Symposium Next Generation Hydro Software (NGHS)

1. Good modelling practice
NGHS symposium 2014
Imagine the result

2. | 4 November 2014 | © ARCADIS 2014
Slide 2

3. | 4 November 2014 | © ARCADIS 2014
Slide 3

4. | 4 November 2014 | © ARCADIS 2014
Slide 4

5. | 18 December 2013 | © ARCADIS 2013
Dia 5
Motivation GMP
•Client requirement
•Certification requirement (Delft3D, ISO)
•Efficiency and cooperation
•Knowledge management
•Training of new employees

6. | 4 November 2014 | © ARCADIS 2014
Slide 6
Content
•Introduction
•Quality and quality improvement
•Good Modelling Practice (7 steps; model journal)
•Modelling Guidelines
•Version Control
•Discussion

7. | 4 November 2014 | © ARCADIS 2014
Slide 7
Introduction
•Models are standard tools
•Might be routinely applied but subjective
•Depends on team and skills
•Often referred to as “the art of modelling”
•But unscientific and ambiguous aspects
•Risks:
•Many choices
•Complex
•Incomplete knowledge
•Result: many uncertainties

8. | 4 November 2014 | © ARCADIS 2014
Slide 8
Quality
•Models are used habitually
•Easiness to use enlarges risk of injudicious use, e.g.
•Careless handling input data
•Insufficient calibration and validation
•Use a model outside its scope
•No predefined requirements
•Result
•Unrepeatable
•Trustworthiness unknown
•Not matching predefined prerequisites

9. Quality control
Quality control:
“Something
adheres to
some criteria”
Without a properly defined
something there is no basis
whatsoever for quality control.
• date x
• batch no. x
• ingredients x
• calories x
• ℮ gram x
• date √
• batch no. √
• ingredients √
• calories √
• ℮ gram √

10. | 18 December 2013 | © ARCADIS 2013
Dia 10
Quality control flavours
•Documents (Imandra, VF)
•Project management (APM)
•Health & safety (risk form)
•Tools (SVN subversion)
•Software (idem)
•Models (…?)

11. | 18 December 2013 | © ARCADIS 2013
Dia 11
Need?
•Is there a need to check and trace model quality?
•If there is: To which extent check and trace?

12. | 18 December 2013 | © ARCADIS 2013
Dia 12
How to check and trace?
Check:
•Based on set-up?
•Based on results?
•Based on report?
•Check against what?
Trace:
•Personal communication?
•Verification form/Model Journal?
•Version Control?

13. | 4 November 2014 | © ARCADIS 2014
Slide 13
Quality management
•Quality management common in software engineering
•However, modelling quality often restricted to verification and validation
•Five maturity stages (Scholten et al., 2007):
•Ad hoc
•Repeatable
•Defined
•Managed
•Optimized

14. | 4 November 2014 | © ARCADIS 2014
Slide 14
Ontology of modelling
•“An explicit specification of a conceptualization” Gruber (1993, 1995)
•Defines modelling
•Represents shared knowledge which can be reused
•How:
•Dividing in activities to build/test intermediate products.
•Based on general agreement and negotiation (Scholten, 2007)

15. | 4 November 2014 | © ARCADIS 2014
Slide 15
1. Start model journal
2. Describe problem Define objective Specify requirements Make plan
3. Define/build model
Make conceptual model
Choose software
Choose discretization
Implement model
Verify model
4. Test/check model Check mass balances Test sensitivity
Calibrate
Validate
Determine uncertainty
5. Run model Make application plan Run model Check results
6. Describe results
Discuss results
Describe conclusions
Check objective
Analyse consequences for problem
7. Report and archive
Check model journal and templates
Good Modelling Practice flow chart
defines modelling process
Use Modelling Guidelines as reference

16. | 4 November 2014 | © ARCADIS 2014
Slide 16
Modelling Guidelines
•Introduction
•Data
•Bathymetry, Topography, Coastlines, Tidal constituents, Discharges, Water levels, Wind, Waves, Tsunamis, Sediment, Temperature and salinity
•Model set-up
•Define model area, resolution and grid layout, check grid quality, convert bathy samples, interpolate bathy, schematize sediment, boundary conditions
•Model calibration and validation
•(Technical) report
•See above
•+ criteria for figures and tables
•+ MATLAB tips and tricks

17. Quality control
Quality control:
“Something
adheres to
some criteria”
Without a properly defined
something there is no basis
whatsoever for quality control.
GMP flow chart (model journal)
and Modelling Guidelines
should be accompanied by
Version Control
• date x
• batch no. x
• ingredients x
• calories x
• ℮ gram x
• date √
• batch no. √
• ingredients √
• calories √
• ℮ gram √

18. | 18 December 2013 | © ARCADIS 2013
Dia 18
Windows Explorer

19. | 18 December 2013 | © ARCADIS 2013
Dia 19
Matlab
Description and version info

20. | 18 December 2013 | © ARCADIS 2013
Dia 20
Report

21. | 4 November 2014 | © ARCADIS 2014
Slide 21
Good Modelling Practice
Why:
•Client requirement
•Certification requirement (Delft3D, ISO)
•Efficiency and cooperation
•Knowledge management
•Training of new employees
How:
•Make Model Journal using GMP flow chart
•Use Modelling Guidelines as reference
•Use Version Control for models and scripts
Delft3D Flexible Mesh facilitates parts of the Model Journal and Version Control

22. | 4 November 2014 | © ARCADIS 2014
Slide 22
References
•Roelvink & Reniers (2012). A guide to modelling coastal morphology. World Scientific.
•Scholten et al. (2007). A methodology to support multidisciplinary model-based water management, Environmental Modelling & Software 22 (2007) 743-759
•Refsgaard et al (2005). Quality assurance in model based water management – review of existing practice and outline of new approaches. Environmental Modelling & Software 20 (2005) 1201– 1215
•Scholten et al. (2000). Good Modelling Practice in water management. HydroInformatics 2000, 23-27 July 2000, Cedar Rapids, IA, USA
•Van Waveren et al. (1999). Good Modelling Practice Handbook. STOWA report 99-05.

23. Imagine the result
Slide 23
| 4 November 2014 | © ARCADIS 2014