uncertainty analysis & uatools statistical network march 3rd 2009

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Uncertainty Analysis & UATools Statistical network March 3rd 2009

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Page 1: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Uncertainty Analysis & UATools

Statistical network

March 3rd 2009

Page 2: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Outline presentation

• Why uncertainty analysis?• What is it?• How to perform an uncertainty analysis?• What can I do with the results?

• Discussion:

• Do we want UATools?

• How to arrange further development of UATools?

Page 3: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Take a physical model …

Model R

Page 4: Uncertainty Analysis & UATools Statistical network March 3rd 2009

… with uncertainties in input…

Model R

Page 5: Uncertainty Analysis & UATools Statistical network March 3rd 2009

… uncertainties in the parameters …

Model R

Page 6: Uncertainty Analysis & UATools Statistical network March 3rd 2009

… uncertainties in the model structure…

Model R

Page 7: Uncertainty Analysis & UATools Statistical network March 3rd 2009

… and thus uncertainty about the results.

Model R

Page 8: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Why uncertainty analysis on models?

It suits the character of the modelled processes: variable and uncertain

But also:• Accuracy of results acceptable?• Possible to improve the accuracy?• Objectives for further research• Estimation of risk of undesired events• …

Page 9: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Example: Regional watermanagement

Noordelijke IJsselvallei (Ruben Dahm)

Parameter Eenheid Verdeling Gemiddelde Standaarddeviatie Ondergrens Bovengrens 1 Berging op maaiveld mm Gamma 4 1 2 Vertragingsfactor overstort 1/min Gamma 0,025 0,01 3 Intreeweerstand dag Gamma 150 100 50 4 Drainagediepte m-maaiveld Gamma 1,5 0,2 0,9* 5 Drainageweerstand dag Normaal 125 12,5 6 Berging op verhard oppervlak mm Uniform 1 3 7 Oppervlakte afvoer dag Uniform 0,1 1,5 8 Infiltratiecapaciteit zand mm/hr Uniform 20 40 9 Infiltratiecapaciteit klei mm/hr Bèta 1,5 0,3 1 5

10 Initiële grondwaterstand m+ streefpeil Bèta 0,35 0,15 0,1 0,75 11 Weerstandcoëfficiënt watergang** s-1 Bèta 20 4 5 30 12 Weerstandcoëfficiënt duiker m1/3/s Bèta 75 7 60 100 13 Afvoercoëfficiënt stuw - Bèta 1,05 0,1 0,85 1,3

Page 10: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Example: Regional watermanagement

Maximale waterstand

Parameter 1070 1149 1320 1414 1564 1616 1070 1149 1320 1414 1564 1616 1070 1149 1320 1414 1564 1616 1070 1149 1320 1414 1564 1616

Berging op maaiveld- 1.6Vertragingsfactor overstort-

Intreeweerstand-

Drainagediepte- 0.9Drainageweerstand-

Berging op verhard oppervlak-

Oppervlakte afvoer- 17.2 TMV %Infiltratiecapaciteit zand- 0 - 1

Infiltratiecapaciteit klei- 1 - 5Initiële grondwaterstand- 51.7 5 - 25

Weerstandcoëfficiënt watergang- 25.3 25 - 50Weerstandcoëfficiënt duiker- 50 - 75

Afvoercoëfficiënt stuw- 0.2 75 - 100Totaal verklaarde variantie (TMV)- 97.9 96.6 98.4 96.1 92.0 96.9 96.6 95.5 97.7 96.6 95.2 98.1 90.3 88.8 84.9 88.9 76.5 78.0 95.0 99.0 96.6 99.3 90.5 96.4

Maximale waterstand Maximaal debiet

Neerslagpatroon 'Hoog' Neerslagpatroon '2 Piek kort' Neerslagpatroon 'Hoog' Neerslagpatroon '2 Piek kort'

Page 11: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Uncertainty analysis in 6 steps:

1. Problem definition

2. Inventory of uncertainties

3. Quantification of uncertainties

4. Identification of main sources of uncertainty

5. Quantification of uncertainty in the model results

6. Interpretation and presentation

Tip: Guidance for UA => bulletin\klis

Page 12: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Model

Model

Model

...

R

statistics

R

R

Often necessary: Monte Carlo analysis

Page 13: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Model

UAToolsDefine

uncertainties

Batch run

Ensemble of output

Statistical analysis of

output

Select values

To facilitate UA: UATools

Page 14: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Screendump of UATools

Page 15: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Example: UA of HBC Waddensea

Uncertainty in HBC • Water level• Wave heigth• Wave period

water level

wave height, period

critical crest level

=> Uncertainty in critical crest level

Joost Beckers et al.

Page 16: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Set-up UA of HBC Waddensea

SWAN calculations in a Monte Carlo setting

h(αw), Uw(αw) Hm0, Tm-1,0

Uncertainty of water level

Uncertainty of wind speed

SWAN modelparametersuncertainty

SWAN inputuncertainty

Hydra-K calculations in a Monte Carlo setting

uncertainty of SWAN results

uncertainty of HBC

uncertainty of crest levels

1a

2c

2a

2b

1b

Page 17: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Location 3

Water level36%

Wind speed47%

SWAN17%

Location 1

Water level45%

Wind speed9%

SWAN46%

UA Waddensea: Contributions to uncertainty

Shallow water locations Deep water locations

Water level statistics

Wind speed statistics important at deep water

SWAN uncertainty,predominantydepth induced breaking

will be less

Page 18: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Example: river morphology Delft3D

variability of the river bed

Page 19: Uncertainty Analysis & UATools Statistical network March 3rd 2009

shipping width at OLR

Example: river morphology Delft3D

Page 20: Uncertainty Analysis & UATools Statistical network March 3rd 2009

Questions & discussion

• Do we want UATools?

• How to arrange further development of UATools?