Universität Wien FIND
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290131 UE Modelling in Physical Geography (2019W)

4.00 ECTS (3.00 SWS), SPL 29 - Geographie
Continuous assessment of course work

Registration/Deregistration

Details

max. 30 participants
Language: English

Lecturers

Classes

The course starts on the 9th of October and will be a 3 hr lecture from 12-3.

The date are as follows
09.10.19 Introduction and course outline.
23.10.19 What is a model?
30.10.19 How to model landslides
06.11.19 Oral Presentations
20.11.19 Intro to scripting
27.11.19 Scripting continued
04.12.19 Statistical landslide susceptibility analysis
11.12.19 Using r.avaflow
15.01.20 Consultation, any unfinished business, discussion and help with final report
22.01.20 Extra time if required

MM-Lab, NIG, first floor


Information

Aims, contents and method of the course

Aim: to give a general introduction and overview on modelling in physical geography, including a number a hands-on examples and short introduction to scripting in Python.

Contents:
• What is a model
• How to model landslides
• Data and Modelling
• Intro to scripting in Python
• Statistical landslide susceptibility analysis
• Using r.avaflow to model landslides
Method of the course: the course will include
• lectures,
• a number of guided hands-on exercises in actual model use and scripting
• group assignment on summarizing and presenting group research.
• individual assignment on the preparation of a report on the concepts of modelling.

Assessment and permitted materials

Attendance, scientific report, oral presentation, homework, final report

Minimum requirements and assessment criteria

Participation and attendance, (absence on max. 2 units, 10%)
Review of models are used in landslide research (individual assignment, 15% max 2500 words)
What models are used in ….? Oral presentation (group assignment, 20% max 15 mins)
Scripting assignments (individual assignment, 25%)
Final report (individual assignment, 30% max 5000 words)

Examination topics

Regular active participation, reports, homework, presentation

Reading list

Mergili, M., Emmer, A., Juřicová, A., Cochachin, A., Fischer, J.‐T., Huggel, C., and Pudasaini, S. P. ( 2018) How well can we simulate complex hydro‐geomorphic process chains? The 2012 multi‐lake outburst flood in the Santa Cruz Valley (Cordillera Blanca, Perú). Earth Surf. Process. Landforms, 43: 1373– 1389. doi: 10.1002/esp.4318.

Mergili, M. and Fischer, J.-T. and Krenn, J. and Pudasaini, S. P. (2017) r.avaflow v1, an advanced open-source computational framework for the propagation and interaction of two-phase mass flows. Geoscientific Model Development (10) 2: 553-569. doi: 10.5194/gmd-10-553-2017

Beguería S. (2006) Validation and Evaluation of Predictive Models in Hazard Assessment and Risk Management. Natural Hazards 37:315–329. doi: 10.1007/s11069-005-5182-6

Fell R, Corominas J, Bonnard C, et al (2008) Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Engineering Geology 102:85–98. doi: 10.1016/j.enggeo.2008.03.022

Guzzetti F, Mondini AC, Cardinali M, et al (2012) Landslide inventory maps: New tools for an old problem. Earth-Science Reviews 112:42–66. doi: 10.1016/j.earscirev.2012.02.001

Venables W., N, Smith, D, M (2009) An Introduction to R (2nd ed.). Network Theory Ltd.

Lovelace R., Nowosad J., Muenchow J., (2019) Geocomputation with R (1st ed.). Chapman and Hall/CRC. ISBN: 9781138304512

Association in the course directory

(MG-S1-PI.m, Block A) (MG-S2-PI.m, Block A)

Last modified: Tu 07.01.2020 15:08