1. Towards time and space evolving extreme wind fields
Joana van Nieuwkoop, Sofia Caires and Jacco Groeneweg
IAHR 2015
Acknowledgements:
Netherlands National Water Authority, Rijkswaterstaat

2. Outline
• Introduction
• Hydraulic boundary conditions
• Lifting method
• Validation method
• Results
• Conclusions and recommendations
30 June 2015

3. Introduction - motivation
• According to the Dutch Water Act
(“Waterwet, 2009”) the strength of the
Dutch primary water defences must be
checked with a certain periodicity for
the required level of protection of 300
to 100,000 year loads.
• The assessment is carried out using
the: Hydraulic Boundary Conditions
(HBC).
30 June 2015

4. Introduction - motivation
• The current computations of the HBC
rely mostly on the statistical
distribution of the basic variables at
(solely) the peak of the storms.
• Depending on the failure mechanism
under consideration, the combination
of the values of the basic variables at
the peak of the storm may lead to
lower failure probabilities than the
probabilities based on combinations at
other instants around the storm peak.
• To improve the accuracy of the HBC
time evolving hydraulic loads along the
water defences are needed.
30 June 2015

5. 30 June 2015
Introduction - motivation
• To produce a set of time evolving hydraulic loads along the water
defences the numerical models will in the future use time and space
varying wind fields.
• For this purpose, wind fields need to be lifted. Two leading experts
in extreme value theory, Prof. Laurens de Haan and Prof. Richard L.
Smith were consulted for advice on how to approach the problem,
i.e. on how to model extreme time and space evolving multivariate
extremes.
• Both experts have recommended the use of max-stable method.
Hydr.
model
Wave
model

6. Introduction – max-stable method
The max-stable method involves:
1. EVA of time series at each
location
2. Augmentation of the local EVA
fits by the empirical distribution
3. Selection of ‘storm’ periods
4. Transformation of the time
series to unit GPD marginal
distributions
5. Uplifting of the transformed
‘storm’ data
6. Inversion of the marginal
transformations: back to wind
speed!
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Wind speed
[m/s]
time
threshold level

7. Lifting methods - choices
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• Reference location (S0)
• Peak wind velocity level (L0) at ref.
loc. (S0) depending on the desired
return period
• Number of storms (n)
• Storm period (period before and after
the storm)
example
Lake
IJssel
(NL)
U10[m/s]
example
North Sea
U10[m/s]
Wind speed
[m/s]
time
L0

8. Lifting methods - result
In space and time varying wind fields
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Question: How real are these fields???? Validation of lifted fields necessary
Example time series at reference location:
original lifted

9. Introduction – objective
Validate the ability of the lifted fields to reproduce extreme hydraulic
conditions for a case study area
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• Area: Lake IJssel (NL)
• Wind data 1979 – 2013 from
HARMONIE model (KNMI)
• Using the hydrodynamic model WAQUA
and the spectral wave model SWAN
• Four different return periods have been
studied: 1/100, 1/1000, 1/4000 and
1/10000 year

10. Validation Method
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35-year Harmonie
wind hindcast
35-year hindcast
(surges, waves,
loads …)
lifted wind fields
of 30 storms with
1/100 year return period
3 days before and after
storm peak
extreme loads for 1/100
return period
Hydrodynamic
Models
mean values of
30 storms
Hydrodynamic
models
Full period
4 lifting methods
30 storm periods
1 reference location
Fixed threshold (99.5%)
Type 1 tail
Etreme value
Analysis
for every location and
parameter
Best local fit
example return period 1/100 year

11. Considered variables
• Wave load (∝ 𝐻𝑠
0.5
𝑇)
• Wave power (∝ 𝐻𝑠
2 𝑇)
• Storminess (mean of the significant wave height from 23h before
until 6h after the peak)
• Significant wave height
• Mean wave period
• Still water level
• Wind speed
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12. Considered output locations
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13. Results
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Full line: point estimates
Dashed line: 95% conf. interval
hindcast lifted

14. Results
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Wave load
comparison
Markers show mean
results at the locations
along the eastern
banks of Lake IJssel

15. Conclusions
• In terms of hydraulic loads, the return value estimates from the four
lifting methods are rather close to each other. Moreover, the
differences between the estimates of the different lifting methods
are in general lower than the differences between them and the
estimates from the hindcast data;
• Possible causes for the differences between the estimates from
the lifting methods and from the hindcast are fundamental
differences between what the estimates based in one and the
other type of data represent.
30 June 2015

16. Recommendations
• Further study is necessary to test the pragmatic choices that have
been made in lifting the wind fields;
• Study the effect of the number of storms and the reference
location.
30 June 2015