Geology, Morphology, and Sedimentology of Estuaries and Coasts

Abstract

The sedimentary rocks exposed at the surface of the Earth today consist primarily of volcaniclastics (~17.6%), graywackes (~2.6%), arkoses (~5.3%), quartz sandstones (~7.5%), mudrocks (~60%), limestones and dolomites (~6.0%), and evaporites (~1.0%). Together with the weathering products of igneous rocks, they form the source of the sediments supplied to the coasts of the world by river and glacier discharge. It is estimated that between 20 and 70  109 t of sediment are delivered to the coast every year. While the majority of beaches consist of gravels and sand, including various proportions of bioclastic material, some coasts remain muddy because wave action is unable to remove the large amounts of fine-grained sediments supplied by some rivers. The morphodynamic behavior of beaches is finely tuned between local grain size and wave climate, beach slope generally increasing with increasing grain size, but decreasing with higher wave energy so that for any given grain size, high-energy beaches tend to be flatter than low-energy beaches. Estuaries show a marked tripartite longitudinal zonation that is independent of tidal range. Both lower and upper estuaries are sandy and/or gravely, bioclastic material being restricted to the lower part. Middle estuaries, by contrast, consist of muddy sediments formed by flocculation processes in the mixing zone between saltwater and freshwater. Aggregates predominately consist of particles smaller than about 8 μm and are the main components of fluid muds found in many estuaries. Muds have higher water contents and hence lower bulk densities than sands so that 50:50 sand–mud mixtures contain more mud per unit volume than a 100% pure mud.

Full text

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Treatise of Estuarine and Coastal Science
Volume 3 / Chapter 2
Geology, morphology and sedimentology
of estuaries and coasts
Burghard W. Flemming
Senckenberg, Suedstrand 40
26382 Wilhelmshaven, Germany
bflemming@senckenberg.de
Citation:
Flemming, B.W., 2011. Geology, morphology and sedimentology of estuaries and coasts. In:
Flemming, B.W., Hansom, J.D. (Eds), Treatise on Estuaries and Coasts, Volume 3, Estuarine and
Coastal Geology and Morphology. Elsevier, Amsterdam, pp. 7–38.

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Synopsis
The sedimentary rocks exposed at the surface of the earth today consist primarily of volcaniclastics
(~17.6%), graywackes (~2.6%), arkoses (~5.3%), quartz sandstones (~7.5%), mudrocks (~60%),
limestones and dolomites (~6.0%), and evaporites (~1.0%). Together with the weathering products of
igneous rocks, they form the source of the sediments supplied to the coasts of the world by river and
glacier discharge. It is estimated that between 20 and 70  109 t of sediment are delivered to the coast
every year. While the majority of beaches consist of gravels and sand, including various proportions of
bioclastic material, some coasts remain muddy because wave action is unable to remove the large
amounts of fine-grained sediments supplied by some rivers. The morphodynamic behaviour of
beaches is finely tuned between local grain size and wave climate, beach slope generally increasing
with increasing grain size, but decreasing with higher wave energy so that for any given grain size
high-energy beaches tend to be flatter than low-energy beaches. Estuaries show a marked tripartite
longitudinal zonation that is independent of tidal range. Both lower and upper estuaries are sandy
and/or gravely, bioclastic material being restricted to the lower part. Middle estuaries, by contrast,
consist of muddy sediments formed by flocculation processes in the mixing zone between saltwater
and freshwater. Aggregates predominately consist of particles smaller than about 8 µm and are the
main component of fluid muds found in many estuaries. Muds have higher water contents and hence
lower bulk densities than sands so that 50:50 sand-mud mixtures contain more mud per unit volume
than a 100% pure mud.
Keywords:
Aggregates, barrier islands, bulk density, beach morphodynamics, beach slope, cliff retreat, coastal
erosion, coastal types, cohesive sediments, concentration, content, estuary types, fluid mud, grain size,
grain-size classification, gravel-sand-mud ratios, headland-bay beaches, heavy minerals, log-spiral
beaches, mass physical sediment properties, sand-silt-clay ratios, sampling strategies, sediment facies,
sediment sources, sortable silt, ternary diagrams, terrestrial supply, tidal flats, water content

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3.02.1. Introduction
This chapter aims to introduce the general characteristics of estuaries and coasts in terms of
geology, morphology and sedimentary characteristics, and to show how these dynamically interact
with environmental factors such as climate, weather patterns, river discharge, tidal currents and ocean
waves. Rock coasts are dealt with elsewhere (Trenhaile, chapter 9), so the present chapter concentrates
on the sedimentary systems of estuaries and coasts, touching on rock coasts only as a source of
sediment, particularly gravel (pebbles, cobbles and boulders).
Estuaries and coasts form the interface between the terrestrial and the marine realms but large
freshwater and saline lakes are excluded here since they are part of the terrestrial realm. Along open
ocean coasts, this interface generally implies land (and hence freshwater) on one side and oceans or
marginal shelf seas (and hence saltwater) on the other. However, in the vicinity of the mouths of some
high-discharge rivers, notably the Amazon, this saltwater criterion may fail because the boundary
between the two water bodies may be located up to several 10s of kilometers offshore, shallow coastal
waters thus being essentially fresh. Nevertheless, in the Amazon and other high-discharge rivers, an
important and often neglected marine influence is the effect of the rising and falling tide as the tidal
wave propagates up and down the lower course of the river.
In most ‘normal’ estuaries, this transition is even more subtle, mixing between saltwater and
freshwater (both vertical and horizontal) being characterized by progressive dilution of the one by the
other. Again it is commonly observed that the tidal wave mostly propagates farther upstream than does
the saltwater/freshwater interface. This interface is itself not stationary but moves along the estuary
over variable distances in response to changing volumes of river discharge and the rise and fall of the
tide, both on a daily basis and over the neap and spring tidal cycles. These interactions have important
influences on the nature and dynamics of the associated sedimentary systems.
The characteristics addressed above indicate that estuaries and coasts are not only influenced by
local environmental conditions, but are effectively impacted by events occurring on relatively short
time scales in the distant hinterland (e.g., strong rainfall resulting in high river and sediment discharge)
or far out in the open ocean (e.g., tides, storm waves and ocean swells, tsunami). The same applies to
the sediments feeding into these estuaries and coasts, except that such sediment may have been subject
to a long history of many cycles of weathering, erosion, transportation and deposition.
3.02.2. Geological constraints on sediment production
3.02.2.1. The igneous heritage of sedimentary rocks
Early crustal processes were dominated by volcanic activity and so the sedimentary deposits
produced at that time were entirely of extrusive magmatic, i.e. volcanigenic, origin. In the course of
time, and with the emergence of intrusive magmatic rocks, the variety and proportional contribution of
sediments increased rapidly at the expense of the volcanogenic component (Fig. 1). Today, the
volumetric proportions of the most important sedimentary rocks are roughly divided between marine
volcaniclastics (~15.0%), continental pyroclastics (~2.6%), graywackes (~2.6%), arkoses (~5.3%),
quartz sandstones (~7.5%), lutites or mudrocks (~60%), dolomites (~0.7%), limestones (~5.3%), and
evaporites (~1.0%) (Ronov, 1964; Garrels and Mackenzie, 1971). Each of these, in turn, is composed
of a variety of minerals and grain sizes that are likely to be found in different proportions in different
estuarine and coastal sedimentary systems, depending on the nature of the source rocks in the
catchments and along adjacent shores.

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Fig. 1. Relative contribution of different sedimentary rock types in the course of earth history (based on Ronov,
1964).
Examination of geological maps will reveal that the different types of sedimentary rocks forming
the upper crust of the earth today are not all of the same age. In a general sense, young deposits occur
more frequently than old deposits. However, looking at the survival of sedimentary rocks over time
(Garrels and Mackenzie, 1971), the trend from older to younger rocks is not characterized by a
steadily increasing progression, but instead by a saw-tooth pattern which suggests that rocks of some
geological periods have had a higher survival rate than others (Fig. 2). Thus, from the relatively low
survival of late Precambrian rocks (>600 Ma BP), the rate increases rapidly to reach a first peak in
rocks of Devonian age (345–395 Ma BP). Thereafter, the survival rate decreases just as rapidly to
reach a marked low in rocks of Permian age (230–280 Ma BP). A second peak, which is only
marginally lower than that of Devonian rocks, is reached in rocks of Triassic age (195–230 Ma BP).
This is followed by a small drop in the occurrence of Jurassic rocks (141–195 Ma BP), followed by a
continuous rise in the survival rate of Tertiary (2–65 Ma BP) and Quaternary rocks (<2 Ma BP). Not
unexpectedly, the youngest deposits are the most prominent because of their relatively short exposure
to weathering and denudation processes.
This peculiar zigzag-trend with pronounced peaks in Devonian and Triassic rock volumes requires
some explanation. The higher survival rates of rocks from some periods may be because of more
resistance to weathering and erosion, or there may have been more sediment being produced and
deposited in these periods. Although differential weathering and erosion may have played a supporting
role, the geological evidence suggests that higher sediment production is more plausible. The early
Devonian was not only a period of major geotectonic activity associated with the Caledonian Orogeny
(McKerrow et al., 2002) but, at the same time, the evolution of vascular plants reached the point where,
for the first time in earth history, large tracts of land began to be covered by dense vegetation (e.g.,
Willis and McElwain, 2002). Without a plant cover, large-scale erosion of weathered rocks and
resulting formation of huge sedimentary basins were the order of the day (e.g., Schumm, 1968; Dott
and Shaver, 1974). This can also be observed today where the destruction of the protective plant cover
usually results in severe erosion. Up to the Devonian period erosion and deposition were not inhibited

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by vegetation and, as a result, massive alluvial fans, deltaic deposits and basin fills accumulated, often
reaching many thousands of meters in thickness (e.g., Visser, 1974). This changed dramatically with
the evolution of higher plants, the production of sediment decreasing by as much as 50% (Schumm,
1968). The widespread development of huge coal deposits during the Carboniferous (Pennsylvanian)
bears witness to this effect that continued well into Permian times and may help explain the low
apparent survival of sedimentary deposits of this age.
Fig. 2. Survival of sedimentary deposits in the course of earth history (modified after Garrels and Mackenzie,
1971).
Towards the end of the Permian, environmental conditions changed so dramatically that it resulted
in the greatest mass extinction in earth history with >90% of marine and >70% of land organisms
disappearing (e.g., Benton and Twitchett, 2003). It was the time when the continents were
amalgamated into a single huge supercontinent known as Pangaea. Global warming, widespread
aridity and extensive lava outpourings severely decimated the global plant cover, the waters of
marginal sea basins evaporating to produce the thick salt deposits of the Late Permian (e.g. Tucker,
1991). Concurrently, increased mechanical erosion and resulting deposition, together with the
accumulation of massive marine limestone deposits, explain the high apparent survival of Triassic
deposits. The zigzag curve of sedimentary rock survival is thus composed of two major trends, one
reflecting survival without vegetation, the other with vegetation, the latter being interrupted by a major
climate-induced excursion peaking in the Triassic (hatched black and blue trend lines in Fig. 2).
The igneous heritage of sediments, however, is not restricted to the rock cycle, but is also reflected
in the mineral composition of the sediments themselves. As evident from Fig. 3, the mineral content of
every intrusive rock has an extrusive counterpart, with the exception of peridotite and dunite (both
rarely exposed on the earth surface). Thus, both granite (an intrusive rock) and rhyolite (an extrusive
rock) are, by definition, volumetrically composed of the same minerals, namely potash feldspar (40%),
plagioclase feldspar (15%), quartz (27%), mica (12%), and amphiboles (6%), the only difference being
the size of the minerals (Clark, 1966). Due to slow cooling, the minerals of intrusive rocks have had

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time to grow and are hence relatively large, whereas those of rapidly cooling extrusive rocks are much
smaller. As a consequence, the mineral grains produced in the course of weathering of these rocks
differ substantially in their size distributions. Metamorphic rocks, by contrast, comprise sedimentary
rocks that have been subjected to high temperatures and partial melting, in the course of which mineral
amalgamations and transformations have occurred. The particles produced by weathering in this case
span a larger grain-size spectrum. Carbonate rocks have either been derived directly by precipitation of
CaCO3 from waters supersaturated in the associated ions originally supplied by the dissolved loads of
rivers, or by the accumulation of bioclastic material produced by marine organisms (e.g., Bathurst,
1975).
Fig. 3. Proportional mineral composition (volume-%) of different intrusive and extrusive igneous rocks (based
on data of Clark, 1966).
Knowing the nature and composition of both sedimentary and igneous rocks, and depending on the
proportional distribution of rock types exposed within a river catchment or along a rocky shoreline, it
is possible to estimate overall grain sizes and mineral compositions of sediments delivered to adjacent
estuarine and coastal sedimentary systems. It must be borne in mind, however, that not every mineral
has the same resistance to mechanical abrasion or response to hydraulic transport. Quartz grains, for
example, are extremely resistant to mechanical wear and tear, whereas feldspars – if not already
transformed into clay minerals by in situ chemical weathering – are rapidly broken down into

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increasingly finer-grained fragments in the course of bed load transport because of their perfect
cleavage and resulting low resistance to mechanical forces (e.g., Suttner, 1989). As a consequence,
quartz generally tends to be enriched relative to other, less resistant minerals, especially in the course
of prolonged transport. However, close to their source, even less resistant minerals may form
dominant sedimentary components. For example olivine, a relatively unstable mineral, can be found in
abundance on some beaches of volcanic islands, lending to the sands a characteristic olive-colored hue.
In terms of transport behavior, both grain shape and grain density profoundly influence the
hydraulic response of different minerals. Thus, the higher specific gravity of heavy minerals (δ >2.9 g
cm-3; e.g. garnet, magnetite, diamond) leads to rapid segregation from quartz (δ = 2.65 g cm-3) in the
course of transport to produce anything from local heavy-mineral linings in cross-bedded sands to
large-scale, economically exploited, placer deposits enriched in particular heavy minerals or heavy
mineral suites. In the case of bioclastic material, it is the frequently dramatic departure in particle
shape from that of average quartz grains that produces mixtures of different geometric particle sizes
due to shape-controlled hydraulic sorting.
3.02.2.2 Tectonic and climatic controls on sediment production
If the solid earth were a static system then the redistribution of weathered material would
eventually have halted because the elevated areas would have long since become eroded with the
products of erosion filling every depression in the earth’s surface. The earth, however, is a dynamic
system, the continents ‘floating’ and ‘drifting’ on the upper mantle and moving in various directions at
speeds up to several centimeters per year in what has become known as ‘plate tectonics’ (e.g., Windley,
1995). With constantly changing configurations in the size and distribution of land masses and ocean
basins, this process is thought to have been going on for at least 3 billion years. Superimposed on this,
and partly driven by it, is the even more dynamic climate system, the two interacting on various time
scales to continually sculpture the face of the earth (e.g., Allen, 1997).
When considering structural processes in the context of sediment production, gradual, long-term
processes (mega-year scales) are distinct from comparatively rapid, short-term processes (kilo-year
scales). In the former case, epeirogeny (uplift and subsidence) can be distinguished from orogeny
(mountain-building and folding) (e.g. Longwell et al., 1969). In the course of continental denudation,
weathered material is constantly being removed from exposed land surfaces (sediment sources) to be
transported to continental margins or intracratonic basins (sediment sinks). Because the continents can
be viewed as floating masses, the removal of material causes source areas to be isostatically uplifted,
whereas sinks (sedimentary basins) gradually subside. Being a viscoelastic process (e.g. Quinlan and
Beaumont, 1984), this large-scale uplift and subsidence proceeds at variable speeds, ranging from
fractions of a millimeter to several millimeters per year depending on the regional tectonic activity
(endogenic processes of uplift and subsidence) and climate (exogenic processes of denuduation)(e.g.
Pirazzoli, 2005). This vertical movement eventually exposes at the earth’s surface formerly deep-
seated rocks (such as granite and gneiss) and allows those rocks, together with the rate of upward
tectonic forcing and the rate of surface denudation, to be dated via thermochronology (Rieners and
Ehlers, 2005). The uplift is partly counter-balanced by proportional subsidence of adjacent
sedimentary basins where, over time, huge amounts of sediment can accumulate. Both the rates of
production and removal of weathered rock material are controlled by climatic factors such as
temperature and rainfall. Due to changing global climates in relation to plate tectonic settings, these
effects have generally been unevenly distributed across the earth in the course of its history.
Orogeny (mountain-building) is the second major long-term process that promotes sediment
production. In the course of plate tectonics, continents collide and thereby fold up former sedimentary
basins into high mountain ranges where climate-controlled weathering and erosion, augmented by
gravitational processes such as slumping, sliding and avalanching, act together to gradually wear the

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mountains down. Tectonics (epeirogeny and orogeny), acting in conjunction with climate, relief and
lithology, thus controls the long-term rock cycle within which sedimentary processes play an
important role. Good summaries of these interactions can be found in Allen (1997), Leeder et al.
(1998), and Leeder (1999).
Besides these long-term tectonic processes, a number of factors acting on shorter time scales are
involved in landform development and associated sediment production. The most important of these
are volcanic activity, sea-level changes, and recent crustal movements such as earthquakes and hydro-
and glacio-isostatic adjustments that are subsumed under the term ‘neotectonics’ (e.g., Hancock and
Williams, 1986; Steward and Hancock, 1994; Pirazzoli, 2005). Volcanoes can contribute large masses
of material over short time periods and thereby substantially affect local sediment budgets, while fine-
grained airborne ash plumes may spread over large latitudinal areas. Sea-level changes, by contrast,
either raise (by forced transgression) or lower (by forced regression) drainage base levels worldwide
and thereby increase or decrease the accommodation space for sedimentary deposits (e.g. Vail et al.,
1977). Such base-level changes strongly affect the sedimentary systems of estuaries and coasts,
producing a variety of deposits that can be identified by characteristic spatial relationships in a
procedure known as sequence stratigraphy (e.g. Emery and Myers, 1996; Miall, 1997). During
regressive phases, material is removed from former estuarine, beach and nearshore repositories, to be
redeposited at corresponding lower positions around the new base levels (lowstand systems tracts). In
the course of subsequent sea-level rise, new accommodation space is created in the incised valleys and
on the newly developing shorefaces (transgressive systems tracts). When the rising sea eventually
stabilizes, the transgressive sedimentary sequences are capped by deposits known as ‘highstand
systems tracts’.
Finally, particular neotectonic crustal deformations affecting coastal zones are produced by hydro-
isostatic and glacio-isostatic adjustment (e.g. Peltier, 1998; Lambeck, 2005; Plater, this volume). The
former results from the loading of continental shelves during transgressive flooding (e.g., the sea-level
rise of ~130 m since the last glacial maximum). The one-sided loading may cause crustal flexuring
along coastlines and has in the Holocene generally been associated with the uplift (emergence) of
shorelines by up to several meters (Pirazzoli and Pluet, 1991). This can locally be counter-balanced by
subsidence around large deltas or be accentuated by isostatic rebound (of up to many tens of meters) in
response to the melting of glacial ice caps. In all cases, coastal and estuarine sedimentary systems are
affected in one way or another (cf. also Plater, this volume).
3.02.2.3. Modern terrestrial sediment supply
From the above, it is clear that a major source of the sediment found in estuaries and along adjacent
shorelines is the terrestrial hinterland. Efforts to calculate annual mean global sediment yields date
back to Kuenen (1950), Gilluly (1955), and Fournier (1960) who respectively estimated that 32.5, 31.7
and 51.1  109 t a-1 of sediment have been eroded from the continents and transported to the coasts
predominantly by large rivers. These relatively high estimates contrast with the lower value of 8.3 
109 t a-1, estimated by Mackenzie and Garrels (1966) on the basis of chemical mass balance between
rivers and oceans. Strakhov (1967) published a first global map showing the areas of differing
sediment yields. Acknowledging the uncertainties inherent in such estimates, and basing their
estimates on medium-sized drainage basins, Walling and Webb (1983; cf. also Walling and Webb,
1996) suggested that the annual global sediment yield ranged between 15 and 20  109 t a-1. Using the
data of Walling and Webb (1983), Smithson et al. (2002) published an annual sediment yield map
from which it is evident that mountainous regions generally have higher sediment yields than
continental lowlands (see Fig. 4).

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Independently, Milliman and Meade (1983) came to a similar order of magnitude, their initial
estimate of 13.5  109 t a-1 being later upgraded to 20  109 t a-1 by Milliman and Syvitski (1992), in
recognition that the sediment supply by small mountain streams had been underestimated. A year
earlier, Oldeman et al. (1991) suggested a modern, human-induced soil loss of 50  109 t a-1, a value
almost identical to that of Fournier (1960). A few years later Pimentel et al. (1995) upgraded this value
to 75  109 t a-1.
Fig. 4. Map of the world indicating annual terrestrial sediment yields (modified after Smithson et al., 2002;
largely based on Walling and Webb, 1983).
The above summary of the most important sediment yield studies over the past 60 years, and the
widely fluctuating estimates of different investigators, demonstrates the inherent difficulty of
obtaining reliable data. Global sediment yield maps as shown in Fig. 4 can therefore only provide a
first-order picture of general trends. One of the main reasons for this is the general dearth of in situ
sediment discharge data for rivers in many parts of the world, coupled with the pitfalls of extrapolating
from one region to another, even within similar climate zones. Fig. 5 shows a selection of major rivers
for which reasonably reliable data are available (after Summerfield, 1991; based on Meybeck, 1976,
and Milliman and Meade, 1983). Comparing two rivers draining tropical drainage basins, the Orinoco
in South America (drainage area 0.945  106 km2) and the Zaire in Africa (drainage area 3.7  106
km2), one might have expected a similar sediment yield after correcting for the different drainage areas.
Yet, in spite of the much larger drainage area, the annual sediment yield of the Zaire (33.3  106 t a-1)
is 4.5 times lower than that of the Orinoco (150  106 t a-1) (data extracted from Allen, 1997), perhaps
reflecting the sediment contribution of the Andean source of the Orinoco and its tributaries. Sediment
yield estimates of less well documented rivers and regions are thus likely to change as more reliable
data become available. For example, in the Eurasian Arctic, Milliman and Meade (1983) estimated an
annual sediment yield of 84  106 t, whereas a more recent study suggested that 60  106 t would be
more appropriate (Gordeev et al., 1996) but this may be revised upwards again given the recent
climate-forced increase in Arctic river discharge (Peterson et al., 2002; Shiklomanov et al., 2006). Not
surprisingly, Syvitski (2003) correctly advocates that future research should focus on local rates of
change in sediment yield, rather than on total global yield.

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Fig. 5. Sediment and solute loads of selected large rivers (modified after Summerfield, 1991; based on data of
Maybeck, 1976; Milliman and Meade, 1983).
An important distinction can be made between natural denudation processes and anthropogenically
influenced sediment yields, the latter impacting progressively larger areas since the rise of ancient
civilizations, and which has increased to global proportions in the course of the modern period of
industrialization (e.g. Crossland et al., 2005; Walling, 2006). In many parts of the world, estuarine and
coastal sediment budgets are today dominated by anthropogenic overprints. In the case of land use, it
is important to also note that human actions can either increase or decrease sediment yield (Walling,
1999), depending on local agricultural practice, grazing control and general land use (e.g.
deforestation/reforestation).
Besides the effects of adverse land use, the construction of dams and other impoundments are of
particular importance (e.g., Davies and Day, 1998; Vörösmarty et al., 2003; Chu and Zhai, 2008;
Slagel and Griggs, 2008). It has been estimated that the 633 largest impoundments intercept 40% of
the global river discharge, 50% of the dams retaining up to 80% of the suspended sediment load
(Vörösmarty et al., 2003). A particularly well illustrated example of the adverse effects of sediment
interception by dams is the east coast of the USA between Cape Cod and Cape Canaveral (Fig. 6)
where, in some cases, the suspended sediment supply to the coast has dropped to virtually zero
(Nichols and Biggs, 1985; based on data from Dole and Stabler, 1909; Meade, 1969; Meade and
Trimble, 1974; Nichols, 1978; Gross, 1975; USCEQ, 1970). In general, river and coastal sediment
budgets are negatively impacted by such interruption in sediment supply, the upset dynamic
equilibrium often resulting in severe downstream and down-coast erosion (Fig. 7).
The lesson here is that the morphologies, dynamics, and sediment budgets of many modern
estuaries and coasts may be very recent features produced by human-induced impacts both within the
catchments (from watershed to coast) and subsequently along the coast. These impacts may now
completely mask the former natural situation. As a consequence, future forecasts, past hindcasts and
other extrapolations that are based on modern observations and measurements should be done with
caution and circumspection.

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Fig. 6. Suspended sediment supply before (1909) and after (1970) the construction of dams on the rivers between
Cape Canaveral and Cape Cod along the eastern seaboard of the USA (modified after Nichols and Biggs, 1985;
based on Dole and Stabler, 1909; Meade, 1969; USCEQ, 1970; Meade and Trimble, 1974; Gross, 1975; Nichols,
1978).
Fig. 7. Severe beach erosion on a barrier island of the Georgia Bight, east coast of the USA, triggered by the
interruption of sediment supply by construction of dams in the hinterland (photo by author).
3.02.2.4. Modern marine sediment supply
The second major sediment source feeding coasts and estuaries is from the nearshore zone and the
coast itself. Most obvious is sediment production (mud, sand and gravel) by wave-driven coastal
erosion, especially during severe storms (e.g., Williams, 1956; Mason and Hansom, 1988; Sunamura,
1992; Pielke and Pielke, 1997), mass wasting events promoted by groundwater seepage and heavy
rainfall (e.g., Barton and Coles, 1984; Clayton, 1989; Griggs and Trenhaile, 1994) or, along Arctic

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shores, due to thawing of coastal permafrost soils (thermokarst) (e.g., Are et al., 2005; Ostroumov et
al., 2005; Forbes, this volume). However, the rate of coastal retreat, and hence the supply of new
sediment to adjacent beaches, varies by several orders of magnitude depending on sediment or rock
type and its degree of consolidation. This is well illustrated in Fig. 8 (modified after Woodroffe, 2002)
where recent tuffaceous sands may erode at several tens of meters per year, whereas the retreat of a
basalt cliff (on average) proceeds at fractions of a millimeter per year (based on Emery and Kuhn,
1980, and Sunamura, 1992).
Fig. 8. Erosion rates of coastal cliffs along exposed shores as a function of rock type (modified after Woodroffe,
2002; based on data of Emery and Kuhn, 1980; Sunamura, 1992).
Generally underrated is the potential for sediment production by submarine abrasion (e.g., Bradley,
1958; Dietz, 1963; King, 1972). Although there is considerable debate about the manner of shore-
platform evolution involving a number of different situations (cf. Trenhaile, 1987; Sunamura, 1992;
Trenhaile, this volume), there can be little doubt that in places where submarine abrasion takes place,
the contribution to the coastal sediment budget can be substantial (Stephenson, 2000). Thus, even
though abrasion rates per square meter are generally small and decrease exponentially with increasing
water depth, the large relative areas that may be involved (up to many hundreds of square meters of
seafloor per meter of shore) can locally contribute as much as 50% to the total sediment production
(e.g., Horikawa and Sunamura, 1970; Healy and Wefer, 1980). Indeed, in the absence of substantial
rivers and where a wide nearshore shelf exists, such as occurs in the western and northern isles of
Great Britain, the proportion of biogenic beach sand derived from the adjacent shelf can reach 95%
(Hansom and Angus, 2001; May and Hansom, 2003). The same applies to shores fringed by coral
reefs where almost the entire beach material may be derived from onshore transport of coral debris
(e.g., Folk and Robles, 1964).
In spite of the considerable variability in the amount and type of sediment supplied to the coastal
zones of the world, there appears to be a distinct latitudinal trend in the overall composition of shelf
and nearshore sediments (Fig. 9) (Hayes, 1967; Emery,1968). It follows that at least part of this
sediment will also be found on adjacent beaches and in estuaries. While offshore mud belts are
characteristic features of most continental shelves, muds are not normally expected to occur in
nearshore areas or on beaches along open ocean coasts. Exceptions to this general rule are the

13
shorelines between the Amazon mouth and the Orinoco delta (e.g., Eisma et al., 1991), some locations
along the southwest coast of India (e.g., Mallik et al., 1988), parts of the shoreline of China (e.g.,
Wang and Aubrey, 1987), the entire west coast of Korea (e.g., Alexander et al., 1990), and some
mangrove-dominated shores of southeast Asia and Australia (e.g., Galloway, 1981; Woodroffe, 1988).
In these cases mud is delivered to the coast at a greater rate than can be removed by local waves, in
some regions the subsequent rapid spread of vegetation, particularly mangroves, being an additional
factor in trapping the mud. In contrast to open ocean coasts, mud is an important sedimentary
component of almost every estuary worldwide (cf. Flemming, 2002, for a comprehensive overview).
Furthermore, while coral sands are restricted to particular shores of the Tropics and Subtropics,
bioclastic material produced by intertidal and shallow subtidal shell-forming organisms, e.g. bivalves,
gastropods and barnacles, can be found in varying proportions on almost any beach from low to high
latitudes.
Fig. 9. Trends in latitudinal sediment composition of beaches and inner continental shelves (modified after
Hayes, 1967; Reineck and Singh, 1980; partly based on Emery, 1968).
3.02.3. Coasts
3.02.3.1. Coastal classification
A conceptual approach to coastal classification based on major processes such as emergence,
submergence, progradation and retrogradation relative to coastal advance or retreat was proposed by
Valentin (1952). However, the plate tectonics paradigm provided coastal classification with a global
tectonic frame within which leading-edge coasts (or collision coasts) are distinguished from trailing-
edge and marginal sea coasts, the former two being further subdivided into continental and island arc
collision coasts, and neo-trailing-, afro-trailing-, and amero-trailing-edge coasts, respectively (Inman
and Nordstrom, 1971). Such classifications successfully delineate major coastal settings in a global
tectonic context, large scale coastal landforms that are related to such settings being shown in Fig. 10
(based on Inman and Nordstrom, 1971). Here, headland-bay coasts are distinguished from coastal
plain coasts, deltaic coasts, permafrost coastal plains, rocky coasts, fjord coasts, and fringing coral reef
coasts. In the case of the global distribution of barrier-islands, for example, 49% are located along
trailing-edge coasts, 24% along collision coasts, and 27% along marginal sea coasts (Glaeser, 1978).
Furthermore, of those located along trailing-edge coasts, 75% occur along amero-trailing-edge, 19%
along afro-trailing-edge, and only 6% along neo-trailing-edge coasts.

14
Fig. 10. Strongly simplified global distribution map of major coastal types (modified after Inman and Nordstrom,
1971).
Such broad geotectonic categories, however, are less suitable for the classification of coasts in a
geographically more restricted sense as would, for example, be required for the purposes of coastal
development and management (Bishop and Cowell, 1997; French, 1997). In this context, the
availability of high-resolution satellite imagery has greatly improved quantitative regional coastal
classification. This is illustrated in the satellite image of Fig. 11, which shows the coastal region
around San Francisco, USA, where headland-bay beaches, straight beaches and rocky shores can
easily be identified and delineated. The demands of coastal management have seen the recent
emergence of ever more detailed classification schemes (e.g., Fairbridge, 2004; Finkl, 2004).
Fig. 11. Annotated satellite picture of the coast near San Francisco Bay, California, showing some typical coastal
types such as rock coasts, headland-bay beaches and extended sandy beaches fronting the open Pacific (satellite
image by courtesy of NASA).

15
Good general overviews of coastal systems and processes can be found in Carter (1988), Hansom
(1988), Carter and Woodroffe (1994), Komar (1998), Haslett (2000), Woodroffe (2002), Masselink
and Hughes (2003), Davis and FitzGerald (2004), Bird (2008), Dillenberg and Hesp (2009), and
Davidson-Arnott (this volume). Muddy shores, as an especially vulnerable coastal type, are dealt with
in Healy et al. (2002), while a systematic encyclopedic presentation of the world’s coasts is presented
in Bird and Schwartz (1985) and Bird (2010).
3.02.3.2. Relationships between beach morphodynamics, wave climate and grain size
Most of those who live on open ocean coasts have probably observed that, from time to time, local
beaches change their appearance. Thus, in fair weather or summer, a beach may be wide with a
relatively steep intertidal slope, whereas in stormy weather or winter it may be narrower with a much
flatter slope. As illustrated in Fig. 12, the nature of the waves impinging on a beach appears to be
closely related to the slope of the nearshore seabed (based on Street and Camfield, 1966, Galvin, 1968,
and Carter, 1988). However, in its commonly presented form, this illustration ignores the fact that the
seabed slope is also very much constrained by grain size. As shown further down, for any particular
wave condition, coarser sediment will generally produce a steeper slope than finer sediment and this,
in turn, may control whether waves will be surging, collapsing, plunging, or spilling. In Fig. 12, the
effect of grain size is intimated by the size of the dots marking the seabed.
Fig. 12. Relationships between beach slope, the ratio between wave height and water depth, and breaker type
(modified after Smithson et al., 2002; in parts based on Street and Camfield, 1966; Galvin, 1968; Carter, 1988).
From the above it is evident that beach morphodynamics is essentially controlled by the interaction
between waves and beach sediment. During stormy weather when waves are high and energetic, as is
often the case in the winter season, the beach erodes, the sediment moving into one or more offshore
bars over which the waves eventually begin to break because of the shoaling water depth. Erosion of
the beach stops when the energy distribution within the broken waves is such that the offshore directed
sediment transport vector is compensated by the onshore directed vector. Following Guza and Inman
(1975), the high-energy beach state is termed ‘dissipative’ and is characterized by relatively flat beach
slopes. The process reverses during calmer weather when waves are lower and less energetic, as is
commonly the case in summer. The onshore transport vector is now larger than the offshore one, as a
consequence of which accretion occurs as the nearshore bars migrate shoreward to amalgamate with
the beach. This low-energy beach state, which is characterized by relatively steep slopes, is termed
‘reflective’. When a beach morphodynamically adjusts to either more dissipative or more reflective
states, it passes through a variety of intermediate states. In a nutshell, this simplified outline represents

16
the well-known conceptual model of beach morphodynamics developed by Guza and Inman (1975),
Short (1979), and Wright et al. (1979, 1985).
In more quantitative terms, the morphodynamic state toward which a beach will adjust under given
wave conditions can be determined from the dimensionless surf scaling parameter (ε) as defined by
Guza and Inman (1975):
ε = Hbσ2/gtan2ß (1)
where Hb is the breaker height (m), σ = 2π/T, T is the wave period (s), g is the acceleration due to
gravity (m s-2), ß is the beach slope in degrees. It should be noted that the beach slope here can be
viewed as a proxy for grain size. In this approach, the reflective beach state is reached when ε ≤ 3,
whereas the dissipative state is attained when ε ≥ 33. Values between 3 and 33 indicate intermediate
beach states.
Alternatively, the beach state can also be determined from the dimensionless so-called ‘Dean
parameter’ (Ω, here replaced by Bs), a ratio originally proposed by Gourlay (1968) and subsequently
used by Dean (1973):
Bs = Hb/(wsT) (2)
where Hb is the breaker height (m), ws is the settling velocity of the beach sand (m s-1), T is the wave
period (s). In this approach, the reflective beach state is reached when Bs ≤ 1, whereas the dissipative
state is attained when Bs ≥ 6. Values between 1 and 6 indicate intermediate beach states. Short (1979)
and Wright et al. (1979) subsequently linked particular morphodynamic beach stages with specific
beach states as defined by these parameters so that the transition from reflective (low-energy) to
dissipative (high-energy) conditions progresses through a sequence from Bs ≤ 1: no nearshore bar(s),
Bs = 2: welded bar with weak rip current action, Bs = 3: fully developed rip currents, Bs = 4: crescentic
bar, Bs = 5: sinuous bar, to Bs ≥ 6: parallel bar. The sequence reverses as wave energy decreases. Both
parameters thus predict the morphodynamic beach state on the basis of wave parameters and grain size,
the latter being represented either by its settling velocity or by the beach slope (Wright et al., 1985). A
good summary of beach and nearshore morphodynamics can be found in Short (1999) and Davidson-
Arnott (this volume).
That beach slope is a direct function of grain size and the degree of wave exposure can be
demonstrated graphically (Fig. 13, modified after Flemming and Fricke, 1983; based on data of
Bascom, 1951, and Wiegel, 1964). Figure 13 illustrates that this empirical relationship is narrowly
constrained, both for dissipative (exposed) and reflective (sheltered) conditions. Thus, for the
dissipative beach state of Bs = 6, the mean grain size for a given beach slope (at mid-tide level) can be
mathematically determined from the empirically derived equation:
D = -49.41 + 51.45 S-0.01563 (3)
where D is the mean grain size in phi, S is the beach slope in degrees. For the reflective beach state of
Bs = 1, the mean grain size for a given slope is defined by the equation:
D = -41.68 + 44.71 S-0.01991 (4)
Conversely, for the dissipative beach state (Bs = 6), the slope of a beach (at mid-tide level) for a given
mean grain size is defined by the expression:
S = 13.39 e(-D/0.7954) (5)

17
For the reflective beach state (Bs = 1), in turn, the beach slope for a given mean grain size is defined
by the equation:
S = 0.057 + 33.5152 e(-D/0.8517) (6)
Fig. 13. Relationships between grain size and beach slope of sandy beaches as a function of wave exposure
(modified and corrected after Flemming and Fricke, 1983).
For intermediate beach states, the points defining the relationship between beach slope and mean
grain size (and vice versa) occupy positions between the reflective and dissipative domains on Fig. 13.
However, not every beach will adjust over the complete range of morphodynamic states in the course
of its annual cycle since this depends entirely on the nature of the local wave climate. Thus, along
exposed stormy shores, a beach may oscillate morphodynamically between some intermediate stage
and the fully dissipative stage (e.g., Bs = 3 to >6), whereas under sheltered or swell conditions, a beach
may adjust between a fully reflective and intermediate stages (e.g., Bs = <1 to 3) (Short, 1979).
Sediment grain size and tides introduce complications to the above model and fine sandy beaches
often have reduced slopes and dissipative conditions, especially at low tide. Coarser sediment beaches
(especially gravel, cobble and boulder beaches) with steep slopes often remain in reflective mode, as
they require inherently higher wave energies to achieve dissipative states. Gravel beaches also show
remarkable shore-normal shape sorting as well as down-drift size sorting (e.g., Bluck, 1967; Carr,
1971; Orford, 1975; Waag and Ogren, 1984; Williams and Caldwell, 1988; Bartholomä et al., 1998;
Jennings and Shulmeister, 2002). Thus, in his detailed study of particle shape sorting on the gravel
beaches of South Wales, UK, Bluck (1967) identified four characteristic zones arranged perpendicular
to the shore. On the upper beach, a wide zone mainly comprising cobble-sized discs was followed
seaward by a narrower zone consisting of disc-shaped gravel showing pronounced landward, i.e.
swash-dominated, imbrication. Seaward again, these graded into an infill zone commencing with
sands containing an increasingly greater number of spherical and rod-shaped gravels downshore. The
seaward margin, or outer frame zone, comprised spherical cobbles with an infill of spherical and rod-
shaped gravels. This remarkable shape sorting of beach gravels reveals the sensitive hydraulic
response of particular particle shapes to swash and backwash mechanisms. A comprehensive overview
of the size and shape evolution of gravels from terrestrial sources to marine sinks can be found in the
case study of Ibbeken and Schleyer (1991).

18
More complex is the morphodynamic behavior of mixed sand and gravel beaches (e.g., Pontee et
al., 2004; Horn and Walton, 2007). The sand and gravel fractions are commonly segregated, the
former dominating the lower beach with a flatter slope, the latter occupying the upper beach above the
high-water line with a steeper slope, besides often also lining the base of the beach below the sand.
However, in particularly high-energy situations such as the glaci-fluvial mixed sand and gravel
beaches of South Island, New Zealand, densely-packed mixtures of sand and gravels occupy the same
facies, reducing percolation and resulting in lower beach slopes than would otherwise be expected
(McLean and Kirk, 1969).
A conspicuous coastal type that has attracted repeated attention over past decades are headland-bay
beach systems (also known as crenulated beaches or log-spiral beaches), e.g. Halfmoon Bay, Bolinas
Bay and Drakes Bay in Fig. 11. Krumbein (1947) was the first to recognize that the shapes of such
beaches appeared to approximate logarithmic spiral curves. Halfmoon Bay, located on the Pacific
coast of California south of San Francisco, is a good example that has been investigated both with
respect to its plan shape and the relationship between grain size and beach slope (Bascom, 1951;
Yasso, 1965). Logarithmic spirals have been successfully fitted to numerous headland-bay beaches
worldwide (e.g., Silvester, 1960; Bremner, 1991). Besides using the logarithmic spiral equation to
describe the plan shapes of beaches, there have also been attempts to use the parabolic and hyperbolic-
tangent equations (Hsu and Evans, 1989; Moreno and Kraus, 1999; cf. also Hsu, 2005). Irrespective of
the equation used, the strict mathematically defined geometric alignments may not be coincidental.
Refraction and diffraction around headlands evidently distributes wave energy in such a way that the
associated shoreline takes on a spiral-related shape once a dynamic equilibrium has been achieved. In
view of the practical implications for coastal engineering applications, equilibrium plan shapes of
headland-bay beaches have been determined in wave-tank experiments for different angles of wave
approach (Silvester, 1960).
That energy distribution along a log-spiral beach is indeed progressive and systematic is
demonstrated when plotting the grain-size data of Halfmoon Bay beach against the corresponding
beach-slope data collected by Bascom (1951; cf. also Bascom, 1964). On the log/log plot of Fig. 14,
the log-spiral curve describing the beach (cf. inset) corresponds to a quasi straight-line relationship
between sample 1 (fine sand, sheltered or reflective part of the beach) to sample 4 (coarse sand,
exposed or dissipative part of the beach). This demonstrates that, at the time of observation, the
shoreline of Halfmoon Bay evidently was in perfect hydraulic equilibrium between wave energy
dispersion, grain size and morphodynamic beach state, as reflected in the slope of the beach at various
positions along the shore. In cases where the grain size remains constant, the progression from
reflective beach states to dissipative beach states along the shore or at a particular point of the beach
would, in Fig. 14, be represented by a horizontal line (e.g., Flemming and Davis, 1994).
3.01.3.3. Beach placer deposits
Besides being the primary source of sand for coastal dunes, beach and nearshore sediments may be
enriched in heavy minerals to form placer deposits of economic significance. Among the most
important economic minerals and metals are gold, copper, chromium, iron (in the form of magnetite or
ilmenite), tin, titanium, monazite, zirconium, and diamonds. The occurrence of heavy mineral
concentrations along the coast depends on the geology of the adjacent hinterland, where they occur in
the detrital products of weathered rocks rich in such minerals, and from where they are selectively
transported to and along the coast. Because particular rock types or secondary deposits typically
contain a variety of characteristic heavy minerals, coastal placer deposits often consist of heavy
mineral suites rather than single minerals (e.g., Dill, 1998; Paine et al., 2005), a feature also reflected
in the global distribution of such deposits (Fig 15, based on Pernetta, 1994). It should be mentioned
here that beach and nearshore mining activities are commonly associated with severe environmental
degradation (e.g., Vongvisessomaij, 1995).

19
Fig. 14. Relationship between beach slope and grain size along the log-spiral shoreline of Halfmoon Bay,
California, plotted into the diagram of Fig. 13 (data from Bascom, 1951). Note the progression from a lower
slope in fine sand (reflective beach stage) in the shelter of the headland (position 1 in inset) to a steeper slope in
coarse sand (dissipative beach stage) in the most exposed part of the beach (position 4 in inset).
Fig. 15. Global occurrence of economically viable heavy mineral placer deposits along the shores of the world
(compiled after Pernetta, 1994).
Due to the higher specific gravity of heavy minerals and native metals (δ = 2.9–19.2) relative to
common quartz (δ = 2.65), heavy minerals and metallogenic particles are hydraulically not equivalent
to the bulk material of normal beach sand. They are hence rapidly segregated from the lighter minerals
by the very effective sorting mechanism of ocean waves, to be concentrated in so-called placer
deposits along the shore (e.g., Swift et al., 1971; Komar and Wang, 1984; Petersen et al., 1986;
Slingerland and Smith, 1986; Shankar et al., 1996; Hughes et al., 2000). Where heavy minerals are

20
rare, they do not get enriched in large placer deposits but are instead distributed around such secondary
point sources with distinct size gradations in the direction of littoral drift (e.g., Anfuso et al., 1999;
Dinis and Soares, 2007). A particularly exotic example is provided by the alluvial diamonds found
along the west coast of South Africa, which continue to be mined on a grand scale because of their
gem-stone quality. Here, major secondary point sources of diamonds along the coast are local river
mouths, especially the Orange River. The alluvial diamonds are found incorporated in certain types of
gravels or are caught in hydrodynamic traps such as potholes and gullies eroded into the bedrock by
surf action (e.g., Murray et al., 1970). As illustrated in Fig. 16, and in agreement with the trend
observed in the river-derived beach gravels along the coast (Bluck et al., 2001, 2007), the size of
diamonds (expressed in carats per stone) rapidly decreases with distance from the Orange mouth with
the largest stones being found near the river mouth and progressively smaller stones up to several
hundred kilometers to the north along the coast of Namibia (Sutherland, 1982; Gurney et al., 1992).
The original source of these diamonds are kimberlite pipes located far inland, from where they have
been eroded and carried down to the coast in the course of the past 80 Ma or so. Having been
reworked within the fluvial bed load and thereafter in the coastal surf, the perfect octahedral shape of
the 2.6 carat diamond recovered near Oranjemund (Orange River mouth) shown in the inset of Fig. 16,
bears witness to the extreme hardness and resistance to abrasion of these stones.
Fig. 16. Size segregation of alluvial diamonds northward of the Orange River mouth, South Africa (modified
after Gurney et al., 1992; partly based on Sutherland, 1982). Note the exponential decrease in carats/diamond
with distance from the river mouth and the almost perfect octahedral shape of the diamond (inset) in spite of the
long transport path from an inland source and extended periods of river transport and exposure to high-energy
wave action along the coast.
3.02.4. Estuaries
3.02.4.1. Definition of an estuary
The definition of what kind of environment the descriptive term ‘estuary’ is supposed to represent
has a long history and an end does not seem in sight (e.g., Lyell, 1834; Pritchard, 1967; Day, 1980;
Fairbridge, 1980; Perillo, 1995a). A comprehensive overview can be found in Perillo (1995b). More
recently, Elliott and McLusky (2002) have re-emphasized the need of clear definitions in estuarine
research in view of the different requirements expressed by various disciplines, including conservation
and management.

21
The term ‘estuary’ is derived from the Latin word ‘aestuarium’, which was used by the Romans to
designate the tide-influenced part of a river. In accordance, the modern definition of the term ‘estuary’
is most commonly restricted to the lower course of a river where fluvial and marine processes interact.
However, while some authors restrict the estuarine part of a river to the limit of saltwater intrusion, i.e.
up to the point where the river water is measurably diluted by seawater (e.g., Pritchard, 1967; Day,
1980), others take the upper limit of tidal penetration as the main criterion, the tidal wave mostly
propagating farther up the river than does the intrusion of seawater (e.g., Lyell, 1834; Dionne, 1963;
Fairbridge, 1980; Perillo, 1995a). If the upstream limit of marine influence (i.e. both saltwater
intrusion and tidal penetration) is the basic criterion, then the latter definition is clearly the more
comprehensive. Even then, neither the limit of tidal penetration nor that of saltwater intrusion is a
stationary boundary, both oscillating up and down the lower river, periodically over spring and neap
tidal cycles in the former, and aperiodically with increasing or decreasing river discharge in the latter
case. The two processes are partly decoupled because the penetration of the tidal wave into a river is
essentially controlled by frictional energy loss (cf. Friedrichs, this volume), whereas the limit of
saltwater intrusion is primarily controlled by the flushing efficiency of the river (Gibbs, 1977). Thus,
seasonal estuaries, i.e. estuaries where the freshwater/saltwater transition is, on average, located at the
river mouth (for example, the Mississippi River), are distinguished from inverse estuaries where the
freshwater/saltwater transition is permanently located out at sea (for example, the Amazon River), and
from what one could call ‘normal’ estuaries where this transition is located some distance upstream in
the river. However, as pointed out above, salinity is not the only criterion and the ultimate upstream
limit of an estuary is, in addition, determined by the penetration of the tidal wave. Furthermore, wave
action in the lower part of an estuary (especially in macrotidal settings) may contribute substantially to
the total energy flux. As will be seen later, the interactions between these processes largely control the
sedimentological structure of estuaries.
More recently, biotic criteria have been included in the definition, e.g. Perillo (1995a) who has
extended the definition by adding “and can sustain euryhaline biological species from either part or
the whole of their life cycle”. Such extensions of the basic definition by secondary factors are not
really helpful because they diffuse the otherwise clearly defined boundaries, besides obscuring the
distinction between definition and classification. Thus, while such secondary factors may serve
parameter-specific classifications (cf. Elliott and McLusky, 2002), they should not form part of the
basic definition (which, incidentally, would also hold for a lifeless, but otherwise earth-like, planet).
3.02.4.2. Classification of estuaries
Whereas definitions demand universal applicability, classifications do not. They are conventions
that can be developed for, or adapted to, regional or local situations, even though universal
applicability may in some cases be desirable for practical reasons (e.g. grain-size classification). In this
context, the classification of estuaries is a case in point. Their morphology and biology are
geographically so variable (Jennings and Bird, 1967; Galloway, 1981; Dyer, 1990; Eisma, 1997;
Allanson and Baird, 1999; Perillo et al., 1999) that classifications should restrict themselves to the
identification of a limited number of basic types that can easily be identified on the basis of a few
characteristic parameters (accepting that, in reality, there will be numerous transitions between, and
subdivisions within, any basic classification). In principle, the condition holds that the larger the
number of basic types, the more confusing the picture. In a geotectonic-morphological context, one of
the most widely used classifications that fulfills the criterion of simplicity, is the one proposed by
Fairbridge (1980; cf. Fig. 17). Perillo (1995a) proposed a modified version of this by distinguishing
between so-called ‘primary estuaries’ and ‘secondary estuaries’. Being mere conventions, there is
nothing basically wrong with introducing a new (or modified) classification, and several
classifications may well exist side by side, each reflecting the peculiarities of a particular region or set

22
of parameters (e.g., Swaney et al., 2008; Taljaard et al., 2009). However, in the case of ‘blind’
estuaries, i.e. estuaries that have a free connection to the sea for only part of the year, being blocked by
a wave-constructed sand bar during the dry season when river discharge is very low or absent, it is
rather doubtful whether general agreement would be reached that, during the blocked period, these
systems should not be regarded as estuaries, as suggested by Perillo (1995a). Many researchers (e.g.,
Day, 1981; Potter et al., 1993; Roy et al., 2001; Rustomji, 2007; Taljaard et al., 2009; Chuwen et al.,
2009) would object to such a proposition. Seasonally closed estuaries commonly occur along coasts
exposed to high wave energy. In such situations, wave-overtopping frequently feeds seawater to the
otherwise stagnant river water, thereby maintaining basic estuarine conditions via measurable dilution
of fresh water. Since wave-overtopping (often assisted by the tides) is a marine influence, one can
justifiably claim that, in agreement with the basic definition, such temporarily (and even permanently)
blocked riverine water bodies are a particular type of estuary.
Fig. 17. Major morphological estuary types (modified after Fairbridge, 1980).
A similar objection can be raised to the undifferentiated inclusion of coastal lagoons as so-called
‘secondary estuaries’ (Perillo, 1995a). While some lagoons qualify as particular types of estuaries,
others do not. Irrespective of whether a lagoon is choked, restricted or leaky (Kjerfve and Magill,
1989), it must comply with the basic definition of an estuary in order to qualify as an estuarine water
body, i.e. the lagoon must in some form communicate with a river or river system and, together, with
the sea. Lagoonal water bodies of this type, for example, are the Dos Patos Lagoon in Brazil (Toldo,
1991), Mar Chiquita in Argentina (Isla, 1995), Pamlico Sound in the USA (Fletcher et al., 1990),
Terminos Lagoon in Mexico (Yáñez-Arancibia and Day, 1982), or Knysan Lagoon in South Africa
(Day, 1967). Other lagoons do not meet this basic criterion, for example Langebaan Lagoon along the
west coast of South Africa (Flemming, 1977), Sandwich Harbour and Walvis Bay lagoons along the
coast of Namibia (Bremner, 1985), Baia dos Tigres in southern Angola (Guilcher et al., 1974), or the

23
Banc d’Arguin tidal flat and lagoonal system off Mauritania (Vermeer, 1985; Wolff and Smit, 1990).
Although these lagoons may exhibit certain features also found in many estuaries (e.g. the occurrence
of fringing salt marshes or mangroves), these (and many other) lagoons exist independently of modern
rivers, having instead formed in the rear of ‘flying’ sand spits or by marine flooding of coastal
depressions. As such, they differ from estuaries in many fundamental aspects. For example, they not
only lack the typical saltwater-freshwater regimes structuring estuaries into salt-wedge, partially
mixed or fully mixed systems, but also have a different biology (e.g., absence of euryhaline species)
and sedimentology (e.g., absence of turbidity maxima and associated mud reaches).
From a hydrological point of view, estuaries have been classified according to particular circulation
patterns produced by the interaction between the tide-driven seawater and the discharge-driven
freshwater (Pritchard, 1955; Pritchard and Carter, 1971). Following the principle of mass conservation,
the rate of change in salinity (and hence also suspended sediment concentration) relative to a fixed
reference point in an estuary is controlled by diffusion (turbulent mixing) and advection (circulation).
On this basis, three basic types of estuaries have been distinguished, namely ‘well-stratified’ (or ‘salt-
wedge’), ‘partially stratified’, and ‘well-mixed’ estuaries. The mixing condition characterizing each
type can be identified by the ratio between the tidal and the fluvial discharge (both expressed in m3 s-1).
Thus, a ratio of <20 is typical for well-stratified or salt-wedge estuaries, from 20–200 for partially
stratified estuaries, and >200 for well mixed estuaries (e.g., Borrego et al., 1995). Since the tidal prism
of microtidal estuaries is relatively small, these tend to be well stratified. Conversely, macrotidal
estuaries tend to be well mixed, while mesotidal ones tend to be partially mixed. However, because
there is a continuum between the three types, some estuaries may change from one basic type to
another in response to seasonal changes in fluvial discharge (cf. Eisma, 1993), or even when tidal
discharge increases and decreases in the course of a neap-spring tidal cycle (cf. Borrego et al., 1995).
Pritchard and Carter (1971) have actually distinguished a fourth type in which there is both lateral and
vertical homogeneity in salinity. This condition, however, is restricted to the outer regions of partially
and especially well-mixed estuaries where it reflects the transition to the open shelf.
Besides being involved in estuarine mixing, the tidal wave entering estuaries is also modulated by
changes in estuarine morphology. Thus, convergence of opposite shores causes the tidal wave to
increase in height, thereby increasing tidal energy per unit width, whereas friction along the bed slows
the tidal wave down, thereby shortening its wavelength and reducing its height due to progressive
energy loss. Three situations are distinguished in this interplay between the effects of convergence and
friction. Where convergence dominates over friction, the tidal wave progressively increases in height,
a condition termed ‘hypso- or hypersynchronic’; where the two are balanced, the tidal wave maintains
a constant height in what is termed a ‘synchronic’ mode; finally, where friction dominates over
convergence, the tidal wave progressively decreases in height, the mode being termed
‘hyposynchronic’ (e.g., Allen et al., 1980; Nichols and Biggs, 1985; Dyer, 1995). In undisturbed
estuaries the synchronicity commonly evolves up-estuary towards a hyposynchronic mode.
The degree of energy dissipation at any particular point in an estuary is thus the result of complex
interactions between fluvial discharge, tidal prism and morphology, wind stress and wave action being
additional aperiodic factors, especially in macrotidal estuaries. In conjunction with the effects of
mixing, these factors control the sedimentary response of an estuarine system. A comprehensive
modern text on estuarine processes has recently been compiled by Prandle (2009).
3.02.4.3. Estuarine sedimentology
Being transitional systems between land and sea, estuaries act as temporary or permanent storage
systems for land- and/or sea-derived sediments (Postma, 1967; Dyer 1973; Dalrymple et al., 1994;
Eisma, 1997). On shorter time scales, sediment may either choke an estuary because of high supply
from adjacent drainage basins or be episodically flushed during periods of high river discharge. In

24
either case, the cause can be natural (climate controlled) and/or human-induced (adverse land use,
river channeling). On longer time scales, two situations can be distinguished. During falling sea-levels,
estuaries are more likely to be temporary storage systems as river valleys are excavated in the course
of incision due to a lowered base level. During rising sea levels, estuarine valley fills are more likely
to evolve into permanent storage systems, the sedimentary fill being conserved below transgressive
shoreface and shelf deposits (Dalrymple et al., 1994).
An intriguing feature of basic estuarine sedimentation patterns is an apparent independence of tidal
range. Dionne (1963) distinguished three zones on the basis of locally dominating processes, i.e. a
lower estuary where marine processes dominate, a middle estuary dominated by intense
saltwater/freshwater mixing, and an upper or fluvial estuary affected by daily tidal action. This basic
pattern was later confirmed in numerous detailed studies (e.g., Nichols, 1972; Clifton, 1982; Nichols
et al., 1991; Dalrymple et al., 1992). As a consequence of the dominating processes, the beds of lower
estuaries are commonly composed of relatively coarse sediments (i.e. sands, shelly sands and, more
rarely, terrigenous gravels) that are carried into river mouths by wave and tidal current action. The
sediments forming the beds of the middle (or central) sections of estuaries, by contrast, are dominated
by muddy sediments, i.e. mixtures of sand and mud, rapidly progressing from muddy sands near the
transitions to both lower and upper estuaries, to sandy muds and pure muds in more central locations.
The preferential deposition of mud in the middle sections of estuaries is the result of enhanced
flocculation, coagulation and aggregation of suspended matter due to the mixing of salt water and
fresh water, the process being promoted by high organic matter contents and microbial activity (e.g.,
Syvitzki, 1991). The larger settling velocities of flocs and aggregates (in comparison to that of their
constituent particles) promote deposition during slack tides (low-energy phases), thereby forming the
prominent mud reaches of the middle (or central) sections of estuaries. The upstream limit of mud
deposition is the point up to which the turbidity maximum migrates during the flood phase of the tide
and generally coincides with the maximum limit of salt intrusion. Conversely, the downstream limit is
determined by the point reached by the turbidity maximum in the course of the ebb tide, and is
commonly located some distance from the actual river mouth. In contrast to this, the bed sediments of
upper estuaries are dominated by sands and gravels of fluvial (terrigenous) origin. Due to the absence
of mixing and associated aggregate formation processes in upper estuaries, the river-borne suspended
sediment is usually dispersed and therefore easily resuspended after short periods of intermittent
deposition (e.g., Dyer, 1973; Eisma, 1993).
A synthetic example representing the classical case of a partly barred (partially mixed) estuary as
commonly found along open-ocean and other wave-dominated coasts is illustrated in Fig. 18 (inspired
by Allen, 1991, and Dalrymple et al., 1992). The sedimentary structures displayed in the synthetic core
sections below the various estuary zones in Fig. 18 are schematic and indicate anticipated facies
changes, including specific details such as the predominant nature of cross-bedding (ripple cross-
bedding, planar cross-bedding, trough cross-bedding), the presence or absence of shell or terrigenous
gravel, or the occurrence of spring-neap cycles. Depending on climatic conditions and bedrock
morphology, estuaries may either be laterally confined by the steep slopes of bedrock-incised valleys,
or they may be laterally unconfined when crossing low-lying coastal plains. In the former case,
fringing intertidal mud flats and salt marshes (in temperate climates) or mangrove forests (in sub-
tropical to tropical climates) are either completely lacking or are restricted to small, localized pockets,
whereas in the latter case such environments may occupy large areas. In response, individual estuary
zones may expand or shrink in extent at the expense of the others (e.g. Cooper et al., 1999). For
example, in the case of estuaries entering the sheltered part of a microtidal embayment, the lower
(sand-dominated) section of the estuary may be confined to the river mouth itself (e.g. Schettini et al.,
2010).

25
Fig. 18. Sedimentary facies zonation of estuaries (modified after Allen, 1991, and Dalrymple et al., 1992). Note
that the tripartite subdivision (lower marine sand reach, central mud reach, and upper fluvial sand reach) applies
to most estuaries and appears to be independent of tidal range.
Similar variations can be identified in relation to tidal range. As tidal range (and hence the tidal
prism) increases, the most notable change takes place in the lower estuary. Thus, the typical barrier
spits and ebb- and flood-delta sand bodies that characterize many micro- and mesotidal estuaries (Fig.
18) are reorganized into elongated mid-channel sand bars in funnel-shaped macrotidal estuaries, the
converging shores often being lined by landward-fining intertidal flats fringed by salt marshes or
mangrove forests (e.g. Dalrymple et al., 1992; Perillo, 1995b; Wells, 1995). In summary, while
changes in river discharge, tidal range and morphology modulate the sedimentary system, they do not
fundamentally change the characteristic tripartite sedimentary subdivision developed along the main
axis of an estuary, the main effect being a spatial reorganization such as the expansion (or contraction)
of one sedimentary facies relative to the others. As pointed out by McManus (1998), however, spatial
and temporal variations in erosion and deposition can also be controlled by longer-term cycles not
directly related to the factors outlined above.
While the mechanisms explaining the formation of the sand/gravel facies in the lower and upper
estuaries are quite straightforward, the processes leading to mud deposition in central estuaries are
much more complex (cf. Dyer, 1986; Whitehouse et al., 2000, and Winterwerp and van Kesteren,
2004, for recent summaries). In addition, recent investigations have shown that so-called ‘sortable
silts’ (sensu McCave et al., 1995) must be distinguished from ‘aggregated muds’ (Bartholdy, 1985;
Chang et al., 2007; Molarinoli et al., 2009). Sortable silt consist of mineral particles that, like sand
grains, are predominantly transported as single grains, i.e. they are rarely incorporated into flocs and
aggregates, probably because their relatively large, inert surfaces inhibit bonding between particles.
Sortable silts thus form the non-cohesive part of the fine fraction commonly known as mud (size range
<63 µm). Where available in abundance and finer-grained material (clay and fine silt) is short in
supply (<~10%), sortable silts may even form extensive tidal flats composed of firm, non-cohesive
sediment (Flemming, 2000). The lower size limit of this grain population was found to be ~8 μm
(Chang et al., 2007), although there appears to be some evidence that this limit can increase up to 20
μm under conditions that are currently not well understood (Molarinoli et al., 2009). This means that
flocs and aggregates are predominantly composed of particles smaller than about 8 μm (or <20 μm)
and that the small particles would, on their own, be rapidly eliminated from shallow-water
environments because of their very low settling velocities.

26
Accumulation of mud in estuaries, on tidal flats and in shallow-marine mud belts is thus a function
of the relatively high settling velocities of the larger composite particles in relation to the degree of
local turbulence and residual current shear at slack tide. The available data suggest that the critical
lower limit for a particle to just overcome the residual current shear is a settling velocity of 0.01 cm s-1
(at 18°C), which corresponds to a particle size of 8 μm. This is graphically illustrated in Fig. 19, which
shows that fecal pellets and composite particles (flocs and aggregates) formed in turbulent water
generally exceed the critical size, the bulk of fecal pellets and some of the aggregated material even
corresponding to equivalent spherical quartz grain sizes of fine and very fine sand (modified after
Nichols and Biggs, 1985; based on data from Migniot, 1968, Haven and Morales-Alamo, 1968, Owen,
1971, and Krone, 1972). Contrary to common perception, mixed sand-mud sediments therefore are,
from a hydraulic point of view, actually very well sorted due to the flocculation and aggregation of
finer-grained muds (Flemming, 2003), the apparent poor sorting generally being an artifact resulting
from the mechanical break-down of the former aggregates into their constituent particles before size
analysis in the laboratory (Chang et al., 2007).
Fig. 19. Settling velocities of dispersed clay particles, flocs and aggregates in quiet and turbulent water, and fecal
pellets (modified after Nichols and Biggs, 1985; partly based on data of Haven and Morales-Alamo, 1968;
Migniot, 1968; Owen, 1971; Krone, 1972). Note that the equivalent quartz-sphere diameters and the
corresponding grain size classification are valid for settling velocities at 18°C.
A phenomenon of particular interest in estuarine sedimentology is the occurrence of so-called
‘fluid mud’ that results from the fall-out of highly concentrated suspended matter at slack tide to form
a thixotropic, high-viscosity mud layer (density 0.2–0.5 g cm-3) immediately above the consolidated
bed in the turbidity maximum zone of estuaries (Ross and Mehta, 1989, cf. also Winterwerp and van
Kesteren, 2004). Depending on the sediment budget of an estuary, such beds can vary in thickness
from a few decimeters to a few meters and may be highly mobile in response to tidal currents. Because
of the inherent difficulty of detecting fluid mud by the conventional echo-sounders fitted to most cargo
vessels, they may form a serious navigation hazard in some estuarine shipping lanes. For this reason,
great efforts are currently being expended to improve continuous acoustic detection of fluid mud in
order to track its spatial and temporal dynamics (e.g., Schrottke et al., 2006).

27
3.02.5. Sediment classification
3.02.5.1. Grain-size classification
The internationally most commonly used grain-size classification scheme is a modified version of
the one originally proposed by Wentworth (1922). It is based on a negative log2 transform of the
millimeter size of the sediment, the transformed log-values being symbolized by the Greek letter ‘phi’
(φ). Mathematically, the conversion from mm to phi is achieved by the equation:
phi = -log2 Dmm (7)
which can be simplified to:
phi = -3.3219log10Dmm (8)
Conversely, phi-values can be converted back to mm-values by the equation:
Dmm = 2-phi (9)
with Dmm in all cases as the grain size in mm (Krumbein, 1934a).
The phi-scale is easy to memorize as every full step corresponds to either double or half the
previous mm-value, the origin being 1 mm; thus, 0 phi = 1 mm, -1 phi = 2 mm, -2 phi = 4 mm, etc., or
1 phi = 0.5 mm, 2 phi = 0.25 mm, etc. Besides ease of recognition, the choice of log2 has a sound
scientific basis, namely in that the settling velocities of quartz grains are proportional to the square of
the grain size (ws  mm2) in the laminar fall regime (Stokes’ Law) and to the square root of the grain
size (ws  mm0.5) in the turbulent fall regime (Impact Law) (cf. Rubey, 1933). In accordance, log2
values of the mm-scale are proportional to the quadratic functions of the fall regime, a fact that
justifies the use of logarithmic transformations of grain-size distributions.
The phi-scale, together with the associated nomenclature of grain-size class and group names, is
tabulated in Fig. 20 and is a modified version of the Wentworth-scale based on the recommendations
of the SEPM Intersociety Grainsize Study Committee (cf. Tanner, 1969; Friedman and Sanders, 1978).
The main change concerns the lowering of the silt-clay boundary from 4 µm (8 phi) to 2 µm (9 phi).
However, not everyone has accepted the change and the 4-µm boundary therefore continues to be used,
especially in North America and East Asia. To highlight the distinction between sortable silt and
aggregated mud, these size groups have also been indicated in Fig. 20.
3.02.5.2. Sedimentary facies descriptions
Besides classifying sediments according to specific grain-size limits, there is also a need to provide
descriptive terminologies (nomenclatures) for various sediment types, such as the mixtures of sand-
silt-clay or gravel-sand-mud commonly observed in nature. Such textural classifications are, amongst
others, useful in the description and representation of sedimentary facies on geological maps or in core
logs. Ternary diagrams, in which sand-silt-clay or gravel-sand-mud ratios are graphically represented,
have proven particularly useful in this context and a variety of classifications based on such diagrams
have been developed since the 1940s (cf. Shepard, 1954). Frequently used ternary schemes for sand-
silt-clay mixtures are those by Shepard (1954) and Folk (1954). Unfortunately, the spatial boundaries
of individual classes having the same names in the two schemes do not coincide. In effect this means

28
that, irrespective of the scheme favored, it is important to reference its origin in order to avoid
confusion. Unfortunately, the practice of identifying the source classification is often neglected.
Fig. 20. Grain-size classification on the basis of the binary Udden-Wentworth scheme (Wentworth, 1922), as
modified by the SEPM Intersociety Grainsize Study Committee (cf. Tanner, 1969). Note that, contrary to the
recommendations of the Committee, a silt-clay transition at 4 μm is still frequently used, especially in North
America and East Asia, the silt class names shifting up one category (i.e. the class name “very coarse silt” drops
out in this case). The division between sortable silts and aggregated muds at 8 μm is based on Chang et al.
(2007).
The use of the Shepard and Folk diagrams requires detailed information on sediment composition
down to the clay fraction. Since the determination of the clay content is technically involved, time
consuming, and in many studies not required, a simpler two-component scheme has been devised in
which silt and clay are summed up under the category ‘mud’ (Flemming, 2000). This is achieved by
subdividing the ternary diagram by five lines running parallel to the silt-clay baseline to produce six
(6) class names (Fig. 21). The class names, for example ‘sandy mud’, can be extended to indicate
sedimentary facies, e.g., a ‘sandy mud facies’ or, in the case of an intertidal deposit, a ‘sandy mud flat’.
As the separation of sand and mud is a primary routine in sediment analysis, this simplified scheme
can be generated with little effort from any basic sediment data set. In addition, it reflects the energy
gradient from sand to mud. The associated class names and their boundary values are listed in Table 1.
To extend the two-component system into a spatially better resolved three-component system, Fig.
21 can be expanded by adding a number of lines fanning out symmetrically from the sand end-member
towards the silt-clay baseline (Flemming, 2000). In this way twenty-five (25) classes or sediment types
are defined (Fig. 22, Table 2), a number that substantially exceeds the 10 (unequal) classes of the
Shepard and Folk schemes. As in the latter cases, this scheme requires the determination of the clay
content in addition to sand and mud (silt = mud - clay). The excellent spatial resolution of sedimentary

29
facies that can be achieved with this more detailed scheme has recently been demonstrated for the
Venice Lagoon by Molarinoli et al. (2007, 2009). In addition, these authors have been able to identify
primary energy gradients by establishing good correlations between the spatial arrangement of the
lagoonal sediment types and root-mean-square (rms) current velocities and mean water residence
times (wrt).
Fig. 21. Ternary diagram for the distinction of various two-component sand-mud mixtures (based on Flemming,
2000).
Table 1. Descriptive terminology of the two-component sand-mud sedimentary system illustrated in Fig. 21 and
that distinguishes six (6) textural classes (after Flemming, 2000).
Mud content (%)
Textural class name
<5
Sand
5–25
Slightly muddy sand
25–50
Muddy sand
50–75
Sandy mud
75–95
Slightly sandy mud
>95
Mud
Fig. 22. Ternary diagram for the distinction of various three-component sand-silt-clay mixtures (based on
Flemming, 2000).

30
Table 2. Descriptive terminology of the three-component sand-silt-clay sedimentary system illustrated in Fig. 22
and that distinguishes twenty-five (25) textural classes (after Flemming, 2000).
Code
Textural class name
Code
Textural class name
S
Sand
D-I
Extremely silty slightly sandy mud
A-I
Slightly silty sand
D-II
Very silty slightly sandy mud
A-II
Slightly clayey sand
D-III
Silty slightly sandy mud
D-IV
Clayey slightly sandy mud
B-I
Very silty sand
D-V
Very clayey slightly sandy mud
B-II
Silty sand
D-VI
Extremely clayey slightly sandy
mud
B-III
Clayey sand
B-IV
Very clayey sand
E-I
Silt
E-II
Slightly clayey silt
C-I
Extremely silty sandy mud
E-III
Clayey silt
C-II
Very silty sandy mud
E-IV
Silty clay
C-III
Silty sandy mud
E-V
Slightly silty clay
C-IV
Clayey sandy mud
E-VI
Clay
C-V
Very clayey sandy mud
C-VI
Extremely clayey sandy mud
Finally, in order to be able to account for gravel in the description of coastal and estuarine
sediments, gravel-sand-mud ratios can be plotted into the ternary diagram of Blair and McPherson
(1999), a slightly modified version of a similar diagram originally developed by Folk (1954). This
diagram, in which fifteen (15) textural classes are distinguished, is illustrated in Fig. 23 (modified after
Blair and McPherson, 1999). The associated terminology is listed in Table 3.
Fig. 23. Ternary diagram for the distinction of various three-component gravel-sand-mud mixtures (modified
after Blair and McPherson, 1999).

31
Table 3. Descriptive terminology of the three-component gravel-sand-mud sedimentary system illustrated in Fig.
23 and that distinguishes fifteen (15) textural classes (after Blair and McPherson, 1999).
Code
Textural class name
Code
Textural class name
G
Gravel
(s)G
Slightly sandy gravel
gmS
Gravely muddy sand
(m)G
Slightly muddy gravel
gsM
Gravely sandy mud
sG
Sandy gravel
gM
Gravely mud
msG
Muddy sandy gravel
(g)S
Slightly gravely sand
smG
Sandy muddy gravel
(g)mS
Slightly gravely muddy sand
mG
Muddy gravel
(g)sM
Slightly gravely sandy mud
gS
Gravely sand
(g)M
Slightly gravely mud
3.02.6 Geotechnical sediment properties
3.02.6.1. Definition of basic mass physical sediment parameters
The distinction between sortable silts and aggregates was introduced above to highlight the
different behavior of these fine-grained particle groups during erosion, transport and deposition.
However, the two particle groups also differ fundamentally in another important mass physical
property, one that is commonly subsumed under the term “cohesiveness”. Thus, in textural terms,
coastal and estuarine deposits consisting of sortable silts would be classified as non-cohesive muds,
whereas those consisting of aggregates would form cohesive muds. However, in nature such pure
deposits are found at best as end-members along particular energy gradients, whereas most other
sediments consist of progressive mixtures, as also intimated by the ternary classification schemes
introduced above.
Although it is clear that the cohesiveness of sediments is related to the mud or clay content, the
phenomenon has commonly been investigated by comparing the dynamics of distinctly non-cohesive
with those of distictly cohesive sediments (cf. Dyer, 1986, Soulsby, 1997, Whitehouse et al., 2000, and
Winterwerp and van Kesteren, 2004, for comprehensive treatments). Variable mixtures between the
two have, by comparison, received much less attention (e.g., Williamson and Ockenden, 1993;
Mitchener and Torfs, 1996) and, until very recently, it was still a matter of debate as to how much mud
or clay was actually required to initiate cohesion. Thus, Mitchener and Torfs (1996) suggested a
transitional range of 3–15% mud content, whereas Howing (1999) identified a 20% mud content as the
transition. These uncertainties demonstrate that the problem is not simply an issue of the weight-%
content of mud or clay, but that other and hitherto poorly understood factors evidently also play an
important role (e.g., organic matter content, microbiological activity).
Keeping these limitations in mind, van Ledden et al. (2004) suggest the transition from non-
cohesion to cohesion to occur somewhere between 5 and 10% of clay content. They propose a mean
clay content of 7.5% as the best compromise. To illustrate this, the scheme has been superimposed on
the two-component sediment classification scheme (Fig. 24). The horizontal red lines separate the
cohesive realm (above) from the non-cohesive one (below). Thus, in descriptive terms, a ‘cohesive
muddy sand’ can, for example, be distinguished from a ‘non-cohesive muddy sand’, etc. The scheme
can, of course, be superimposed on any other ternary sand-silt-clay diagram. In addition, the network
structure (fabric) that supports the sediment is defined by the diagonal broken green lines on the lower
left and their blue counterparts on the lower right. The percentage values correspond to average

32
volume fractions of water in the sediment, 40% being typical for sands or silts consisting of mineral
grains having a density of 2.65 g cm-3. Together with the red lines, the blue and green lines divide the
ternary diagram into a number of zones that are characterized by particular network structures (fabrics).
Thus, sand-dominated network structures (zones I, II) are distinguished from silt-dominated ones
(zones V, VI), a mixed sand-silt dominated one (zone III), and a clay-dominated one (zone IV) (van
Ledden et al., 2004).
Fig. 24. Criteria for sediment cohesion (red lines) and framework structure (broken green and blue diagonal
lines) after van Ledden (2004) superimposed on the ternary two-component sand-mud sediment classification
scheme of Fig. 21. For more details see text.
Other common mass physical properties that are frequently determined for a variety of purposes,
e.g., to assess the geotechnical nature of sedimentary deposits, to assess the erosion behaviour of
sediments, or to relate bio(geo)chemical parameters to sediment parameters, are the water content, the
wet and dry bulk densities, the porosity, and the carbonate content (e.g., Flemming and Delafontaine,
2000). In the case of water content, two forms have to be carefully distinguished, i.e. the ‘relative
water content’ (Wr), which is defined as the ratio between the mass of pore water (Mw) and the mass of
the dry solids (Ms), and the ‘absolute water content’ (Wa), which is defined as the ratio between the
mass of pore water (Mw) and the mass of the total water-saturated sample (Mt). In both cases water
contents are commonly expressed as percentage values. Thus,
Wr = (Mw/Ms)100 (10)
Wa = (Mw/Mt)100 (11)
The difference between the two measures is that the relative water content can reach several
hundred percent, i.e. the mass of the water can greatly exceed the mass of the dry solids, whereas the
absolute water content is always a fraction of one hundred. Relative water contents <100% can
therefore be confused with absolute contents and, in such cases, it should be indicated whether relative
or absolute water contents have been determined. The water contents determined from equations (10)
and (11) refer to samples recovered from freshwater environments. If the samples were recovered in
salt water or brackish water environments, then a correction for the salt content (r) is required if the

33
water content was determined by the weight loss after drying. In this case, the corresponding equations
are:
Wr = [(Mt-Ms)(1+r)/Mt]100 (12)
Wa = [(Mt-Ms)/(Ms-rMt)]100 (13)
In the case of bulk density determinations, the wet bulk density (BDw), defined as the ratio between
the total water-saturated sediment mass (Mt) and the volume of the water-saturated sediment (Vt), has
to be distinguished from the dry bulk density (BDd), defined as the ratio between the mass of the dry
solids (Ms) and the volume of the water-saturated sediment (Vt). Thus,
BDw = Mt/Vt (14)
BDd = Ms/Vt (15)
Again, the dry sediment masses have to be corrected for any salt content if they were determined by
loss of weight after drying.
There is generally a high correlation between mud content and bulk density and average values of
the latter can thus be calculated from the former once an appropriate calibration curve has been
established for a particular region. By the same token, bulk densities can be calculated from the water
contents of the sediment. As illustrated in Fig. 25, there is an excellent correlation between dry bulk
density (BDd) and water content (Wc%), the curve being universally valid for sediments having an
average density of 2.65 g cm-3. Thus,
BDd = 2.6596369 – 0.0886164(Wc%) + 0.0088041(Wc%)1.5 – 0.0002594(Wc%)2 (16)
Fig. 25. Dry bulk density of Wadden Sea sediments as a function of water content (modified after Flemming and
Delafontaine, 2000). The regression has universal validity for sediments consisting of particles having an
average density of 2.65 g cm-3 (e.g., quartz, carbonates, clay minerals).

34
The porosity (η) of sediment is defined as the ratio between the volume of the pore space (Vp) and
the total volume (Vt) of the water-saturated sample, expressed as a percentage value. Thus,
η = (Vp/Vt)100 (17)
In a simplified approach, η can easily be calculated because Vp is directly proportional to the mass of
the pore water (without salt) and Vt corresponds to the sum of Vp and the volume of the dry solids (Vs),
the latter being directly proportional to the average grain density, which in most cases can be assumed
to approximate 2.65 g cm-3. This is a reasonable assumption as coastal and estuarine sediments
commonly consist of quartz, carbonates, and clay minerals, all of which have similar average densities.
On the other hand, average grain densities can also be determined by calibrated pycnometer
measurements. If necessary, corrections for organic matter contents can be made on the basis of
similar reasoning.
Carbonate contents of estuarine and coastal sediments can either be determined by the weight loss
induced after acid digestion or by more involved analytical techniques, the former being generally
acceptable at carbonate contents exceeding 5-10% by weight. Where carbonate contents are low, a
more precise procedure is to calculate the CaCO3-content after measuring the total carbon content (Ct)
and the organic carbon content (Corg) in sediment samples, all expressed as percentage values. Thus,
%CaCO3 = (%Ct - %Corg) 8.33 (18)
For other mass physical parameters and advanced analytical procedures , Lambe and Whitman
(1969), Carver (1971), Inderbitzen (1974), Dunn et al. (1980), Hillel (1998) and Warrick (2002) all
carry more detailed treatments.
3.02.6.2. Applications of mass physical sediment parameters
The mass concentrations of the bulk sediment are a sum of the individual sediment components.
This is illustrated in Fig. 26A (left panel), where the dry mass concentrations of the sand and mud
components as a function of mud content of Wadden Sea sediments are contrasted with the trend
described by the total sediment (sand + mud). Of particular importance here is the counter-intuitive
trend described by the dry mass concentration of the mud component (Fig. 26B, right panel). Thus,
with increasing mud content, the mass concentration of mud at first increases as expected. Unexpected,
and hence counter-intuitive, is that the mass concentration does not continue to increase with
increasing mud content but, instead, reaches a peak (in this case at a mud content of about 60%) and
thereafter decreases again towards 100% mud content. This trend can be explained by the changing
network structure (fabric) of the sediment as mud and water contents increase beyond the apex of the
trend line. In effect this means that, in a unit volume of Wadden Sea sediment, the amount of material
contained in pure mud (>95% mud content) is equal to that reached at a mud content of about 23%,
while at its peak concentration (at 60% mud content) it is by a factor of 1.37 larger than at 100% mud
content. It must be emphasized that the particular trend observed in Wadden Sea sediments does not
necessarily apply to other coastal or estuarine environments and calibration curves are thus required
for any study area before local relationships can be assessed. However, once a calibration has been
established most mass physical properties of a study area can be determined from basic parameters
such as the mud or water content.

35
Fig. 26. Dry mass concentration of Wadden Sea sediments as a function of mud content (modified after
Flemming and Delafontaine, 2000). Note that in A (left panel) the trend line of the total sediment is the sum of
the trend lines of the sand and mud fractions. The counter-intuitive trend in the mass concentration of the mud
fraction as a function of mud content is highlighted in B (right panel).
This unexpected behaviour of mud mass concentration as a function of mud content has far-
reaching implications because other parameters linked to the mud fraction (e.g., organic matter, trace
elements, pollutants) will by necessity follow a similar trend. Contrary to common perception, highest
mass concentrations of mud, and hence of any substance linked to the mud fraction, are found in
mixed sediments (muddy sand and sandy mud) and not in pure mud. This potentially confusing issue
is explained by the fundamental and often overlooked difference between content (mass per unit mass)
and concentration (mass per unit volume) (cf. Flemming and Delafontaine, 2000, for a detailed
discussion). For example, in marine biology, microbiology and biogeochemistry it is common practice
to relate measures of concentration (e.g., number of individuals per m2) to values of a variety of
parameters such as organic carbon or other chemical compounds (expressed as weight-%). However,
as shown by Bird and Duarte (1989), the mixing-up of different dimensions can produce spurious
trends that have no scientific meaning and which can result in the misinterpretation of otherwise good
data (cf. Flemming and Delafontaine, 2000). The conceptual error made in such studies is illustrated in
Fig. 27. Instead of relating a biological parameter expressed per unit area against a bio(geo)chemical
parameter expressed per unit volume, it is common practice to express the latter parameters per unit
mass. By doing this, it goes unnoticed that, in the example of Fig. 27, the organisms living in 1 m2 at
all three sites are being related to organic matter proportional to 1 m2 at the sand site, 2 m2 at the
mixed sand-mud site, and 5 m2 at the mud site (represented by the yellow squares). The simple reason
for the discrepancy (and hence the resulting error) is the change in bulk density (or water content) of
the sediment with increasing mud content, i.e. the lower the bulk density (or the higher the water
content), the larger the volume of a unit mass of sediment. The organic matter, in this case, is thus
overrated by a factor of 2 in the mixed sediments and by a factor of 5 at the mud site.
Unfortunately, such misrepresentations pervade the scientific literature (cf. Flemming and
Delafontaine, 2000) and errors have found their way into models (e.g., Paarlberg et al., 2005; Borsje,
2008), manuals (e.g., Gray and Elliot, 2009), and environmental guidelines and directives (e.g.,
Bjørgesæter and Gray, 2008). That this is not merely a matter of semantics can be illustrated by the
meaning of ‘salinity’. It is common knowledge that the synonym for salinity is (and has been for
centuries) ‘salt content’, not ‘salt concentration’. Salt content means the amount of dissolved salt in 1
kg of seawater. The salt concentration, by contrast, would be the amount of salt in 1 l of seawater.
Clearly, 1 kg of standard seawater (35 psu) has a volume of slightly less than 1 l, whereas 1 l of

36
standard seawater weighs slightly more than 1 kg. Although for standard seawater the difference is
small (about 2%), the error rapidly increases with increasing salinity, e.g. reaching almost 10% in the
case of brine from the Dead Sea.
Fig. 27. Relative areas (or volumes) of Wadden Sea sediments in relation to the bulk density of pure s and, of a
50:50 sand-mud mixture, and of pure mud (modified after Flemming and Delafontaine, 2000). Note the
increasing areas (volumes) occupied by a unit sediment mass with decreasing bulk density (yellow squares).
In the years since the problem was highlighted by Flemming and Delafontaine (2000), steady
progress has been made in eliminating the misuse of content-based measurements (which are
important measures in other contexts). Thus, Perkins et al. (2003), Tolhurst et al. (2005, 2008), Köster
et al. (2005), Jesus et al. (2006), Chapman and Tolhurst (2007), amongst others, have resorted to only
relating measures of concentration to each other, thereby correcting previous errors and posing novel
interpretations and questions that would otherwise never have been asked. Progress has also been
made in developing remotely-sensing instrumentation capable of measuring mass physical sediment
properties, including concentration-based properties (e.g., de Groot et al., 2009; Jacobs et al., 2009).
3.02.7. Sampling strategies
In view of the issues raised above in connection with sediment analyses and the measurement of
mass physical sediment properties, one may question whether standard sampling procedures are
always appropriate. It is, for example, difficult to find studies where the choice of sampling sites has
been adequately justified in terms of how representative they are in characterizing the various parts of
a wider study area. In the case of generating sediment distribution maps, the problem does not
generally arise because sample preparation and analysis are fairly rapid so that large sample numbers
taken on dense grids can easily be handled. More problematical are situations where only a limited
number of samples can be processed. In such cases the location of transects and the choice of sample
positions along them may be critical. Most commonly, sample positions are selected on the basis of
subjective rather than rational decisions, precursor or pilot studies aiming at identifying the most
representative locations being rarely carried out. This section aims at providing a rational basis for the
best choice of sample positions along sediment gradients comprising progressive mixtures of sand and
mud, particularly in cases where the number of samples that can be taken is limited.
The basis for the proposed sampling strategy is the diagram in Fig. 28, in which the dry mass
concentration of mud (g cm-3) is plotted against the mud content (dry weight-%) and which
corresponds to the right panel in Fig. 26. The regression curve represents the average conditions
relative to the mud fraction, which – in many respects – is the most important sediment fraction. To be
representative, sample stations should lie as close as possible to the regression line, besides being

37
evenly distributed along it. In order to generate such a regression, a pilot study is recommended during
which small but well defined samples are recovered until a good spread across the sand-mud gradient
has been achieved, i.e. the samples should in the end cover mud contents at intervals of roughly 5%. In
all cases, several samples should be taken at each site in order to reduce the probable sampling error.
According to Krumbein (1934b; also see Krumbein and Pettijohn, 1938), the probable sampling error
is reduced by about 30% when 2 samples are taken, by 50% at 4 samples, by 60% at 6 samples, etc.
As can be seen, the gain in error reduction decreases as the sample number increases, 10 samples
merely achieving a 70% error reduction. Therefore, to optimize time and effort, sample numbers
between 2 and 4 are recommended.
Fig. 28. Rationalized sampling strategy (numbered red dots) on the basis of the dry mass concentration of mud as
a function of mud content (modified after Flemming and Delafontaine, 2000). Note that the sample positions
should lie as close as possible to and be spread along the regression line in order to be representative of the study
area.
In order to gain as much mass physical information as possible from these samples, a minimum
sample volume of 50-60 cm3 is recommended. The samples should be recovered in such a manner as
to minimize sediment disturbance and to avoid subsequent loss of sediment and pore water, e.g. by
using specially prepared short coring vials. The position of each sampling site should be determined as
accurately as possible (e.g., by GPS). Since sample masses are small, weight is not a limiting factor
during the pilot campaigns. Following standard procedures, wet and dry bulk densities, water contents,
mud contents, organic matter or POC-contents, carbonate contents, etc. can be determined on the
whole sample or on small subsamples. The mud contents covered by the first sampling campaign can
then form the basis for subsequent campaign(s) to close the gaps in the progression from 0 to 100%
mud content. If two samples are recovered per site and the spacing corresponds to about 5% mud
content intervals, then the total number of samples for the calibration would amount to 42.
Once all samples have been acquired and analyzed, dry mass concentrations are plotted against
mud contents, and the regression is calculated. A rational decision as to the most interesting sample
locations for subsequent detailed investigations can then be made using the GPS data for guidance in
the field. In the case of Fig. 28, for example, a scientifically interesting strategy would be to select
study sites at the numbered positions (red dots) along the regression curve (7 stations) for detailed
investigations. In addition, one or two extraneous sample positions can be chosen to investigate why
these locations depart so much from the average trend. This rationalized procedure optimizes time and
effort without jeopardizing scientific objectives and standards.

38
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