Sediment Properties in the Western Baltic Sea for Use in Sediment Transport Modelling

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Sediment Properties in the Western Baltic Sea for Use in Sediment TransportModellingAuthor(s): Bernd Bobertz, Christiane Kuhrts, Jan Harff, Wolfgang Fennel, Torsten Seifert, and BjörnBohlingSource: Journal of Coastal Research, Number 213:588-597. 2005.Published By: Coastal Education and Research FoundationDOI: http://dx.doi.org/10.2112/04-705A.1URL: http://www.bioone.org/doi/full/10.2112/04-705A.1

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Journal of Coastal Research 21 3 588–597 West Palm Beach, Florida May 2005

Sediment Properties in the Western Baltic Sea for Use inSediment Transport ModellingBernd Bobertz, Christiane Kuhrts, Jan Harff, Wolfgang Fennel, Torsten Seifert, and Bjorn Bohling

Baltic Sea Research Institute WarnemundeSeestrasse 1518119 Rostock, Germany

ABSTRACT

BOBERTZ, B.; KUHRTS, C.; HARFF, J.; FENNEL, W.; SEIFERT, T., and BOHLING, B., 2005. Sediment propertiesin the western Baltic Sea for the use in sediment transport modelling. Journal of Coastal Research, 21(3), 588–597.West Palm Beach (Florida), ISSN 0749-0208.

To simulate transport of clastic material in the Baltic a sediment transport module is linked to a Baltic Sea Modelthat is based on the Modular Ocean Model—MOM3. In order to describe the properties of the seabed sedimentparameters as mean grain size, critical shear velocity and bed roughness length must be provided as input data tothe numerical model system. To obtain maps of these quantities for the Baltic Sea area the proxy-target concept isapplied. As proxy-variable the mean grain size of the sediment types is used. For different sediment samples thecritical shear velocity was measured and serves as the target variable. Using the relation between the sedimentclassifications based on the mean grain size (proxy) and the measured critical shear velocity (target) a map of thecritical shear velocity in the Baltic is derived.

In January 1993 several extreme strong storm events occurred in the Baltic. Using this period for a model calcu-lation maximum values of current and wave induced bottom shear velocities were obtained. Comparing these modelresults with the critical shear velocity distribution provided by the proxy-target concept we identify potential erosionareas. Further we show the transport path of material initially deposited in the Mecklenburgian Bight.

ADDITIONAL INDEX WORDS: Sedimentology, numerical model, proxy-target, sediment map, risk of erosion.

INTRODUCTION

An important issue in modelling the marine ecosystem isa quantitative description of sedimentation, resuspension,and sediment transport processes. In the framework of coast-al zone management numerical modelling of these processesis important to estimate the effects of anthropogenic activi-ties to the marine ecosystem. The dynamics of sedimenttransport is complex and involves physical, geochemical, andbiological processes. In recent years different sediment trans-port models have been developed and applied to a large num-ber of problems (JANKOWSKI et al., 1996; HOLT and JAMES,1999; RIBBE and HOLLOWAY, 2001, PULS et al., 1994; BLACK

and VINCENT, 2001). Basically, these model studies considertwo different classes of problems: long-term changes in thebottom sediment distribution as result of morphodynamicalprocesses (ELIAS et al., 2000, HIRSCHHAUSER and ZANKE, 2001)and the investigation of sediment transport paths over someweeks or months (CHRISTIANSEN et al., 2002).

Our study is aiming at the latter type of problems, focus-sing on processes of erosion, transport, and deposition of ma-terial in relation to anthropogenic processes such as dumpingor dredging in the western Baltic Sea. For the model calcu-lations the Institute Warnemunde Baltic Sea Model includinga sediment transport model is used.

To quantify sediment transport rates in the numericalmodel, several parameters such as sinking velocity or critical

DOI:10.2112/04-705A.1 received and accepted in revision 29 April2004.

shear velocity (e.g. CSANADY 2001) for sedimentation and re-suspension must be provided to the model. These parametershave to be measured or may be adjusted by published data.Usually, available data sets are uneven, and hence inconsis-tently distributed over the area. To regionalise such data theproxy-target concept (HARFF et al., 1992) can be applied. Thisconcept allows to substitute missing model parameters (tar-gets) by proxy-variables available for the area of research.The relation between proxies and targets is investigated inkey areas, where good data sets are available and which rep-resent the sedimentological variability of the entire area ofinvestigation.

Our aim is to implement and test a sediment transportmodel to describe natural erosion, transport, and depositionprocesses as well as processes related with dredging anddumping. Case studies were performed in the Mecklenbur-gian Bight located in the western Baltic Sea.

This study is part of the project Dynamics of Natural andAnthropogenic Sedimentation (DYNAS) funded by the Ger-man Federal Department of Education and Science (Code:03F0280A, http://www.io-warnemuende.de/projects/dynas/index.htm).

INVESTIGATION AREA

The present study aims at the area of the western BalticSea, that is part of the transition zone for water exchangebetween the Baltic Sea and the North Sea, see Figure 1. Thecirculation is highly variable and currents develop in re-

589Sediment Transport Modelling

Journal of Coastal Research, Vol. 21, No. 3, 2005

Figure 1. The western Baltic Sea. DEM data by GFDL (2000), bathymetric data by SEIFERT and KAYSER (1995), geographic data by ESRI (2002), projectionEurope: Mercator on WGS84, projection western Baltic Sea: UTM32 (km) on WGS84.

sponse to pressure gradients caused by differences in the sealevel between the Baltic and the Kattegat and local wind forc-ing, see e.g. FENNEL and STURM, 1992, and SCHMIDT et al.1998. In a tideless sea like the Baltic waves play an impor-tant role for the sediment transport by stirring up depositedmaterial from the sea bottom which then can be transportedby the currents.

The distribution of surface sediments has been investigatedby many authors (e.g. EMELYANOV et al., 1994; JENSEN et al.,1996; LEMKE, 1994, 1998; LEMKE et al., 1994; NIELSEN et al.,1992; TAUBER and LEMKE, 1995; TAUBER et al., 1999). Fine andmedium sands are predominant at the sills and the othershallow regions. On top of submarine outcropping glacial tilland along the coastlines lag sediments, mainly coarse sand

590 Bobertz et al.


Figure 2. Schematic overview of the Baltic Sea Model.

Figure 3. Data sources. 1. Winterhalter et al. (1981); 2. Repecka andCato (1999); 3. Bobertz (2000); 4. Anonymous (1987); 5. Bohling (2002).Geographic data by ESRI (2002), projection: Mercator on WGS84.

and gravel, can be found. Glacial till and glaciofluviatilesands form the main sources for selective transport and de-position of sediments. In the deeper parts silt accumulates.

PROXY-TARGET-CONCEPT

The input parameters which are required for the modellingof sediment transport are:

—critical shear velocity for erosion and deposition (u ),*crit

—bed roughness length z0,—mean grain size (md).

Information about the grain size distribution of the Baltic Seabottom is available either as data sets or sediment maps. Val-ues of critical shear velocity for erosion have been determinedexperimentally for different sediment samples.

In order to provide complete data sets for the model setupwe have to interpolate the data gaps. This was achieved withthe proxy-target-concept (HARFF et al., 1992). According tothis concept a set of longitude and latitude vectors r ∈ R isassigned to the seabed. The bottom sediments are describedby sedimentological variables X. Making use of proxy vari-ables XP(r), XP , X, ∀r ∈ R (as grain size parameters), whichare available in the entire area of investigation, target vari-ables (as physical sediment properties), measured only in aselected key area R9 , R, are predicted for the entire area.To solve this problem the knowledge of the relationship XT 5f(XP) is required. An empirically estimated regression func-tion is derived from the measured values of proxy and targetvariables in the key area.

The grain size data (proxy) used in this study are not avail-able as primary quantitative data, but as semi-quantitativedata in form of sedimentological maps. Therefore, the region-alisation of the grain size is basing on the classificationschemes (legends) of primary data used for the mapping. Forthis purpose we determine first a partition (classification) ofsediments based on the grain size legend of the maps (proxyvariable) ZP 5 {X , X , . . . , X }. Classes X are described byP P P P

1 2 K K

the grain size intervals of the different data sources. For a

key area samples are taken (random sample) and grain sizeparameters (proxy) as well as the critical shear velocity astarget variable are measured. We assign these samples bytheir grain size to the division ZP. For the samples we mea-sure the target variables and wind up with a second divisionZT 5 {X , X , . . . , X }. Each of the classes X is described byT T T T

1 2 K j

averaged values of the measured data. The investigation of fis now simplified to ZT 5 f(ZP). This relation is used to re-gionalise the target variables. To each model grid node a classof the partition ZP is assigned according to the grid node’slocation at the sedimentological map. On the base of the re-lation ZT 5 f(ZP) the averaged values of the target variablesare selected and assigned to the grid node.

DISTRIBUTION OF SURFACE SEDIMENTPROPERTIES

Map of Sediment Types

As data sources we made use of five sediment maps (BOHL-

ING, 2002; BOBERTZ, 2000; REPECKA and CATO, 1999; ANONY-

MOUS, 1987; WINTERHALTER et al., 1981). The areas covered bythese maps are outlined in Figure 3.

We consider in the following four sediment classes reflect-ing the main surface sediment types of the Baltic Sea: mud,fine sand, medium to coarse sand, gravel and hard rock. Theparameters describing the sediment properties of these fourmodel types are presented in Table 1. The assignment be-



Table 1. Sediment types and their properties used for the sediment trans-port model as input data. The mean grain size is denoted by md, z0 is theroughness length, and u*crit the critical shear velocity for erosion.

Model type md (mm z0 (cm) u*crit (cm/s)

SiltFine sandMedium sandHardrock

20130250

0.0050.0330.0630.125

4.01.41.6

infinite

Figure 4. Sample sites, location of samples for u measurements, and*crit

sediment types obtained within the key area. Geographic data by ESRI(2002).

tween the sediment types used in the five sediment maps andour four-class subdivision is given in Table 2.

The assignment was done for each of the five sedimentmaps and the resulting maps were combined within a GIS(ArcView, ESRI, 1998). In some areas the information of dif-ferent maps overlapped and therefore the maps were rankedby their grade of detail—the more detailed maps were rankedhigher. Then in the overlapping areas the information of thehighest ranked map was used (see Table 2).

Figure 5 shows the resulting sediment map based on thefour-class division we made. The artificial border in the cen-tral part of the map (Figure 5) reflects the transition fromthe low detailed overview map of WINTERHALTER et al. (1981)in the north to the high detailed map of REPECKA and CATO

(1999) describing the surface sediments in the central BalticSea. A second artificial border zone appears in the southernpart of the map easterly of Bornholm island resulting from agap between the maps of REPECKA and CATO (1999) and BOB-

ERTZ (2000). However, the area of investigation is located inthe south-western Baltic Sea were the derived sediment mapis consistent.

Sediment Type Properties

In order to assign the target variables to the regionalscheme surface sediment samples were taken within the keyarea (Figure 4). This area, which is a transition zone betweena coastal area and a depositional basin, represents almost theentire sedimentological variability of the Baltic Sea’s surfacesediments. For samples marked additionally within Figure 4the critical shear velocity for erosion (u ) was measured us-*crit

ing an erosion chamber and a flume (ZIERVOGEL and BOHLING,2003; SPRINGER et al., 1999). The averaged measured data aregiven in Table 1 representing the target division ZT. The crit-ical shear velocity for erosion of mud could not be identifiedwith the instruments, because only bottom shear velocitiesup to 2 cm/s could be generated. For the model calculationswe have adopted a value of 4 cm/s for the critical shear ve-locity of mud according to the literature data (TOLHURST etal., 2000; AUSTEN et al., 1999; AMOS et al., 1997). In additionto u the mean grain size (md) calculated from the measured*crit

values is given in Table 1. The bed roughness length (z0) isestimated from md using the common relation z0 5 2.5·md/30 (SOULSBY, 1997).

The relation ZT 5 f(ZP), expressed by the data in Table 2,is used to parameterise the model by assigning a parametervector (md, u , z0) to each grid node according to the map*crit

in Figure 5 (regionalisation).

THE BALTIC SEA MODEL

The model system consists of five components (Figure 2): aparametric atmospheric boundary layer model, a circulationmodel basing on the MOM3 (Modular Ocean Model, PACA-

NOWSKI and GRIFFIES, 2000) code, a parametric wave model,an analytical bottom boundary layer model, and a sedimenttransport model.

To calculate the currents, temperature, and salinity in re-sponse to the atmospheric forcing and river discharges weoperate a circulation model basing on the Modular OceanModel MOM-3.1. We use an implementation with an explicitfree surface scheme involving tracer conservation propertiesas described in GRIFFIES et al. (2001). The model covers thewhole Baltic Sea and has an open boundary to the North Sea.For the model topography we use a digitised map of the BalticSea given by SEIFERT et al. (2001). The horizontal resolutionof the model is 3 nautical miles (nm 5 1852 m) in the westernBaltic and the vertical resolution is 3m.

To calculate the bottom shear velocity we apply a bottomboundary layer model schematically shown in Figure 2. Inthe shallow parts of the western Baltic the bottom shearstress is dominated by waves. To estimate the bottom shearstress induced by waves and currents we apply a model pro-posed by GRANT and MADSEN (1979). In this approach a log-arithmic velocity profile inside and above the wave boundarylayer is assumed. Using an iterative procedure the current-induced shear velocity can be calculated. To estimate thewave-induce shear velocity the parameterisation of NIELSEN

(1992) is used. The total bottom shear stress consists of twocomponents: (1) form drag as a result of pressure differencesgenerated by larger structures of the seabed and (2) skin fric-tion which is the relevant component for the sediment trans-port process. To extract the current-induced skin friction ve-locity from the total shear velocity calculated with the modelof GRANT and MADSEN we use the concept of SMITH and MC-

LEAN (1977). In this approach the existence of a thin bottom-

592 Bobertz et al.


Table 2. Assignment of sediment types of the data sources to the model sediment types. Some maps are fragmented into parts with separate legends foreach part, marked by letters indicating the geographical location of the fragment (e.g. 1n means sediment type 1 of the northern part of the map). The mapswere ranked by their grade of detail in order to decide which information has to be employed in the case of overlapping maps.

Model typeWinterhalter et al. (1981)

rank 1Repecka and Cato (1999)

rank 2Bobertz (2000)

rank 3SDH-DDR (1987)

rank 4Bohling (2002)

rank 0

1234

7n, 8n, 9n, 10n, 7s, 8s, 9s5n, 6n, 6s3n, 4n, 3s, 4s, 5s1n, 2n, 11n, 2s, 10s

14w, 18w, 15e, 16e, 17e12w, 9e, 13e10w, 11w, 10e, 7e, 8e, 19e1w, 2w, 3w, 4w, 2e, 3e, 4e, 5e, 6e

123

0, 1, 2345, 6

12, 34, 5, 6

Winterhalter et al. (1981)(n, northern part, s, southern part)

Map-Type Description Model-Type

1n2n3n4n5n

Hard bottom (till, also bedrock)Hard bottom with minor sand depositsHard bottom and sand bottom equally distributedSand bottom (sand and gravel)Sand bottom with minor soft bottom areas

44332

6n7n8n9n

10n

Sand bottom and soft bottom equally distributedSoft bottom with minor sand bottom areasSoft bottom (silt, clay and mud)Soft bottom with minor hard bottom outcropsSoft bottom and hard bottom equally distributed

21111

11n1s2s3s4s

Hard bottom with minor soft bottom areasSand bottom with minor soft bottom areasHard bottom (till, also bedrock)Hard bottom and sand bottom equally distributedSand bottom with minor hard bottom areas

34333

5s6s7s8s9s

10s

Sand bottom (sand and gravel)Sand bottom and soft bottom equally distributedSoft bottom (silt, clay and mud)Soft bottom with minor hard bottom outcropsSoft bottom and hard bottom equally distributedHard bottom with minor soft bottom areas

321114

Repecka and Cato (1999)(w, western part, e, eastern part)1w2w3w4w

10w

Crystalline bedrockSedimentary bedrockGlacial deposits (till)Clay of the Baltic Ice Lake, the Yoldia Sea, and the Ancylus LakeSand (2.0–0.06 mm)

44443

11w12w14w18w2e

Coarse and medium sand (2.0–0.2 mm)Fine sand (0.2–0.06 mm)Coarse silt (0.06–0.02 mm)Gyttja clay and clay gyttja (Litorina and postlitorina Sea)Sedimentary bedrock

32114

3e4e5e6e

10e

Glacial deposits (till)Clay of the Baltic Ice Lake, the Yoldia Sea, and the Ancylus LakePebble (100–10 mm)Gravel (10–1 mm)Sand (1–0.1 mm)

44443

7e8e9e

13e15e

Coarse sand (1–0.5 mm)Medium sand (0.5–0.25 mm)Fine sand (0.25–0.1 mm)Coarse aleurite (0.1–0.05 mm)Fine aleurite (0.05–0.01 mm)

33221

16e17e19e

Aleurite pelitic mud (50-70 percent , 0.01 mm)Pelitic mud (.70 percent ,0.01mm)Mixed sediments

113

Bobertz (2000)321

MudFine sandMedium to coarse sand

123



Table 2. Continued.

Model typeWinterhalter et al. (1981)

rank 1Repecka and Cato (1999)

rank 2Bobertz (2000)

rank 3SDH-DDR (1987)

rank 4Bohling (2002)

rank 0

1234

7n, 8n, 9n, 10n, 7s, 8s, 9s5n, 6n, 6s3n, 4n, 3s, 4s, 5s1n, 2n, 11n, 2s, 10s

14w, 18w, 15e, 16e, 17e12w, 9e, 13e10w, 11w, 10e, 7e, 8e, 19e1w, 2w, 3w, 4w, 2e, 3e, 4e, 5e, 6e

123

0, 1, 2345, 6

12, 34, 5, 6

Winterhalter et al. (1981)(n, northern part, s, southern part)

Map-Type Description Model-Type

SDH-DDR (1987)0123456

Schlick (mud)Schlick sandig (mud, sandy)Sand schlickig (sand, muddy)Feinsand (fine sand)Mittelsand (medium sand)Grobsand (coarse sand)Kies, Rest-bzw, Mischsedimente (gravel, relict and mixed sediments)

1112344

Bohling (2002)123456

Mud (‘‘Schlick’’)Muddy fine sandWell sorted fine sandPoorly sorted fine to medium sandWell sorted medium sandWell sorted medium to coarse sand

122333

Figure 5. Map of the four sediment types used in the sediment transportmodel. The artificial borders resulting from the different data sources areoutside the area of investigation and therefore not relevant for this study.Geographic data by ESRI (2002), projection: Mercator on WGS84.

near sublayer is assumed, where the grain roughness is therelevant roughness for the velocity profile.

In the sediment transport model we consider two differentmechanisms for the transport of sedimentary material: trans-port in suspension and bed load transport. To calculate thetransport in suspension the following three-dimensionalequation is solved

]c ]1 =(c · u) 1 (c · w ) 5 =(v=c),sink]t ]z

where c is the sediment concentration, uW the current velocity,wsink the sinking velocity of the considered sediment type, andv the turbulent diffusion coefficient. To account for depositionand resuspension of material the following bottom boundarycondition is applied

]cc · w 2 v 5 Q.sink z[ ]]z bottom

The source term Q quantifies the amount of sediment whichis deposited or resuspended as a function of the bottom shearvelocity u*s

(w · c) , u* # u*sink bottom s dQ 5 0, u* , u* # u*

d s rq , u* , u* r r s

The parameters u*d and u*r are the critical shear velocitiesfor deposition and resuspension which are material parame-ters. To quantify the erosion rate qr we make use of a para-meterisation proposed by PULS and SUNDERMANN (1990)

qr 5 Mr(u 2 u ),2 2* *s r

where M is a material constant and r the water density. For

594 Bobertz et al.


Figure 6. Maximum of the critical shear velocity u* (upper panel) and maximum erosion risk (u* 2 u ) (lower panel) for the model period of January*crit

1993.

the bed load transport a two-dimensional equation for thebottom sediment concentration CA is solved

]CA 1 =q 5 2Q.b]t

To quantify the amount of transported material the para-meterisation of MEYER-PETER and MULLER (1948) is applied

1.524u*s3q 5 r Ï(s 2 1)gd 2 0.188 , u* . u* .b s d 50 s b1 2(s 2 1)gd50

The critical velocity for bed load transport u*b depends on thesediment type, s denotes the relative density of the sediment,rS the sediment density, and g the gravitational constant.

A more detailed description of the model system is givenin KUHRTS et al. (2002).

MODEL EXPERIMENT

As period for our model experiments we have chosen Jan-uary 1993 because of the occurrence of extreme strong windevents. First we discuss the shear velocities predicted by the



Figure 7. Vertically integrated concentration of fine sand on a logarithmic scale at the end of two the periods in January 1993. The asterisks indicatethe source locations.

model in the western Baltic. In the shallow parts of the Balticthe maximum shear velocities are dominated by the wavecontribution. The current-induced shear velocities are limitedto a value of 0.2 cm/s. The maximum of the shear velocitycalculated for every grid point is shown in Figure 6 (upperpanel). These maximum shear velocities allow an identifica-tion of potential erosion areas. Using the critical shear veloc-ities given in Table 1 for the four bottom sediment classes ofour model we find the regions where the critical shear veloc-ity for erosion was exceeded, shown in Figure 6 (lower panel).Significant sediment transports can be expected in the areassouth off the Danish islands, southeast off the Darss Sill, aswell as on the Oderbank and on the Ronne Bank.

The model can also be used to study the transport of sed-imentary (non cohesive clastic) material added to the system.As an example we consider an artificial sediment source lo-cated in the southern Mecklenburgian Bight. The source ismarked by the asterisk in Figure 7. The spreading of finesand is studied for two periods of two weeks under the forcingconditions of January 1993. In the beginning of each model

run the source is initialised with 30,000 tons of fine sand. Tocalculate the transport rates we have used the following val-ues for the material parameters of the fine sand: a sinkingvelocity of 0.4 cm/s, a critical shear stress velocity for bed loadtransport of 1.1 cm/s, and a critical shear stress velocity forresuspension of 1.4 cm/s. To compute the bed load transportrates we apply the parameterisation of MEYER-PETER andMULLER (1948). The rates for resuspension are calculated bythe parameterisation of PULS et al. (1994). In Figure 7 thecalculated distribution patterns are shown at the end of eachperiod. To display a wide range of the concentrations we usea logarithmic scale. During the first model period (30.12.1992–13.01.1993) almost no transport of sand was predictedby the model, although strong storms have passed the west-ern Baltic. In the second period (14.01.1993–28.01.1993),when strong storms were related to a major Baltic Sea inflow,a strong transport of sedimentary material directed to northand northeast is predicted by the model. The fine sand istransported to the northeast and partly deposited in the Ka-det Channel.

596 Bobertz et al.


CONCLUSION

The proxy-target-concept has been proven to be a suitabletool to parameterise a regional sediment transport model. Forthe strong wind period January 1993 maximum values of cur-rent- and wave-induced bottom shear stress velocities havebeen calculated by the model. Comparing these results withthe critical shear velocities for erosion, provided by the proxy-target concept, potential erosion areas are identified, whichare the Oderbank, the Darss Sill Area, and the Ronne Bank.For an artificial sediment source located in the Mecklenbur-gian Bight transport paths were studied which are stronglydepended on the wind forcing.

For further studies an improved map of the sediment typedistribution, and a higher horizontal model resolution of 1 nmshould be used in order to reflect the sediment transport pro-cesses in more detail.

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