long-term bathymetry changes quest4d job janssens – flanders hydraulics research

Long-term bathymetry changes

Quest4D

Job Janssens – Flanders Hydraulics Research

• Available data• Interpolation

concerns

methodology

results

• Analysis of the gridsvisualization of the depth lines

trend analysis

chart differencing

conclusions

Outline

Available data

Selection of historical navigation charts:(charts available at Hydrography Department, Flemish Authorities)

2007 chart high resolution grid (20m x 20m)

other charts irregular pattern of data points

Example:Chart of 1938

Available data


datapoints 1938 digitized in ArcGIS

Available data




Available data




different charts have datapoints on different locations

interpolation of each set of datapoints to a grid

Available data

ArcGIS interpolation techniques:

IDW

kriging

natural neighbor

Problems associated with interpolation:

are averaging techniques

average value cannot be greater than highest or less than lowest input

in sparse data sets:

interpolation cannot reproduce ridges or troughs!

seafloor morphology flattened by interpolation

Interpolation: concerns

“straightforward” interpolation: test case

• 2007 data point set: - high resolution (20m x 20m) - no interpolation needed




• subset of the 2007 data point set




• subset of the 2007 data point set

• interpolation of this subset



difference chart: 2007 - 2007 interpolated

• ridges less higher than they are• troughs less deeper than they are

Conclusion:

interpolation of sparse data set flattens morphology

interpolation error correlated with location


Solution: use high resolution data of 2007 to estimate interpolation error

Example: grid of 1938

grid of 1938 = interpolation of data points 1938

interpolation of subset data points 2007

grid of 2007_

Interpolation: methodology

_

estimation of interpolation error

! Basic assumption:

data points of 2007, but only at locations of the 1938 data points

stable morphology: no major changes in location of ridges/troughs

Interpolation: illustration methodology

1866

Interpolation: results

1908


1938


1969


2007


1) visualization of different depth lines

2) trend analysis

3) chart differencing

Erosion/sedimentation patterns studied through:

Analysis of the grids

1) visualization of depth lines:


Example: Middelkerkebank, 8m depth lines

2) Trend analysis:


linear least square fit on time series of depth values

sedimentation trend

~ 0.03 m/year

(time series of 5 depth values for each grid cell)

2) Trend analysis:


3) Chart differencing:


Conclusions:


Morphologic changes:

• Anthropogenic:

dredging: of navigation channels (Scheur, Pas van ‘t Zand)

dumping: S1 (Sierra Ventana), …

influence of breakwaters Zeebrugge harbour: bay of Heist

• Natural:

no significant movement of the banks sedimentation/erosion: coastal banks form the most dynamic zone

sedimentation of the ridges (e.g. Oostendebank)

erosion of the troughs (e.g. Grote Rede, Kleine Rede)

long-term bathymetry changes quest4d job janssens – flanders hydraulics research

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