presentation

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Page 1: Teaching Innovation Project Modelling in the environmental sciences -

Teaching Innovation Project

Modelling in the environmental sciences-

Enhancing employability for the environmental sector

Stefan Krause, Zoe Robinson

School of Physical and Geographical Sciences

Page 2: Teaching Innovation Project Modelling in the environmental sciences -

Modelling in Environmental Sciences

Page 3: Teaching Innovation Project Modelling in the environmental sciences -

Modelling in Environmental Sciences

lumped 2D distributed 3D distributed

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Numerical Model Generation, Conceptualisation and Model Parameterisation, Data analysis, Geo-statistics, Calibration and Validation of Numerical Models, Scenario Development and Simulation, Model Testing and Prediction, Forecasting, Uncertainty Analysis….

Page 4: Teaching Innovation Project Modelling in the environmental sciences -

www.jobs.ac.uk/environment:

…. An understanding of open channel hydraulics and the principles of hydraulic modelling, as well as the ability to use river modelling software, would be advantageous. Experience in topographic surveying and use of GIS would also be beneficial

…. Experience in characterizing and simulating fate, transport, of organic and inorganic contaminants

…. GIS, map preparation, data analysis, modelling, and report preparation

…. Working experience with ArcGIS type mapping and geostatistical methodologies

…. Working experience with mixing models or flow path simulators such as MT3D, Bioplume, SEAWAT, Visual MODFLOW, etc.

Motivation – Increasing Employability

Page 5: Teaching Innovation Project Modelling in the environmental sciences -

• Descriptive approaches instead of strategies for problem solving and analytical methods

• Strong opinions but weak knowledge backgrounds

• Insufficient methodological knowledge – lack of tools

• Misunderstood ‘Problem Based Learning’

talking about problems (exciting) –

methods to analyse or mitigate (boring, difficult)

Motivation – The Status Quo

Page 6: Teaching Innovation Project Modelling in the environmental sciences -

• Significant methodological background knowledge required before PBL-application in Environ. Science

• Perception of maths, statistics (difficult, boring….)

• Unexciting teaching strategies!

Reasons – The Status Quo

Page 7: Teaching Innovation Project Modelling in the environmental sciences -

Reasons – The Status Quo

Page 8: Teaching Innovation Project Modelling in the environmental sciences -

The Project

Applied Methods in the Environmental Sciences

Page 9: Teaching Innovation Project Modelling in the environmental sciences -

The Project

Applied Methods in the Environmental Sciences

Page 10: Teaching Innovation Project Modelling in the environmental sciences -

Applied Methods in the Environmental Sciences

1. Environmental Statistics (Statistical Programming)

• Environmental data• Introduction into statistics and time series analysis• Spatial statistics – Geo-statistics• Data analysis and presentation tools

2. Environmental (Geographical) Information Systems

• Spatial data – types and structures• Spatial data bases and how to use them• Grid based digital terrain analysis• GIS for hydrological modelling

3. Environmental Modelling

• Modelling in an environmental context• Model types and model building• Model procedures, calibration and validation techniques• Scenario techniques• Model uncertainties

Page 11: Teaching Innovation Project Modelling in the environmental sciences -

How to make simulations and statistics exciting?

• Problem based projects – use of own data – field courses, dissertations

• Focussing on the controversies

• Uncertainties in model simulations and scenario assumptions

Page 12: Teaching Innovation Project Modelling in the environmental sciences -

Degree of sophistication:

- How much complexity can we afford?

- Complex, fully integrated system solutions vs. simple and basic approaches

Commercial vs. open source software

- Integration of supporting partners

(Un-conventional?) teaching styles – permanent alteration of lecture – computer based practical – tutorial

Problems to consider:

Page 13: Teaching Innovation Project Modelling in the environmental sciences -

Digital Surface Models• Types

– DEM : Digital Elevation Model– DSM : Digital Surface Model – DTM : Digital Terrain Model

• Data Structure– Raster– TIN

Steve Kopp, Dean Djokic ( ESRI), Al Rea (USGS)

Page 14: Teaching Innovation Project Modelling in the environmental sciences -

Geographical data analyses

Spatial Interpolation

Ex: Interpolation of precipitation for weather forecasting

Page 15: Teaching Innovation Project Modelling in the environmental sciences -

Numerical Modelling of Groundwater Pollution

Page 16: Teaching Innovation Project Modelling in the environmental sciences -

Conceptual Model

Development

Scenario Generation and

Simulation

Critical Analysis of

Model Uncertainties

Page 17: Teaching Innovation Project Modelling in the environmental sciences -

Problems and Obstacles

• High demand on supervision, especially during computer based classes

• “Unexpected” content, style - course expectations

• Attention deficits

• To late for being really beneficial for dissertation data analysis

Page 18: Teaching Innovation Project Modelling in the environmental sciences -

OUTLOOK

Module going to run in 1st semester from this year

Demonstrator for computer based classes requested

More problem based “surgeries” on selected real data

Course expectations and content – employer evaluation