Workshop quantitative bed dynamics from new bathymetric time series of the Netherlands continental shelf

1. Deltares
Thaiënne A.G.P. van Dijk
Tommer Vermaas
Delft Software Days – Data Science workshop
28 October 2015
Quantitative bed dynamics
from new bathymetric time series
of the Netherlands Continental Shelf

2. Workshop Data Science
16:00 – 16:30
• Presentation of methods, project results and applications of
quantitative bed dynamics – Thaiënne van Dijk
16:30 – 17:10
• Demonstration of bathymetric time series on OpenEarth.nl and
examples of analyses – Tommer Vermaas
17:10 – 17:30
• Discussion, suggestions from you as users &
time to access the data
2
Introduction

3. Presentation
• Relevance
• Data
I. Quantification of vertical nodal dynamics
- method, results, applications
II. Quantification of vertical nodal dynamics in dredged areas
- idem
III. Quantitative analysis of individual bedforms
- idem
• Conclusions
3
Introduction

4. 4
Relevance of sea- and river bed dynamics
• Dynamic bedforms
• Safe navigation
• Monitoring and maintenance policies
(naval charting, dredging,
nourishments)
• Offshore and coastal engineering:
studies of seabed dynamics in the
North Sea for e.g. offshore wind
farms, pipelines and cables, or
marine aggregates
Bathymetry
[m -GLLWS]
+ 2.72 m
- 71.07 m
Bathymetry NCS
(TNO, 2004)
Rationale

5. Relevance of sea bed dynamics
5
Rationalegcaptain.com
MSC Napoli, off the coast of Devon,
UK (with explosives)
Forwairey , Western Scheldt, 2005 (photo ANP),
Flinterstar, off the coast of Zeebrugge,
Belgium, 2015
• Shipping: critical water depths
• Safety
• Environment
• Large economic benefit
transport: 15 cm extra
draught
• Marine Spatial Planning:
e.g. adjustment traffic
separation schemes (TSS)

6. Relevance of sea bed dynamics
• Shipping: critical water depths
• Offshore and Coastal Engineering
• Design and construction of
offshore wind farms
• Pipelines and cables
• Anchors of rigs
• Coastal constructions
6
Rationale

7. Relevance of sea bed dynamics
• Shipping: critical water depths
• Offshore and Coastal Engineering
• Monitoring and maintenance
policies:
• Resurvey policies
• Dredging of harbour approach
channels
• Coastal maintenance
(nourishments)
• Sand extraction (marine
aggregates)
7
Rationale
NLHO’s re-survey policy for
the NCS, 2007

8. 8
Acknowledgements
Rijkswaterstaat (RWS), Ministry of
Infrastructure and the Environment
Netherlands Hydrographic Office
(NLHO), Royal Netherlands Navy
Data

9. 9
Hydrographic surveys
• length: 75.0 m, width: 13.1 m
• DGPS
• SBES, MBES, SSS, sound
velocity profiler, box corer
Hr. Ms. Snellius
Netherlands Hydrographic Office,
Royal Netherlands Navy
RV Zirfaea
Rijkswaterstaat, Dutch Ministry of
Infrastructure and the Environment
• length: 63.0 m, width: 11.5 m
• 2 x Sercel 203 DGPS
• DP, SBES, MBES, SSS,
seismic instruments, box corer
Data

10. 10
Available data NCS
• All bathymetric data in NLHO’s
Bathymetric Archive System (BAS)
• NLHO & RWS
• SBES & MBES
• Late 1980s – June 2010 (update
2014)
• Non-digital data NLHO (fair sheets)
• Wrecks/Objects point data set
(NLHO & RWS)
• Maritime data (AIS-database)
• Seabed sediments
(TNO & Deltares digital map)
• Hydrodynamics
(MATROOS-database)
NLHO BAS
Data

11. 11
Available data NCS
MBES
530100 530150 530200
5743000
5743050
5743100
595250 595255 595260
5805890
5805895
5805900
100 x 100 m 10 x 10 m
SBES
Reasons of uncertainty (precision) in dynamic calculations:
• Width SBES beam: first reflection (shallowest point within beam)
• MBES: velocity profiles, footprint, etc.
• Horizontal positioning and data resolution
• Tidal reduction
• Shallowest point selected on fair sheets
• Digital data from BAS:
reduction to 1 observation
per 3 x 5 m
• Digitised fair sheets at lower
resolution
Data

12. Automated methods for quantifying bed dynamics
12
Methods
• Fully-automated method for the quantification of vertical bed dynamics.
The method can deal with large data sets and high-resolution data.
• organises the data spatially per survey,
• creates interpolated grids (5x5 km) (DEMs) at
user-defined resolution of all surveys in time,
• defines unique overlaps of surveys in time
series using metadata and
• quantifies statistics per grid node, e.g.
• mean z
• min z, max z
• dz/dt

13. • Surveys
• Digital Elevation Models (DEMs)
13
x
z
y
dz/dt (morphodynamic trend)
label (e.g. n, stdv)
Method I: Quantification vertical dynamics NCS
Methods

14. Method I: Quantification vertical dynamics NCS
• Vertical nodal bed dynamics [m/
year] based on the time series
14
y = 0.2724x + 0.5286
R² = 0.4908
0
1
2
3
4
5
0 2 4 6 8 10
(c) node (0,0)
x
z
y
dz/dt (morphodynamic trend)
label (e.g. n, stdv)
Methods

15. 15
Product I-a: Bathymetric map
Time series of DEMs:
• Quantified vertical dynamic
trend through entire time
series (“dynamic DEM”)
• 25 x 25 m cells
DEM of most recent echo soundings
Digital Elevation Model (DEM):
mosaic of most recent bathymetry:
• recognises most recent in time
series
• 25 x 25 m cells
Results

16. 16
Product I-b: Vertical nodal dynamics NCS (m/yr)
• Corrected for tidal-
reduction effects
Relatively dynamic on NCS:
• north of Texel
• west of Texel
• southern part with bedforms
• antropogenic
Results
Coast is dynamic:
• tidal inlets and
tidal channels
• estuaries
(Van Dijk et al., 2011)
‘Eurogeul’
offshore

17. 17
Product I-b: Simplified map of dynamics NCS
Non-dynamic areas NCS:
• > 30 m deep
• north of Wadden islands
• zone offshore North-Holland
• locally offshore South-Holland
and Zealand
Dynamic areas NCS:
• Long bed wave field (n. Texel)
• Sand wave field (w. Texel)
• Southern NCS with bedforms
Results

18. Comparison to study of German Bight
• Bed elevation range (m)
• data 1982 - 2004
(Winter, 2011)
Literature

19. Product I-c: statistics per node
• number of surveys per grid node
• water depth, mean z
• min_z, max_z, max_diff
• standard deviation of z
• dz/dt
• dz/dt_corrected
• goodness of fit of the linear trend
19
Results

20. 20
Application I: risk-based resurvey policy
Applications
• Aim: validation & optimisation of re-survey policy NLHO
GIS-overlay method:
• re-survey policy
• combined grounding dangers for ships
(based on AIS-data)
• morphodynamics (dz/dt) as predicted
water depths

21. Application I: risk-based resurvey policy
Applications
• Object grounding• Regular grounding

22. 22
Application I: risk-based resurvey policy
• Development of combined grounding danger in the future based on
predicted water depths identify when areas need to be re-surveyed
2010 to 2015 2010 to 20202010 to 2011
Applications
(Van Dijk et al., 2011)

23. Harbour approach areas and channels
23
Bathymetric time series:
• Approach channels surveyed
up to 12 times per year
• Offshore approach areas
surveyed 1 time per year
• Higher spatial resolution
(1-m grids)
• but also dredged regularly
Data

24. 24
Methods
Method II: nodal dynamic trends in dredged areas
• ‘Maasgeul’

25. Method II: nodal dynamic trends in dredged areas
25
Methods
• Automated recognition of dredging operations
• Nodal dynamic trends in between dredging operations (red lines)
correspond well to autonomous trends in bed level
• Broken trend line algorithm (blue line): fits through increased bed
level rise after dredging; applies one trend in each part
• dz/dt through entire time series (green line) is not valid in dredged
areas

26. Products: vertical nodal dynamics (m/yr)
• ‘Maasgeul’
• linear trends
(dz/dt, m/yr)
between
dredging
operations
per year
26
2009
2013
Results

27. Application II: dredging strategy
27
• Large operation → higher
sedimentation rate
• immediately after dredging
operation (2 months) :
higher sedimentation rate
• “Recovery effect”
• Linear trend:
underestimation immediately
after dredging
All grid nodes in km 5
that were dredged
Applications

28. 28
Application II: dredging strategy
Applications
• Period to exceeding of the bed level before the dredging operation
• Deeper dredging is less efficient (in terms of “recovery time”)
0.4 m → 4 days/cm
160 days
0.8 m → 3 days/cm
240 days
Twice as deep, but
1.5 time to recover

29. Vertical dynamics NCS
• sand waves west of Texel

30. 30
Marine bedforms
(e.g. Ashley, 1990; *local observation by Knaapen et al., 2001)
Compound sand wave
• descriptive parameters
• small slope
Bedform Wavelength
(m)
Height
(m)
Orientation
(degrees to
tidal current)
Morphodynamic
time scale
(order of years)
Offshore sand banks
(tidal ridges)
1 000– 10 000 5 - 50 0 - 30 centuries
Long bed waves* 1 000 – 2 000 1 - 10 60
Sand waves 100– 1 000 1 – 10 90 years-decades
megaripples 7 – 40 < 1 90 hours

31. 31
Method III: Morphodynamics individual bedforms
• Semi-automated method for the separation of the bathymetric signal
into bedforms of different scales with truncated Fourier series
Methods
• semi-automated identification
of crest and trough points
• analysis of geometry and
morphodynamics
(Van Dijk et al., 2008)

32. 32
Morphodynamics individual bedforms
Results
• Migration
• Growth
TWIN profile 1 (southwest to northeast)
-36
-34
-32
-30
2500 2700 2900 3100 3300 3500
distance along profile [m]
bedelevation[m-LAT]
Jan-91
Jun-92
Apr-94
May-95
Mar-99
Feb-01
May-01
Mar-03
Apr-04
Apr-05
Oct-06
SW NE
STW SMARTSEA-project PhD-student:
• Automated method for high-resolution analysis of all sand waves
• Heights, shapes and dynamics
Sand-wave migration rates NCS
spatially variable:
• mostly 0 – 5 m/yr
• west of Texel: > 17 m/yr
• tidal inlets: up to 90 m/yr

33. Application III: Offshore Wind Farm Borssele
• Sand waves migrate
to the southwest
(ebb direction)
as well as to the
northeast (flood
direction)
• 3 bathymetric data
sets in time
33
Applications
IV
I
II
III
Schematized and simplified
migration directions
(Hasselaar et al., 2015)

34. • Separation of different types
of bedforms
• Identification of sand wave
crests and troughs
• Track identified points in time
• Obtain statistics per transect
Application III: Offshore Wind Farm Borssele
Applications
(Hasselaar et al., 2015)

35. Application III: Offshore Wind Farm Borssele
35
• Exceedance
curves for
2010/2015
wavelength wave height
migration
distance
migration
speed
Applications

36. Application III: Offshore Wind Farm Borssele
• Used to predict the minimum and maximum bed levels for the
lifetime of the wind farm (per year for 30 years)
• Resulting in a classification of zones that are preferred or
unrecommended as wind pile locations
36
Applications
(Hasselaar et al., 2015)

37. 37
Conclusions
• Dynamics of sea- and river beds are relevant to e.g. safe
navigation, offshore engineering, coastal maintenance and
marine spatial planning.
• Empirical studies of bed dynamics rely on bathymetric time
series

38. Further information
38
References to the literature in this presentation:
Hasselaar, R., Raaijmakers, T., Riezenbos, H.J., Van Dijk, T.A.G.P., Borsje, B.W. and Vermaas, T.
(2015). Morphodynamics of Borssele Wind Farm Zone – WFS-I and WFS-II, Deltares report
1210520-000-HYE-0004, 62pp.
Van Dijk, T.A.G.P., R.C. Lindenbergh and P.J.P. Egberts (2008). Separating bathymetric data
representing multi-scale rhythmic bedforms: a geostatistical and spectral method compared.
Journal of Geophysical Research 113 (F04017).
Van Dijk, T.A.G.P., C. Van der Tak, W.P. De Boer, M.H.P. Kleuskens, P.J. Doornenbal, R.P.
Noorlandt and V.C. Marges (2011). The scientific validation of the hydrographic survey policy
of the Netherlands Hydrographic Office, Royal Netherlands Navy. Deltares, Report
1201907-000-BGS-0008: 165 pp. http://kennisonline.deltares.nl.
Winter, C. (2011). Macro scale morphodynamics of the German North Sea coast. Journal of
Coastal Research SI 64(Proceedings of the ICS2011, Poland): 706 - 710.
For further information,
• Thaiënne van Dijk, thaienne.vandijk@deltares.nl
• Deltares
Dept. of Applied Geology and Geophysics
Postbus 85467
3508 AL Utrecht

39. Next: Demonstration of Data
• time series on OpenEarth.nl and examples of analyses
• Bathymetric grids (5x5km)
• at 25 x 25 m resolution
• Tommer Vermaas, tommer.vermaas@deltares.nl
39

40. Hand-out workshop DSD 28th of Oct - bathy
• Hand-out DSD-INT-2015 Data Science workshop “Quantitative
bed dynamics from bathymetric time series” contains:
• OpenEarth.nl
• Information 3D pdf
• Useful links (URLs)
• Overview of metadata of the bathymetric time series
(DEMs 25x25m in 5x5km grids)
• Tools are to be open-source
40

41. 41
Discussion
• What applications do you see for these DEMs in time series on
OpenEarth?
• Do you have suggestions for the presentation of DEMs on
OpenEarth that would make the data best applicable to your
applications?
• Do you have suggestions (requirements) for the tools on
OpenEarth?