Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
www.hydrol-earth-syst-sci.net/17/2029/2013/
doi: 10.5194/hess-17-2029-2013
© Author(s) 2013. CC Attribution 3.0 License.
Hydrology and f
Earth System >
S cien ces I
Global multi-scale segmentation of continental and coastal waters
from the watersheds to the continental margins
G. G. Laruelle1, H. H. Dürr2 4, R. Lauerwald13, J. Hartmann3, C. P. Slomp2, N. Goossens1, and P. A. G. Regnier1
1Biogeochemical Modelling of the Earth System, Dept, of Earth & Environmental Sciences, CP 160/02,
Université Libre de Bruxelles, 1050 Brussels, Belgium
2Department of Earth Sciences - Geochemistry, Faculty of Geosciences, Utrecht University, Utrecht, the Netherlands
institute for Biogeochemistry and Marine Chemistry, KlimaCampus, Universität Hamburg, Bundesstrasse 55,
20146 Hamburg, Germany
4Ecohydrology Reserach Group, Dept. Earth and Environmental Sciences, University of Waterloo, Waterloo,
ON, N2L 3G1, Canada
Correspondence to: G. G. Laruelle (goulven.gildas.laruelle@ulb.ac.be)
Received: 20 August 2012 - Published in Hydrol. Earth Syst. Sei. Discuss.: 4 October 2012
Revised: 30 April 2013 - Accepted: 2 May 2013 - Published: 29 May 2013
Abstract. Past characterizations of the land-ocean contin­
uum were constructed either from a continental perspec­
tive through an analysis of watershed river basin proper­
ties (COSCATs: COastal Segmentation and related CATchments) or from an oceanic perspective, through a regionaliza­
tion of the proximal and distal continental margins (LMEs:
large marine ecosystems). Here, we present a global-scale
coastal segmentation, composed of three consistent levels,
that includes the whole aquatic continuum with its river­
ine, estuarine and shelf sea components. Our work delineates
comprehensive ensembles by harmonizing previous segmen­
tations and typologies in order to retain the most impor­
tant physical characteristics of both the land and shelf areas.
The proposed multi-scale segmentation results in a distribu­
tion of global exorheic watersheds, estuaries and continental
shelf seas among 45 major zones (MARC ATS: MARgins and
CATchments Segmentation) and 149 sub-units (COSCATs).
Geographic and hydrologie parameters such as the surface
area, volume and freshwater residence time are calculated
for each coastal unit as well as different hypsometric pro­
files. Our analysis provides detailed insights into the distri­
butions of coastal and continental shelf areas and how they
connect with incoming riverine fluxes. The segmentation is
also used to re-evaluate the global estuarine CO 2 flux at the
air-water interface combining global and regional average
emission rates derived from local studies.
1
Introduction
The land-ocean aquatic continuum is commonly defined as
the interface, or transition zone, between terrestrial ecosys­
tems and the open ocean (Billen et al., 1991: Mackenzie et
al., 2012: Rabouille et al., 2001: Regnier et al., 2013). This
continuum includes inland waters, estuaries and coastal wa­
ters (Billen et al., 1991: Crossland et al., 2005: Liu et al.,
2010), a succession of biogeochemically and physically ac­
tive systems that not only process large quantities of car­
bon and nutrients during their natural transit from upland
soils to the open ocean (Arndt et al., 2007, 2009: Laruelle,
2009: Mackenzie et al., 2005: Nixon et al., 1996: Regnier
and Steefel, 1999: Vanderborght et al., 2002, 2007), but also
exchange vertically significant amounts of greenhouse gases
with the atmosphere (Cole et al., 2007: Laruelle et al., 2010:
Tranvik et al., 2009: Regnier et al., 2013). Although the landocean aquatic continuum is acknowledged to play a signif­
icant role in global biogeochemical cycles (Gattuso et al.,
1998: Mackenzie et al., 1998: Mantoura et al., 1991), the
quantitative contribution of inland waters, estuaries and con­
tinental shelves to carbon and nutrient budgets remains en­
tailed with large uncertainties, reflecting primarily the lim­
ited availability of field data and the lack of robust upscaling
approaches (Regnier et al., 2013).
Over the past few years, a growing number of environ­
mental databases dedicated to inland waters (GLORICH,
Published by Copernicus Publications on behalf of the European Geosciences Union.
2030
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
Hartmann et al., 2011), estuaries (Engle et al., 2007) and the
coastal zone have been assembled (LOICZ, Crossland et al.,
2005). Extrapolation of the numerous local measurements in
these databases to provide regional and global budgets calls
for the segmentation of the aquatic continuum into areas
of broadly similar biogeochemical and physical behaviour,
based on multiple criteria such as climate, morphology and
physical forcings. In addition, the surface area and volume
of the resulting segments need to be constrained for budget­
ing purposes, a task that is more complex than one might
actually presume. For instance, the geographical extent of
the continental shelf itself (i.e. the extended perimeter of a
continent, usually covered by shallow seas) is still a matter
of debate (Borges et al., 2005; Chen et al., 2012; Liu et al.,
2010), partly because there is no common definition of its
outer limit. So far, the delineation of the coastal ocean has
been constrained using administrative limits (Sherman and
Alexander, 1989), the 200 m isobaths (Walsh, 1988) or the
maximum increase in slope of the seabed (Liu et al., 2010),
leading to surface area estimates that differ by up to 20 %.
Similar issues arise for the delineation of regional boundaries
on land (Meybeck et al., 2006, 2013). It has however been
shown that a careful segmentation of continental shelf seas
into representative units together with a robust, GIS-based
estimation of the corresponding surface areas contributes to
improved biogeochemical budgets, as exemplified by the re­
vised global air-water CO 2 exchange flux estimated by Laru­
elle et al. (2010) for the coastal ocean.
At the global scale, a segmentation that incorporates con­
sistently the aquatic continuum of inland waters, estuaries
and continental shelves remains to be developed. A major
difficulty arises because their spatial scales are fundamen­
tally different and may vary regionally. For instance, estu­
aries exhibit typical length and width scales ranging from 1
to 100 km and are thus much smaller entities than large-scale
coastal entities delimited by well-established currents such as
the Gulf Stream or the California Current, which flow along
continents over thousands of kilometres (Longhurst, 1998).
The largest rivers in the world exceed thousands of kilo­
metres in length but require a representation of their river
network at resolutions < 1 degree for a proper identifica­
tion of the routing of their main tributaries (Vörösmarty et
al., 2000a, b). Moreover, environmental databases gathering
monitoring data, climatological forcings and average earth
surface properties are available under various forms and at
different spatial resolutions. Some consist of gridded maps,
files or model outputs at 0.5 or 1 degree resolution (World
Ocean Atlas, DaSilva et al., 1994; Levitus et al., 1998; GlobalNEWS, Mayorga et al., 2010; Seitzinger et al., 2005) while
others are databases containing measurements from millions
(SOCAT, Pfeil et al., 2012) to thousands (GLORICH) or just
several dozen (Lonborg and Alvarez-Salgado, 2012; Laruelle
et al., 2010; Seiter et al., 2005) of unevenly distributed sam­
pling points. Thus, for environmental budgeting purposes,
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
a multi-scale approach is required to integrate and combine
this variety of databases.
In this study, we present a harmonized multi-scale seg­
mentation for the land-ocean continuum, from the watershed
to the outer limit of the continental shelf. It is based on three
increasing levels of aggregation, and the inter-compatibility
of these levels not only allows the integration of a wide vari­
ety of databases compiled at various spatial resolutions, but
also the comparison and combination of them with one an­
other. The first level, at the finer resolution of 0.5 degrees,
is based on the work of Vörösmarty et al. (2000a, b) and
resolves the watersheds and river routing. It also attributes
an estuarine type to each watershed following the typology
of Dürr et al. (2011), which includes small deltas, tidal sys­
tems, lagoons and fjords. This spatial resolution allows for
a realistic representation of the global river network and is
compatible with many global databases (World Ocean At­
las, LOICZ, Buddemeier et al., 2008; Crossland et al., 2005).
This level is also suitable for detailed regional analyses of
coastal regions and their corresponding watersheds. The sec­
ond level is built on an updated version of the COSCAT
(COastal Segmentation and related CATchments) segmen­
tation (Meybeck et al., 2006), which distinguishes differ­
ent segments of the global coastline based on a combina­
tion of terrestrial watershed characteristics and coastal géo­
morphologie features. It is extended here to include the rele­
vant portions of the adjacent continental shelves. The highest
level in the hierarchy is termed MARCATS (for MARgins
and CATchments Segmentation) and consists of aggregated
COSCAT units according to the main climatological, mor­
phological and oceanographic characteristics of the coastal
zone. This new segmentation is inspired by a classification
of the continental shelf seas proposed in the recent synthesis
by Liu et al. (2010) and defines 45 regional units, which al­
low for coarser regional analysis and upscaling calculations
when data sets are limited. It nevertheless retains the major
physical features of many different coastal regions and iden­
tifies a number of widely studied systems such as the main re­
gional seas and some major coastal currents. It can be viewed
as an analogue to the coarse segmentation of Takahashi et
al. (2009) for the estimation of CO 2 fluxes in the open ocean.
The novelty of our approach thus lies in the development
of an integrated scheme that includes the entire land-ocean
continuum. Numerous studies already proposed global seg­
mentations or classifications from either an oceanic (Sher­
man and Alexander, 1989; Seiter et al., 2005) or terres­
trial perspective (Koppen, 1936; Meybeck et al., 2006, 2013;
Peel et al., 2007). Here, the COSCAT and MARCATS seg­
mentations were used to calculate, for different isobaths,
the surface area and volume of each segment of the coastal
ocean as well as the surface areas of watersheds and estuar­
ies. Our estimates are compiled into a global data set that
provides a new regionalized assessment of the size of the
different compartments of the land-ocean continuum (see
also www.biogeomod.net/geomap). The three levels of our
www.hydrol-earth-syst-sci.net/17/2029/2013/
G. G. Laruelle et al.: Global multi-scale segmentation of continental and coastal waters
segmentation can be used in conjunction with biogeochem­
ical databases (e.g. World Ocean Atlas, LOICZ, Hexacoral,
GLORICH, SOCAT, and so forth) to establish regional bud­
gets and, eventually, refine global assessments of the carbon
and nutrient cycles. This is performed in this study by pro­
viding regionalized estimates of CO 2 fluxes from estuarine
systems at the global scale. Furthermore, the combination of
several layers of increasing spatial resolution allows the in­
tegration, combination and comparison of various databases
through, for example, the calculation of average properties
for any given segment (watershed, COSCAT or MARCATS)
depending on the data density and availability. The segmen­
tation is also combined with watershed models (e.g. GlobalNEWS) to constrain, for each region of the world, the amount
of fresh water that is routed through the different estuarine
types and delivered to a given segment of the coastal ocean.
These volumes of fresh water are compared to those of the
continental shelves they flow into. Although not performed
here, the same approach could easily be expanded to terres­
trial carbon and nutrient fluxes. Thus, the newly compiled
and homogenized data set is applicable in a wide range of fu­
ture investigations of biogeochemical fluxes along the landocean continuum, which are still largely misrepresented or
ignored in current global circulation and Earth system mod­
els (Regnier et al., 2013). The GIS files provided in the Sup­
plement will allow the community to alter the approach or to
refine local settings if needed.
2
Segmentation: limits and definitions
The present study describes a segmentation of continental
waters based on three levels of increasing aggregation. The
finest segmentation corresponding to the lowest level of ag­
gregation (level I) resolves the 0.5 degree river network of
Vörösmarty et al. (2000a, b). This river network is generated
using digital elevation models to calculate the direction of the
surface water flow in each terrestrial cell of 0.5 degree resolu­
tion. The interconnections of the surface water flow direction
determine the path of each river and its tributaries. Each wa­
tershed is then delineated by the aggregation of all the cells
belonging to a given river, and subsequently connected to a
coastal cell. The global river network used here includes all
inland waters and provides a canvas for a coarser aggregation
consisting of a group of riverine watersheds on the continen­
tal side and an ensemble of contiguous continental shelf seg­
ments on the oceanic side (Fig. 1). This intermediate level of
aggregation is based on an updated version of the COSCAT
segmentation developed by Meybeck et al. (2006) (level II).
Finally, the merging of COSCATs units into larger entities
called MARCATS provides the coarsest segmentation (level
III).
www.hydrol-earth-syst-sci.net/17/2029/2013/
2031
U pper Slope
I
I B a s i n L im i ts
□
C O S C A T L im i t s
□
M ARCA TS L im i t s
Fig. 1. M ap o f equatorial South A m erica displaying the 3 lay­
ers o f the segm entation and their boundaries ( 1 - w atersheds, 2 C O SCA Ts, 3 - M A RCA TS).
2.1
COSCAT segmentation and GIS calculations
The COSCATs are homogeneous geographical units which
are independent of administrative borders. They primarily
rely on lithological, morphological, climatic and hydrolog­
ical parameters to partition the global coastline into seg­
ments with similar properties. The total number of COSCAT
units amounts to 149 for an average coastline length of
3000 km. Meta-watersheds attributed to each coastal seg­
ment are constituted of all the individual watersheds whose
rivers discharge within the corresponding COSCAT. Follow­
ing Laruelle et al. (2010), each COSCAT is also associated
with a section of the continental shelf adjacent to the coast­
line. The lateral boundaries of a specific shelf unit are de­
fined by perpendicularly extrapolating the limits of the cor­
responding coastal segment from the shoreline to the 1000 m
isobaths, extracted from 1 min resolution global bathymetries (see below). Where the limit between two COSCATs
on the shelf corresponds to a major topographic feature
such as a submarine ridge or the connection between two
oceanic basins, this feature is used as boundary instead. For
the purpose of the study, a number of minor modifications
were applied to the original COSCAT boundaries, to account
for stretches of coasts with similar estuarine characteristics
(Dürr et al., 2011) or the profile of some continental shelves.
The COSCAT 401 running from the Strait of Gibraltar to
the Atlantic border between France and Spain was split into
two segments (COSCATs 401 and 419), corresponding to
the northern and western Iberian coasts, respectively. The
COSCATs 414 and 1302, corresponding to the European and
Asiatic coasts of the Aegean Sea, were merged. The bound­
ary between COSCATs l i l i and 1112, at the southern edge
of South America in the Pacific, was moved northward to ac­
count for the change in estuarine types from fjords to arheic
(Dürr et al., 2011). In addition, all endorheic watersheds were
excluded from the study. This includes the four COSCAT
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
2032
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
segments flowing into the Aral and Caspian seas (410, 1304
1306). The Antarctic continent, on the other hand, was incor­
porated using five new COSCATs (1501 to 1505). A map of
all the COSCAT segments and their updated limits is pro­
vided as a Supplement.
The isobaths on continental shelves were extracted from
1 min resolution global bathymetries. The version 9.1 of the
bathymetry of Smith and Sandwell (1997, updated in 2007,
http://topex.ucsd.edu/marine_topo) was preferably used as it
generally better represents very near shore coastal features
(Dürr et al., 2011). However, its geographical coverage does
not extend past 80° N and S. Beyond this limit, the isolines
were then extracted from the ETOPO 2 bathymetry (US De­
partment of Commerce, National Oceanic and Atmospheric
Administration, National Geophysical Data Center, 2006,
http://www.ngdc.noaa.gov/mgg/fliers/06mgg01.html). In the
Northern Hemisphere, this concerns the northern part of the
Canadian archipelagos and Greenland as well as the Russian
Arctic shelves. In the Southern Hemisphere, it only affects
Antarctica. Ten isobaths were extracted for each COSCAT:
20 m, 50 m, 80 m, 120 m, 150 m, 200 m, 350 m, 500 m, 750 m
and 1000 m. After a conversion from grid data to vector poly­
gons using CIS, the surface area and average water depth
were calculated for each polygon. The aggregation of poly­
gons for each COSCAT provides the surface area and the
volume of a shelf segment comprised between two isobaths.
Table 1 summarizes the globally integrated surface areas
and volumes of the continental shelves for the succession of
depth intervals.
For each COSCAT, the depth at which the shelf breaks
was estimated by calculating the slope of the sea floor. The
outer limit of the shelf was defined as the isobath for which
the increase in slope is the maximum over the 0-1000 m in­
terval, yet still inferior to 2 %. This value was selected as a
compromise between the average slope and the upper conti­
nental slope of 0.5 and 3 %, respectively, although the latter
varies between 1 % and 10 % (Gross, 1972; Pinet, 1996). Lo­
cally, some very irregular topographic features smaller than
the spatial resolution of our bathymetric grid induced arte­
facts which required manual corrections based on geographic
atlases (New York Times, 1992).
2.2
MARCATS segmentation
The coarsest segmentation (level III) aggregates COSCAT
units into larger geographical boundaries whose limits ac­
count for oceanic features such as coastal currents or the
boundaries of marginal seas. The resulting 45 units (Fig. 2),
named MARCATS, are an aggregation of 3-4 COSCATs
on average. Some MARCATS, however, correspond to one
COSCAT only when their boundaries embrace a well-defined
coastal current like the Leeuwin Current (MARCATS 33,
LEE), which flows southward off the coast of Australia and
differs in nature from adjacent COSCATs (Pearce, 1997).
Other MARCATS are an aggregation of up to 10 COSCATs
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
Table 1. G lobal surface areas and volum es o f coastal seas betw een
various isobaths. The integrated values betw een the shore and the
deepest isobaths are also provided.
D ep th (m)
C um ulative
V olum e (IO6 k m 3 )
C um ulative
0 -2 0
2 0 -5 0
5 0 -8 0
4.969
7.413
5.100
12.379
17.480
0.053
0.260
0.330
0.312
0.643
8 0 -1 2 0
1 2 0 -1 5 0
1 5 0 -2 0 0
2 0 0 -3 5 0
4.306
2.124
2.476
4.550
21.786
23.909
26.386
30.937
0.428
0.287
0.434
1.234
1.070
1.358
1.792
3.026
3.083
3.401
2.417
39.838
34.020
37.421
39.838
1.307
2.098
2.113
8.545
4.333
6.432
8.545
3 5 0 -5 0 0
5 0 0 -7 5 0
7 5 0 -1 0 0 0
Total
S urface (IO6 k m 2 )
in the case of a large marginal sea like the Mediterranean
Sea (MARCATS 20, MED). Each MARCATS was attributed
a type following Liu’s classification of continental shelf seas
(Liu et al., 2010). The different classes considered here are
eastern boundary current (EBC, 1), western boundary current
(WBC, 2), monsoon-influenced margins (3), sub polar mar­
gins (4), polar margins (5), marginal seas (6), tropical mar­
gins (7).
Eastern and western boundary currents (1 and 2) are gen­
erated by large oceanic gyres when they flow parallel to the
continents. The lateral water flow created by Ekman’s cur­
rent perpendicular to the boundary current induces upwelling
of deeper waters, which sustain primary production where
the upwelling flux is large enough (Atkinson et al., 2005).
Monsoon-dominated margins (3) regroup all Indian Ocean
coasts where the hydrodynamics are strongly driven by the
seasonal wind patterns of the monsoon (Nag, 2010). Sub­
polar margins (4) are characterized by cool temperate wa­
ters located on latitudes higher than 50° N and lower than
30° S approximately. These limits are used to differentiate
them from the polar margins (5), which explicitly refer to
coastal waters surrounding the Arctic and Antarctic oceans.
Marginal seas (6) refer to interior seas only comprising rela­
tively shallow waters flowing on the continental shelf (Hud­
son Bay, Baltic Sea, Persian Gulf) or wider entities includ­
ing deep waters (Gulf of Mexico, Mediterranean Sea, Sea
of Japan, etc.). In the latter case, the MARCATS only cover
the generally narrow shelves surrounding the main regional
sea. An important characteristic of such marginal systems is
a generally longer renewal rate of water compared to other
systems directly connected to the open ocean (Meybeck and
Dürr, 2009). Last, tropical margins (7) are typically warm
coastal waters located in the tropics and form an equato­
rial belt around the Earth. The average temperature in such
areas is high (> 18 °C) all year long regardless of season­
ality. Note that some coastal regions present characteristics
corresponding to several classes. For instance, the Red Sea
could arguably be defined as a marginal sea influenced by the
monsoon. In such cases, a hierarchy of criteria was used to
identify the dominant characteristic. The first criterion is the
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G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
2033
Shelf T y p o lo g y
□
I
I
I
I
I
EBC
I WBC
I M onsoonal
I S ub p o lar
I P olar
I Marginal
I Tropical
I E ndorheic
Fig. 2. G eographic lim its o f M A RCA TS and CO SCA T segm ents w ith the typology o f M A RCA TS.
occurrence or absence of EBC
of a marginal sea is used and,
is applied. There is no overlap
classes (tropical, polar and sub
3
3.1
or WBC. Next, the presence
finally, monsoonal influence
between the three remaining
polar).
Results and discussion
MARCATS classification of continental shelves
Figure 2 presents the location and surface area of the 45
MARCATS units. Table 2 lists all the MARCATS and their
constitutive COSCATs for which the shelf break depth is also
given. The limits of the individual COSCATs are also repre­
sented by black lines in Fig. 2. The colour code corresponds
to the MARCATS classification, the continental shelves be­
ing highlighted in slightly darker colours. Note that the geo­
graphic projection used for this map over-represents the sur­
face area of high latitude regions - this has been corrected
for the surface area and volume calculations. EBC and WBC
(in orange and yellow, respectively) border most continents
at the mid-latitudes and account for a cumulative coastline
of over 70 000 km. The major upwelling regions (Califor­
nia, Morocco, Canary, Humboldt, etc.) are driven by EBC
or WBC: yet these currents generally follow the continents
over much larger distances than those corresponding to the
area where upwelling is intense (Longhurst, 1995; Xie and
Hsieh, 1975). In the Pacific, the MARCATS 2 (CAL) and 4
(HUM) exemplify this feature. They comprise five and three
COSCATs, respectively, while in reality, only one COSCAT
covers the high intensity upwelling area (COSCAT 805 for
the California Current and COSCAT 1114 for the Humboldt
Current, Table 2). The California Current, for instance, is a
part of the North Pacific Gyre, which extends up to the lat­
itude corresponding to British Columbia in Canada (Karl,
1999; Mann and Lazier, 2006), although the upwelling is
www.hydrol-earth-syst-sci.net/17/2029/2013/
induced along the south-western coast of the United States.
In the Atlantic, Northern Hemisphere EBCs are located in
the zone along Senegal to the Iberian Peninsula, and pro­
duce the Morocco (MARCATS 22, MOR) and Portugal upwellings (MARCATS 19, IBE). In the Southern Hemisphere,
the EBC is located off the coast of Namibia (Benguela Cur­
rent, MARCATS 24, SWA). The only EBC in the Indian
Ocean is the Leeuwin Current, located along the western bor­
der of Australia (MARCATS 33, LEE). The distribution of
WBCs essentially mirrors that of EBCs on the opposite side
of the oceans. In the Pacific Ocean, South East Asia is bor­
dered by a WBC in the north (MARCATS 39, CSK) and the
south (MARCATS 35, EAC). In the Atlantic, the Brazilian
(MARCATS 6, BRA) and the Florida currents (MARCATS
10, FLO) are the pair of WBCs, one per hemisphere. Finally,
in the Indian Ocean, the southern tip of Africa is associated
with the Agulhas Current, which flows from Madagascar to
Cape Town (MARCATS 25, AGU).
Margins under monsoonal influence (green) account for
about half of the length of the shelves in the Indian Ocean,
forming a 20 000 km long arc running from the coast of So­
malia (MARCATS 27, WAS) to the Bay of Bengal (MAR­
CATS 31, BEN), which also includes all the coast of India
(MARCATS 30, EAS). The main characteristic of this re­
gion is the seasonal inversion of wind patterns, affecting the
climate as well as the direction and strength of coastal cur­
rents. As a consequence, the coast of Somalia is an area of
upwelling in the summer (Longhurst, 1998) as this region is
influenced by a seasonal boundary current which disappears
during wintertime.
Subpolar margins (light blue) are found on all conti­
nents but Africa. They are located at relatively high latitudes
(above 40-50 degrees) in regions where EBCs and WBCs
fade out or drift away from the coasts. In the North Pacific,
the subpolar margins lie along the western coast of Canada
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
2034
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
Table 2. L ist o f the m odified CO SCA T segm ents w ith the depth o f the outer lim it o f their continental shelves and the residence tim e o f fresh
water. CO SCA Ts follow ed by a star (*) have been defined or m odified for the purpose o f the present w ork.
MARCATS
COSCAT
1-NEP
0809
0810
0811
0804
0805
0806
0807
0808
0801
0802
0803
1115
1116
2-CAL
3-TEP
4-HUM
5-SAM
6
-BRA
7-TWA
8
-CAR
1 1 1 2
10-FLO
11-LAB
12-HUD
13-CAN
14-NGR
15-SGR
16-NOR
17-NEA
Freshwater
Residence Time (yr)
350
350
500
150
29.6
87.2
1552.1
42.2
428.1
4340.1
33.7
12.5
34.6
89.3
4.9
33.6
5.7
43.5
239.8
1044.3
367.5
3502.1
142.8
18.5
130.2
9.8
200
200
200
*
350
150
350
80
150
150
350
1113
1114
1109
in o
lili*
1106
1107
1108
1103
1104
1105
0830
0831
200
1101
1102
9-MEX
Shelf
Lim it (m)
0832
0833
0834
0826
0827
0828
0821
0822
0824
0825
0817
0818
0819
0820
0814
0815
0816
0823
0501
0502
0505
0503
0504
0407
0402
0403
500
350
350
500
120
350
350
150
1.8
120
120
21.3
9.3
120
12.1
150
350
150
3.4
155.1
40.6
74.0
200
120
150
150
120
500
120
120
150
-
150
120
500
80
500
500
500
500
500
200
350
200
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
COSCAT
18-BAL
0404
0405
0406
0401
0419*
350
350
0001
200
0 002
150
150
150
19-IBE
20-MED
21-BLA
22-MOR
23-TEA
2 .8
200
1 1 .6
261.2
75.2
41.9
164.4
57.3
14.7
12.9
226.9
2 4-SWA
25-AGU
26-TWI
27-W IB
28-RED
29-PER
30-EIB
31-BEN
32-TEI
-
2808.0
1960.0
1367.9
1369.9
166.7
92.4
371.8
113.0
0003
0414*
0415
0416
0417
0418
1301*
0411
0412
0413
1103
0019
33-LEE
34-SAU
35-EAC
36-NW Z
-
200
350
200
200
150
-
0 02 0
350
350
150
150
150
0021
200
0014
0015
0016
0017
0018
0013
0009
0 01 0
8 .6
375.8
531.6
2055.4
24.6
2596.8
Shelf
Lim it (m)
MARCATS
150
200
350
200
200
750
150
120
0011
120
0 012
350
0007
0008
0005
0006
1341
0004
1344
1342
1338
1339
1340
1336
1337
1334
1335
1414
1413
1411
1412
1410
1406
1407
1408
1409
120
150
120
150
150
150
150
-
150
200
200
350
150
150
200
200
350
350
350
350
200
350
350
350
Freshwater
Residence Time (yr)
1 1 0 .1
40.1
9.1
172.4
62.1
234.4
3525.9
8.3
162.0
232.8
76.7
389.2
69.6
40.3
13.0
19.4
593.0
2 .8
24.5
11722.1
743.5
162.0
232.8
76.7
389.2
69.6
5613.6
10.9
15.8
4.8
421.0
3.1
1 1 .2
1409.9
97.4
3678.4
762.0
41071.0
135.6
48.8
64.3
86 .1
6 .8
13.4
29.7
18.6
620.8
848.5
261.1
2163.1
181.8
87.8
282.7
43.7
81.1
www.hydrol-earth-syst-sci.net/17/2029/2013/
G. G. Laruelle et al.: Global multi-scale segmentation of continental and coastal waters
2035
Table 2. C ontinued.
MARCATS
COSCAT
37-NAU
1330
1333
1401
1402
1403
1415
1416
1328
1329
1331
1332
1322
1323
1324
1325
1326
1320
1321
1317
1318
1319
38-SEA
39-CSK
40-JAP
41-OKH
Shelf
Lim it (m)
Freshwater
Residence Time (yr)
150
35.2
52.5
7.7
14.1
88.7
252.4
31.7
40.2
46.9
23.1
98.6
192.5
24.4
517.5
42.8
35.4
89.8
223.8
1360.0
84.7
569.5
200
200
150
500
350
150
200
200
150
350
500
150
-
350
350
500
750
500
500
and South Alaska (MARCATS 1, NEP) and on the eastern
face of Russia (MARCATS 42, NWP). The southern portion
of South America is also considered sub polar and extends
from the northernmost fjords of Chile on the Pacific side to
the Rio de la Plata on the Atlantic side (MARCATS 5, SAM).
A large fraction of the North Atlantic is bordered by sub­
polar shelves including the Labrador Sea (MARCATS 11,
LAB), southern Greenland (MARCATS 15, SCR) and north­
western Europe (MARCATS 17, NEA). The latter comprises
southern Iceland, as well as the Irish, Celtic and North seas.
On the antipodes, southern Australia (MARCATS 34, SAU)
and New Zealand (MARCATS 36,NWZ) complete the world
distribution of subpolar margins.
Polar margins (deep blue) are located at very high lat­
itudes of the Northern Hemisphere and include the Cana­
dian archipelagos (MARCATS 13, CAN), northern Green­
land (MARCATS 14, NCR), the Norwegian Basin (MAR­
CATS 16, NOR) and the Russian Arctic Ocean (MARCATS
43, SIB and 44, BKS). In the Southern Hemisphere, the
Antarctic continent is bordered by the polar MARCATS 45
(ANT).
In our classification, marginal seas (purple) include all
enclosed and semi-enclosed shelves. All of them are lo­
cated in the Northern Hemisphere, and they can be sub­
divided into two broad categories. The first category con­
sists of the shelves bordering large deep oceanic basins such
as the Gulf of Mexico (MARCATS 9, MEX), the Sea of
Japan (MARCATS 40, JAP) and the Sea of Okhotsk (MAR­
CATS 41, OKH). The Black Sea (MARCATS 21, BLA), the
Mediterranean Sea (MARCATS 20, MED) and the Red Sea
www.hydrol-earth-syst-sci.net/17/2029/2013/
MARCATS
COSCAT
4 2-NWP
0812
1314
1315
1316
1309
1310*
1311*
1312*
1313
0408
0409
1307
1308
1501*
1502*
1503*
1504*
1505*
43-SIB
44-BKS
45-ANT
Shelf
Lim it (m)
Freshwater
Residence Time (yr)
350
350
350
500
150
150
500
150
500
321.8
518.3
195.5
108.0
13.7
261.0
352.4
1563.2
1697.0
196.9
3477.7
97.6
61.0
200
200
500
500
1000
750
1000
1000
1000
-
(MARCATS 28, RED) also consist of narrow shelves sur­
rounding deeper waters, but, in addition, they are character­
ized by a very limited connection to the ocean. In spite of
being defined as a marginal sea, the influence of monsoon
wind patterns can be observed in the hydrodynamics of the
southern Red Sea (Al-Barakati et al., 2002). The other cat­
egory of marginal seas consists of inner continental bodies
of relatively shallow waters such as the Hudson Bay (MAR­
CATS 12, HUD), the Baltic Sea (MARCATS 18, BAL) and
the Persian Gulf (MARCATS 29, PER).
The remaining margins are located between both tropics
(red). They are aligned in a sort of equatorial belt around the
Earth and include the Pacific and Atlantic coasts of Central
America (MARCATS 3, TEP and MARCATS 7, TWA), the
Caribbean Sea (MARCATS 8, CAR), the Atlantic and Indian
coasts of central Africa (MARCATS 23, TEA, and 26, TWI)
as well as a large section of Oceania running from the north
of Australia to the south of China and comprising most of
Indonesia and the Philippines (MARCATS 37, NAU).
3.2
Global importance of the continental margins
Table 1 provides global values for sea surface areas and wa­
ter volumes between the different isobaths used in this study.
The global surface area of 26 x IO6 km2 between the coast­
line and the 200 m isobath (the commonly used outer limit
for the coastal ocean in global studies, Walsh, 1988; Borges
et al., 2005) is similar to that of Laruelle et al. (2010). Yet, the
distribution of this area among depth intervals indicates that
the portion shallower than 80 m contributes to 17 x IO6 km2.
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
2036
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
A significant fraction of the continental margins thus corre­
sponds to shallow coastal waters such as the wide North Sea
(COSCAT 404), and the Patagonian and Arctic continental
shelves. The latter two exhibit highly extended shallow sur­
face areas (< 200 m) followed by a gentle slope and a deep
shelf break.
Most coastal ocean surface area evaluations yield values
in the range 25-30 x IO6 km2 (Laruelle et al., 2010; Walsh,
1988; Cai et al., 2006; Chen and Borges, 2009), which corre­
sponds to 8 % of the world’s ocean. These values have been
largely used in the literature to constrain global budgets and
box models (Borges et al., 2005; Laruelle et al., 2009, 2010;
Mackenzie et al., 1993; Rabouille et al., 2001; Ver, 1998;
Wanninkhof et al., 2013), but the use of surface areas varying
by 20 % from one study to another has implications regarding
the accuracy of the budgets calculated. The common defini­
tion of a single proper limit for the outer edge of the continen­
tal shelf remains a matter of debate in the literature (Borges
et al., 2005; Laruelle et al., 2010; Liu et al., 2010), and the
choice of this limit depends not only on various sedimentological and morphological criteria, but also, to some degree,
on convenience of use. Convenience is the main reason why
the 200 m isobath has often been selected as it provides a con­
sistent limit which is easy to manipulate and allows for inter­
comparability between studies. However, the morphological
heterogeneity of the coastal zone cannot be accounted for by
such a simple boundary. Liu et al. (2010) proposed a defini­
tion based on the increase in slope of the continental shelf as
an alternative, which is also used here (see Sect. 2.1) and, al­
though our estimate of 30 x IO6 km2 falls within the range of
previously reported values, the method allows for a more rig­
orous regional analysis of the shelf area distribution around
the globe. The shelf break depths for each COSCAT are pro­
vided in Table 2. Furthermore, the surface areas and volumes
between the calculated isobaths for all COSCAT segments
are available as supplementary material as well as CIS files
providing the exact geographic extent of each unit. This al­
lows for comparisons between studies relying on different
definitions for the boundary between the open and the coastal
ocean. It also provides a clear boundary for oceanic studies
which either exclude the coastal zone (Takahashi et al., 2009)
or treat it differently from the open ocean (Wanninkhof et al.,
2013).
The integrated volume of all continental shelves, from the
shore to the shelf break, is 3860 x IO3 km3 (for a surface
area of 30 x IO6 km2). Most continental shelves break at wa­
ter depths between 150m and 350m (Fig. 3). The deeper
shelves are found in polar and sub polar regions, and their
integrated volume accounts for more than half of the world’s
total volume of the coastal ocean. This includes the shelves of
Antarctica, which are very deep and extend down to 1000 m.
Such particularity is a result of the downwarping caused by
the weight of the ice sheet on the continent, glacial ero­
sion and the lack of sedimentation from fluvial discharge
(Anderson, 1999). It also includes the very wide Arctic
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
40
35
30
T ro p ic a l
25
V la re in a
z 20
Jo a r
15
SubPo ar
10
V lo n s o o n a
5
0
_
7
in
T ro p ic a l
J 6
S 5
•£>
HUD+BAL+PER
v la rg m a
3 4
ro
aí 3
(jro
Jo la r
Sub Po ar
t3 2
i/l
1
0
V lo n s o o n a
SO
120
150
200
350
500
750
1000
S h e l f b r e a k d e p t h (m)
Fig. 3. R epartition o f the depth at w hich the sh e lf breaks for each
CO SCA T segm ent (top, a - num ber (N ) o f C O SCA T segm ents per
shelfbreak depth) and integrated surface area o f continental shelves
(bottom ). The colour code represents the type o f M A RCA TS.
shelves. Tropical shelves are generally shallower whereas
shelves in contact with EBCs and WBCs do not exhibit a
clear trend. Regions under monsoonal influence all have a
shelf limit between 150 m and 350 m. Internal marginal seas
such as the Hudson Bay, the Baltic Sea and the Persian Gulf
(HUD, BAL and PER) are relatively shallow and are en­
tirely comprised within the continental platform. Therefore,
they do not break and are not included in the accounting of
COSCATs in Fig. 3a. In Fig. 3b, HUD, BAL and PER were
assigned to the range corresponding to their maximum water
depth, excluding any highly localized deep features (< 5 %
of surface area). The bulk of this distribution consists of rel­
atively deep shelves. This is explained, in part, by the signifi­
cant contribution of the deep Arctic shelves which amount to
5 x IO6 km2 alone. It also indicates that many shallow shelves
are relatively narrow. This is particularly striking for EBCs,
which only represent a total surface area of 1.2 x IO6 km2
and, to a lesser extent, WBCs with a total surface area of
2.9 x IO6 km2.
3.3
Connecting MARCATS with the continents
Table 3 summarizes the surface areas of watersheds, estuaries
and continental shelves for every MARCATS. The surface
areas of watersheds and continental shelves are also com­
pared with published values for the North Sea, Baltic Sea,
Hudson Bay and Persian Gulf (Table 4). The consistency be­
tween our estimates and literature data is fairly good, and
www.hydrol-earth-syst-sci.net/17/2029/2013/
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
the discrepancy never exceeds 3 %. Table 4 also provides
comparison between reported values and our estimates for
the continental shelf volumes. Only 2 %, 5 % and 6 % de­
viation are obtained for BAL, HUD and PER, respectively.
The discrepancy reaches 15 % in the case of the North Sea
(COSCAT 403), but this is likely due to the use of a slightly
different geographic definition of the extent of the North Sea
in Thomas et al. (2005), which includes a very deep trench
located on the eastern side. The surface areas of estuarine
systems are based on a spatially explicit typology consist­
ing of four different types of active estuarine filters and three
types where estuarine filtering is absent (Dürr et al., 2011).
Type I consists of small deltas and miscellaneous secondary
streams or transitional systems which exhibit very limited fil­
tering capacities. Type II regroups all estuaries and embayments dominated by tidal forcing. This includes not only all
macro-tidal estuaries and bays but also most rias and many
meso-tidal systems like those found in South Atlantic Amer­
ica and Siberia. Type III represents lagoons and enclosed es­
tuaries, relatively protected from tidal influence (Schwartz,
2005). Type IV comprises fjords, fjaerds and other miscella­
neous high latitudes systems generally characterized by deep
waters and very long freshwater residence time. Large rivers
(Type V) often produce an estuarine plume that protrudes
past the conventional geographical limits of estuaries and,
sometimes, even of continental shelves (McKee et al., 2004).
To attribute a surface area to each estuarine type within each
MARCATS, the respective length of each estuarine class is
multiplied by an average ratio of estuarine surface per km
of coastline following the procedure of Dürr et al. (2011).
The distribution of estuarine types varies widely amongst
the different classes of MARCATS. The polar margins in
the Northern Hemisphere contribute 31 % to the estuarine
surface areas (IO6 km2). These estuaries are heavily domi­
nated by fjords (Fig. 4a). Antarctica does not have any estu­
ary according to this calculation because the few rivers are
essentially meltwater streams (Anderson, 1999; Jacobs et al.,
1992).
The world’s exorheic watershed surface totals 113 x
IO6 km2, which is 4 times larger than that of continental
shelves and more than 100 times that of estuaries (Fig. 4b).
Naturally, the ratio between these surfaces significantly
varies from one region to another as well as the estuarine dis­
tribution along the coast. The spatial distribution of estuarine
systems is indicated in Fig. 5a-f. Generally, EBCs and WBCs
are characterized by narrow shelves that are connected to
much larger watersheds (Fig. 4b). Moreover, it can be ob­
served that many EBCs and WBCs present relatively narrow
watersheds too, in particular in the Pacific (CAL and HUM,
Fig. 5a and b). The cumulative surface area of shelves under
influence of boundary currents is 4.4 x IO6 km2 only (14 %
of the world’s total). The regional contributions vary widely
from the very wide China Sea (CSK) on the one hand to the
very narrow coastal ribbon following South America in the
South Pacific on the other hand (HUM). In the Atlantic, the
www.hydrol-earth-syst-sci.net/17/2029/2013/
2037
0.35
I F jo r d s
0,30
I L agoons
0.Z5
■ T id a l S y s te m s
0 .2 0
■ S m a ll D e lta s
0.15
0.10
0.05
0.00
35
b
s h e lf
30
□ E stu a rie s
25
■ W a te rs h e d s
20
15
10
5
0
EBC
WBC
M ons.
Sub-P
P o l.
M arg.
Trop.
Fig. 4. Integrated surface areas for each M A R C A T S class o f the d if­
ferent estuarine types (a) and w atersheds, estuaries and continental
sh e lf (b ).
coasts of Morocco (MOR) and Portugal (IBE) are also very
narrow, while those of the eastern US (FLO), Brazil (BRA)
and Namibia (SWA) extend over several tens of kilometres.
Margins under monsoonal influence are essentially located
between the Equator and the Tropic of Cancer (23° N). A
large section of this coastline is dominated by arid regions,
on the western side (WAS, Fig. 5d). The cumulative estuarine
surface area in these regions is only 43 x IO3 km2, consisting
mostly of small deltas located on the Indian sub-continent
(EAS, Fig. 5d). The shelves are generally narrow while sev­
eral watersheds are very large, in particular those flowing into
the Bay of Bengal (BEN, Fig. 5e) like those of the GangesBrahmaputra, Godavari and Krishna rivers.
Subpolar margins present a wide diversity of profiles
with extended shallow shelves (North Sea, NEA, Patagonian
shelf, SAM) as well as fragmented archipelagos (Labrador
Sea). Their cumulative watershed area amounts to 9.5 x
IO6 km2, and the ratio of watershed to shelf surface varies
from 1 in New Zealand (NWZ) to 8 in the Labrador Sea
(LAB) with an average value of 2.4. Estuaries in sub-polar
regions essentially consist of tidal systems and fjords at the
highest latitudes (NWP, NEP, Fig. 5a).
Polar margins are very wide as well as deep and account
for over 50 % of the volume of the coastal ocean and 29 %
of its surface area (Fig. 4). Although these systems include
watersheds of several very large Russian rivers (Ob, Yeni­
sei, Lena, Amur, etc.), the average watershed to shelf ratio is
only 2, the lowest amongst the classes of margins. Most of
the fjords of the world are located in polar regions and, while
they represent 40% of the world’s estuarine surface area
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
2038
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
Table 3. List o f the M A RCA TS segm ents w ith their type, the surface area o f their various com ponents, the freshw ater discharge and the
volum e o f their continental shelves.
N um ber
S y s te m N a m e
Sym bol
C lass
1
N o rth -e a s te rn P acific
NEP
S u b p o la r
E s tu a rin e S u rfa c e
W a te rsh e d S u rfa c e
S h e lf S u rfa c e
(IO 3 k m 2)
(IO 3 k m 2)
(IO 3 k m 2)
33 .9
919
F re sh w a te r
D isc h arg e (k m 3 y r
S h e lf V olum e
3)
(k m 3)
461
785
58 932
2
C a lifo rn ia C u rren t
CAL
EBC
8.9
1781
214
428
16 668
3
T ro p ic a l E a ste rn P acific
TEP
T ro p ic a l
6.2
638
198
586
15 777
4
P e ru v ia n U p w e llin g C u rren t
HUM
EBC
4.2
725
143
120
19 769
5
S o u th A m e ric a
SAM
S u b p o la r
22 .0
1917
1230
289
141 652
6
B ra z ilia n C u rren t
BRA
W BC
26 .3
4624
521
1117
36 214
7
T ro p ic a l W e ste rn A tlan tic
TW A
T ro p ic a l
13.4
9242
517
8981
20 691
8
C a rib b e a n S e a
CAR
T ro p ic a l
26.2
1109
344
941
15 721
9
G u lf o f M e x ic o
M EX
M a rg in a l S ea
31 .9
5411
544
1085
22 432
10
F lo rid a U p w e llin g
FL O
W BC
34 .0
1130
858
531
50 522
11
S e a o f L a b rad o r
LA B
S u b p o la r
36.1
2351
395
1080
43178
12
H u d so n B a y
HUD
M a rg in a l S ea
39 .0
3601
1064
666
105 267
13
C a n a d ia n A rc h ip e la g o s
CAN
P o la r
1 63.7
3725
1177
382
157 543
14
N o rth e rn G re e n la n d
NGR
P o la r
24.1
373
614
82
139337
15
S o u th e rn G re e n la n d
SG R
P o la r
8.8
101
270
108
60 538
16
N o rw e g ia n B asin
NOR
P o la r
17.0
219
171
183
16915
17
N o rth -e a s te rn A tlan tic
NEA
M a rg in a l S ea
37 .6
1089
1112
498
101984
18
B a ltic S ea
BAL
M a rg in a l S ea
26 .3
1619
383
376
20165
19
Ib e ria n U p w e llin g
IB E
EBC
12.7
818
283
202
26 640
20
M e d ite rra n e a n S ea
M ED
M a rg in a l S ea
15.1
8168
580
674
42 224
21
B la c k S ea
BLA
M a rg in a l S ea
10.3
2411
172
360
8 246
22
M o ro c c a n U p w e llin g
MOR
EBC
5.6
3637
225
125
11 520
23
T ro p ic a l E a ste rn A tlan tic
TEA
T ro p ic a l
26 .6
8394
284
2762
14 786
24
S o u th -w e ste rn A fric a
SW A
EBC
1.7
1293
308
14
76 289
25
A g u lh a s C u rren t
AGU
W BC
28 .4
3038
254
657
19 607
26
T ro p ic a l W e ste rn In d ia n
TW I
T ro p ic a l
5.8
1022
72
328
2 039
27
W e ste rn A ra b ia n S ea
W AS
In d ia n M a rg in s
2.0
1723
102
26
5 234
28
R e d S ea
RED
M a rg in a l S ea
0
771
190
6
8101
29
P e rsia n G u lf
PER
M a rg in a l S ea
2.3
2466
233
61
8 296
30
E a ste rn A ra b ia n S ea
EAS
In d ia n M a rg in s
14.5
1847
342
293
18 823
31
B a y o f B en g a l
BEN
In d ia n M a rg in s
10.1
2934
230
1640
12 888
32
T ro p ic a l E a ste rn In d ia n
TEI
In d ia n M a rg in s
16.2
2060
809
1324
48 634
33
L e e u w in C u rren t
LEE
EBC
34
S o u th e rn A u s tra lia
SA U
S u b p o la r
0 .6
471
118
11
9 707
13.1
2249
452
66
38 307
35
E a ste rn A u s tra lia n C u rren t
EAC
W BC
7.9
290
139
67
12 149
36
N e w Z e a la n d
NW Z
S u b p o la r
7.3
265
283
340
36 833
37
N o rth e rn A u s tra lia
NAU
T ro p ic a l
40.5
3010
2463
25 4 8
145 236
38
S o u th E ast A s ia
SEA
T ro p ic a l
45 .6
3343
2318
2872
155 848
39
C h in a S e a a nd K u ro sh io
CSK
W BC
27 .8
4401
1299
1594
125 364
40
S e a o f Ja p a n
JA P
M a rg in a l S ea
6.7
418
277
252
40 760
41
S e a o f O k h o tsk
OKH
M a rg in a l S ea
19.7
2472
992
539
199 588
42
N o rth -w e ste rn P acific
NW P
S u b p o la r
22 .3
1783
1082
363
82 323
43
S ib e ria n S h e lv es
SIB
P o la r
37 .8
5041
1918
801
123 368
72.2
7940
1727
1585
44
B a re n ts a nd K a ra S eas
BKS
P o la r
45
A n ta rc tic S h e lv es
ANT
P o la r
(Fig. 6), their cumulative contribution remains fairly small
compared to the vety wide Arctic shelves. Locally, however,
they may contribute significantly to the surface area, as in the
case of Norway where some of the largest and deepest fjords
are located and where the shelf breaks only a few kilometres
offshore. Here, fjords account for a surface area as high as
10 % of that of the shelf.
Marginal seas, like sub polar margins, do not exhibit a
clear geomorphological pattern. An area of 28 x IO6 km2 of
watershed is connected to marginal seas, which amounts to
21 % of the surface of the continents. Shallow internal seas
(HUD, BAL, PER) have a very large surface area while most
other marginal seas consist of narrow shelves collecting very
large watersheds. This includes the Mississippi, the Nile and
the Danube rivers, which discharge into the Gulf of Mex­
ico (MEX), the Mediterranean Sea (MED) and the Black Sea
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
-
-
2952
-
181707
1 362 298
(BLA), respectively. The Sea of Okhotsk (OKH) is an ex­
ception as it is characterized by a wide shelf (IO6 km2) con­
nected to a relatively modest watershed of 2.4 x IO6 km2.
Tropical margins are generally very narrow along the
coasts of Africa (TEA and TWI) and America (TEP and
TWA) and connected to some of the widest watersheds in
the world (Amazon, Congo River, Niger). Their cumulative
shelf surface area is 1.3 x IO6 km2 for a cumulative water­
shed surface of 19.4 x IO6 km2. Tropical margins in Oceania
(TEI, NAU and SEA) display an opposite trend. The cumu­
lative surface areas for shelves and watershed in this region
are 4.9 x IO6 km2 and 7.4 x IO6 km2, respectively, yielding
a ratio of 1.5. This is an order of magnitude lower than that
of the other tropical margins, and the average ratio is thus
on the order of 4. Generally, the tropical MARCATS do not
exhibit very large estuaries because their coastline is either
www.hydrol-earth-syst-sci.net/17/2029/2013/
G. G. L am elle et al.: Global multi-scale segmentation of continental and coastal waters
2039
Lagoons
Fjords
Large
Karsts
¡H ] Arheic
Residence Time (yr)
< 70
J
I
I
OKH /
I
Types
I Endorheic
Types
I Endorheic
Fig. 5. M ap representing the CO SCA T segm ents (bold lines) and their corresponding continental shelf. T he colour o f the sh e lf indicates the
freshw ater residence tim e, and the grey area represents the geographic extent o f the upper slope (from the sh e lf break until the — 1 0 0 0 m
isobaths). W ithin each CO SCA T the lim its o f all w atersheds are indicated at a 0.5 degree resolution, and the colour code indicates the type
o f estuarine filter at the interface betw een the river and the shelf. T he lim its o f the M A RCA TS segm ents are indicated by the grey lines and,
for each one, a pie chart represents the total freshw ater discharge from rivers and its distribution am ongst the different estuarine types. The
size o f the pie is proportional to the total w ater discharge for a given M A RCA TS. T he panel provides the integrated surface area o f the sh e lf
w ith respect to the depth o f its outer lim it for each M A RCA TS segm ent.
dominated by small deltas or wide arheic regions (Dürr et al.,
2011) where rivers do not flow constantly and occasional rain
events create wadies rather than permanent estuaries. The lat­
ter is characteristic of regions such as, for example, the west­
ern coast of the Arabic Sea (WAS, Atroosh and Moustafa,
2 01 2 ).
The cumulative surface area of MARCATS shelves in­
tegrated to the 350 m isobaths is shown in small panels
on Fig. 5. The most common distribution displays a rapid
www.hydrol-earth-syst-sci.net/17/2029/2013/
increase in cumulative surface area up to isobaths 100—
150 m. At this depth, 80 % of the total shelf area is accounted
for, and the increase is then more progressive. However,
some MARCATS possess distinct features with a slope that
increases linearly with depth. They belong mainly to the po­
lar and sub-polar classes (NOR, LAB, NWZ) or to boundary
currents (FLO, HUM, TEA). The peculiar profile of MAR­
CATS 23 (TEA) is strongly influenced by the deep coastal
canyon created by the Congo River (Droz et al., 1996). Other
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
2040
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
Table 4. C om parison betw een published (bold) and calculated (this study, italic) w atershed surface area, w ater discharge, continental sh e lf
surface and volum es in the N orth Sea, B altic Sea, H udson B ay and Persian Gulf.
S ystem
N orth Sea
CO SCA T 403
B altic Sea
M A R C A T S 18
H udson Bay
M A R C A T S 12
P ersian G u lf
M A R C A T S 29
W atershed Surface
850a 870
1650a 1619
3700b 3601
n.a.
575.3C 592
374.6d 383
1040e 1064
239f 233
4 2 .3C 36.3
20.5d 20.1
1008 W 5
00
00
A rea (IO 3 k m 2)
S h e lf Surface A rea
(IO 3 k m 2)
od
<4—
S h e lf Volume
(IO 3 k m 3)
a O S P A R (2 0 1 0 );b D é ry a n d W o o d (2 0 0 5 ); c T h o m a s et al. (2 0 0 5 ); d W u lff et al. (2 0 0 1 ); e M a c d o n a ld a n d K u z y k
(2 0 1 1 ); f P o u s et al. (2 0 1 2 ); 8 S a u c ie r et al. (2 0 0 4 ).
significant exceptions to the typical hypsometric profile in­
clude the Baltic Sea (BAL), the Black Sea (BLA) and the
Persian Gulf (PER). All are shallow marginal seas which do
not exhibit a real shelf break.
3.4
Water flows
The annually averaged freshwater discharges into the coastal
ocean were calculated for each COSCAT and MARCATS
(Table 3). The data set used is GlobalNEWS2 (Mayorga
et al., 2010) from an original compilation of Fekete et
al. (2002). Within each MARCATS, the discharge flow­
ing through each estuarine type is also calculated (Fig. 5).
The well-known hotspots for freshwater discharge are eas­
ily identified: the Amazon region (TWA), the Congo region
(TEA), the Bengal Bay fuelled by the Ganges-Brahmaputra
River (BEN) and South East Asia/Oceania (TEI, NAU and
SEA). All these regions are located in the tropics, and their
segment is thus listed as tropical in Liu’s classification except
for BEN, which is under monsoon influence. Polar and sub­
polar regions do not provide as much fresh water, with the
exception of MARCATS 44 (BKS) which collects the dis­
charge of the Ob River. The Gulf of Mexico (MEX) is the
only marginal sea that receives more than 103 km3yr_1 of
fresh water, and, to a large extent, this is due to the Missis­
sippi River (Table 3). Together, the nine marginal systems
contribute 13 % to the world’s river discharge.
In most segments fed by at least one large river, the fresh­
water input is largely dominated by its discharge (CAN,
MEX, CAL, TWA, TEA, AGU, SIB, BEN, TEI). Similarly,
regions where tidal estuaries are present tend to be dom­
inated by these systems. This concerns, in particular, the
Atlantic coast of the USA (LAB and FLO), the Brazilian
Current (BRA), Western Europe (NEA and IBE), the Bar­
ents and Kara Seas (BKS), the Sea of Okhotsk (OKH), the
Eastern China Sea (CSK) and northern Australia (NAU).
Fjords are exclusively found at high latitudes (NEP, SAM,
CAN, HUD, LAB, NCR, SGR, NEA, NOR, BAL, BKS,
NWZ) and, although their integrated surface area is impor­
tant, their freshwater flow is quite modest (~ 7 % of the world
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
total). Lagoons are found on most continents and all lati­
tudes (Fig. 4) but, in terms of freshwater inputs, are only
marginal contributors except in the Caribbean (CAR) and
along the Gulf of Mexico (MEX) where they can be found
along stretches of the coastline and intercept ~ 40 % of the
riverine water discharge. Small deltas, on the other hand, can
locally be the main estuarine type through which significant
water flow is transported. They are mainly located in tropical
and sub-tropical areas and contribute very actively to highly
rheic regions like South East Asia and Oceania (SEA, TEI,
NAU).
For each COSCAT and MARCATS, the ratio between
the shelf volume and the corresponding riverine discharge
has been calculated (Fig. 5a-f). Globally, the compari­
son between the volume of continental shelf seas (3860 x
IO3 km3) and the annual freshwater input into the ocean
(39 x IO3 km3yr_1) yields an average value of ~ 100. How­
ever, this “freshwater residence time” is somewhat skewed
by the very large contribution of Antarctic shelves to the to­
tal (Fig. 6). If they are excluded from the calculation, the
freshwater residence time drops to ~ 5 5 y r, which remains
significantly higher than the average residence time of ~ 8lOyr calculated on the basis of the exchange with the open
ocean through upwelling fluxes (Brink et al., 1995; Rabouille
et al., 2001; Ver, 1998). Therefore, our results reveal that the
renewal of continental shelf waters by freshwater inputs is
5-7 times slower than through upwelling fluxes on average.
It should however be noted that the globally averaged boxmodel calculations for upwellings fluxes do not account for
the significant spatial and temporal variability in intensity of
upwelling processes, which can locally renew coastal waters
in just weeks (Gruber et al., 2011). Furthermore, neither the
box model nor our calculations resolve the lateral transport
by along-shore coastal currents. The ratio of freshwater dis­
charge to continental shelf volume varies significantly from
one region to the other, from 2yr (for COSCAT 1104 where
the Amazon flows) to several thousands of years in many arid
regions. Only 17 of the 149 COSCATs have freshwater res­
idence times shorter than lOyr, and the cumulative annual
freshwater input of these 17 COSCAT segments amounts to
www.hydrol-earth-syst-sci.net/17/2029/2013/
G. G. Laruelle et al.: Global multi-scale segmentation of continental and coastal waters
100%
Ü
2
80%
a
I
■
I Tr opical
_Q
o
M a r g in a l
o
P o la r
en) 60%
.1
•M
40%
Sub-Polar
20%
WBC
FC02 c o u n t
M onsoon
-Û
£
o
2041
u
b
I EBC
0%
W atershed
Estuaries
Shelf
S h e lf
Surface
Surface
Surface
V olum e
Fig. 6. C ontribution o f each M A R C A T S class to the global w ater­
shed surface area, estuarine surface area, continental sh e lf surface
area and continental sh e lf volum e.
16 x IO3 km3, which corresponds to 41 % of the global water
flux. These regions can be identified as coastal waters un­
der strong riverine influence and bear resemblance, in that
respect, to the RiOMARs, which are defined ascontinental
margins where biogeochemical processes are dominated by
riverine influences (McKee et al., 2004).
3.5
CO 2 outgassing from estuaries
Globally, estuaries have been identified as net emitters of
CO2 to the atmosphere (Abril and Borges, 2004; Borges,
2005; Borges et al., 2005; Cai, 2011; Chen and Borges,
2009; Laruelle et al., 2010). The first set of studies, based on
simple upscaling from a few local measurements, provided
first-order estimates of CO 2 evasion ranging from 0.4 to
0.6P gC yr-1 (Abril and Borges, 2004; Borges, 2005; Borges
et al, 2005; Chen and Borges, 2009). The more recent works
by Laruelle et al. (2010) and Cai (2011) relying on a more
detailed typology of estuarine systems have revised these es­
timates down to a value o f0 .2 5 ± 0 .2 5 P gC yr-1 (Regnier et
al., 2013). Yet, the best available global flux values remain
largely uncertain because of the limited availability of mea­
surements, their clustered spatial distribution and their biased
representativeness. For instance, out of the 63 available local
studies used by Laruelle et al. (2010), about 2/3 are located in
Europe or the US with only one value for fjord environments.
Here, we use the MARCATS segmentation in conjunction
with a denser network of 161 local flux estimates to estab­
lish regionalized estuarine CO2 fluxes (FCO 2 ), at the global
scale. A total of 93 local F CO2 estimates are used and com­
plemented by 68 additional F CO2 values derived from esti­
mates of the net ecosystem metabolism (NEM) reported by
Borges and Abril (2012). For the latter, the linear FCO 2 NEM regression established by Maher and Eyre (2012) is
used. The raw data are then clustered to derive a flux estimate
for each estuarine type considered here (small deltas, tidal
systems, lagoons, fjords). In MARCATS where at least two
local studies are available for a given estuarine type (n = 14,
www.hydrol-earth-syst-sci.net/17/2029/2013/
Fig. 7. (a) N um ber o f local a ir-w a ter C O 2 flux estim ates available
per M A R C A T S (black lines), CO SCA T lim its are indicated by grey
lines. (b) A ir-w a te r C O 2 em ission rates for estuaries from direct
estim ates (dots) and derived from n e t ecosystem m etabolism (tri­
angles). M ean rates per M A R C A TS are represented by the colour
scale.
Fig. 7a), the emission rate is directly extrapolated from the
measurements and the total surface area of the estuarine type
within the given MARCATS (Table 5). Their cumulative sur­
face area amounts to 184 x IO3 km2, which corresponds to
17 % of the world total for all types and 30 % if only small
deltas, tidal systems and lagoons are taken into account. For
the other MARCATS (n = 31), the global area-specific aver­
age flux calculated for each type (F CO2 , Table 5) is used and
multiplied by the type-specific estuarine surface-area for the
corresponding MARCATS.
Estuaries in Western Europe (IBE, NEA) are dominated by
heavily polluted tidal systems and are hotspots of CO2 emis­
sions with average rates up to 28m olC m - 2 yr-1 (Fig. 7b).
European marginal seas, however, are characterized by lower
values (BAL, MED). The region comprising the estuar­
ies of India, Bangladesh and Indonesia (EAS, BEN, TEI)
displays emission rates > 20m olC m - 2 yr-1 , but, because
of a smaller estuarine surface area (Table 3), the total
CO 2 evasion from Indian estuaries is substantially lower
than that of Western Europe (6.5 vs. 13.4TgCyr-1 ), as
also calculated by Sarma et al. (2012). The estuarine outgassing from the western, southern and eastern coasts of the
US (CAL, MEX, FLO), derived from local F CO2 , yields
smaller values between 11.7 and 14.1 m olC m - 2 yr- 1 . Un­
der warmer latitudes, BRA, TEA and TWI exhibit emis­
sion rates > 15 m olC m - 2 yr-1 while the eastern Aus­
tralian coasts (EAC) display the lowest rate of any region
(3.0 mol C m-2 yr-1 ). This average is largely influenced by
the estuaries studied by Maher and Eyre (2012), which are
characterized by an intake of atmospheric CO2 .
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
2042
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
Table 5. A ir-w a te r C O 2 fluxes for each estuarine type based on field studies. Positive values represent a source o f C O 2 to
the atm osphere. a indicates a C O 2 rate calculated from a N E M estim ate and b indicates sites used to derive regional averages.
G lobal em issions per unit surface area based on direct F C O 2 and derived from N E M lead to sim ilar results for sm all deltas
(14.6 m ol C m - 2 y r - 1 vs. 15.2 m ol C m - 2 y r- 1 , average 14.7 m ol C m - 2 y r- 1 ), lagoons (18.3 m ol C m - 2 y r - 1 vs. 13.4 m ol C m - 2 y r- 1 ,
average 15.1 m ol C m - 2 y r - 1 ) and fjords (5 m ol C m - 2 y r - 1 vs. 4.9 m ol C m - 2 y r- 1 , average 5.0 m ol C m - 2 y r- 1 ). In the case o f tidal sy s­
tem s, direct F C O 2 estim ates (25 m ol C m - 2 y r- 1 ) are ~ 2 -3 tim es larger than N E M -derived estim ates (8 . 8 m ol C m - 2 y r- 1 ) for an average
o f 15.1 m ol C m - 2 y r - 1. T his bias is likely due to the dom inance o f polluted E uropean estuaries in the F C O 2 data set w hile the N E M -derived
values are m ore hom ogeneously distributed (M aher and Eyre, 2012; R evilla et al., 2002).
fco2
Site
M A RCA TS
Long.
Lat.
(m ol C m -
-4 4
- 8 1 .1
-2 3
25.2
41.4
18.4
B orges et al. (2003)
K oné and B orges (2008)
2
y r- 1 )
R eference
Small deltas
Itacuraça C reek (BR)
S hark R iver (US)
6
9
D uplin R iver (U S)b
10
- 8 1 .3
31.5
21.4
W ang and Cai (2004)
N o rm a n ’s Pond (BS)b
Rio S an Pedro (ES)
10
19
- 7 6 .1
- 5 .7
23.8
36.6
5.0
39.4
B orges et al. (2003)
F errón et al. (2007)
K idogow eni C reek (KE)b
26
39.5
- 4 .4
23.7
B ouillon et al. (2007a)
M toni (TZ)b
26
39.3
- 6 .9
7.3
K ristensen et al. (2008)
Ras D ege C reek (TZ)b
M atolo/N dogw e/K alota/M to Tana (KE)
26
27
39.5
40.1
- 6 .9
- 2 .1
12.4
25.8
B ouillon et al. (2007c)
B ouillon et al. (2007b)
K ali (IN)b
30
74.8
14.2
1 .2
Sarm a et al. (2012)
M andovi (IN)b
30
73.8
15.4
6.6
Sarm a et al. (2012)
N etravathi (IN )b
30
74.9
12.9
25.8
Sarm a et al. (2012)
Sharavathi (IN )b
30
74.4
14.3
3.7
Sarm a et al. (2012)
Z uari (IN )b
30
73.8
15.4
2.3
Sarm a et al. (2012)
A m balayaar (IN)b
31
79.5
10
0.0
Sarm a et al. (2012)
B aitarani (IN )b
31
86.5
20.5
7.3
Sarm a et al. (2012)
C auvery (IN )b
31
79.8
11.4
0.8
Sarm a et al. (2012)
G aderu C reek (IN)b
31
82.3
16.8
20.4
B orges et al. (2003)
K rishna (IN)b
31
81
16
2.5
Sarm a et al. (2012)
M ooringanga C reek (IN)b
31
89
22
8.5
B orges et al. (2003)
N agavali (IN )b
31
84
18.2
0 .1
Sarm a et al. (2012)
P enna (IN)b
31
80
14.5
1.9
Sarm a et al. (2012)
R ushikulya (IN)b
31
85
19.5
0.0
Sarm a et al. (2012)
Saptam ukhi C reek (IN )b
31
89
22
20.7
B orges et al. (2003)
Vaigai (IN)b
31
79.8
10
0 .1
Sarm a et al. (2012)
V am sadhara (IN)b
31
84.1
18.3
0 .1
Sarm a et al. (2012)
V ellar (IN)b
31
79
10
6.2
Sarm a et al. (2012)
K hura R iver estuary (TEl)b
32
98.3
9.2
35.7
M iyajim a et al. (2009)
T rang R iver estuary (TEl)b
N agada C reek (ID)
32
37
99.4
145.8
7.2
- 5 .2
30.9
15.9
M iyajim a et al. (2009)
B orges et al. (2003)
K iên V áng creeks (V N )b
38
105.1
8.7
34.2
K oné and B orges (2008)
Tam G iang creeks (V N )b
38
105.2
8 .8
49.3
K oné and B orges (2008)
E lkhorn Slough, A zevedo (U S)b
2
-
1 2 1 .8
36.8
15.2a
C affrey (2004)
E lkhorn Slough, South M arsh (US)b
2
-
1 2 1 .8
36.8
1 1 2
. a
C affrey (2004)
S outh Slough, S tengstacken (U S)b
2
- 1 2 4 .3
43.3
14.5a
C affrey (2004)
S outh Slough, W inchester (U S)b
2
- 1 2 4 .3
43.3
1 0 6
. a
C affrey (2004)
T ijuana River, O neonta Slough (M X )b
2
-1 1 7
32.5
23.7a
C affrey (2004)
T ijuana River, Tidal L inkage (M X )b
2
-1 1 7
32.5
24.7a
T óm ales B ay (US)b
2
- 1 2 2 .9
38.1
6.3a
avg.
14.7
F C O 2 , sm all deltas
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
C affrey (2004)
S m ith and Elollibaugh (1997)
www.hydrol-earth-syst-sci.net/17/2029/2013/
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
2043
Table 5. C ontinued.
FC 0 2
Site
M ARCATS
Long.
Lat.
(mol C m - 2 y r- 1 )
Reference
Tidal systems
Piaui River estuary (BR)
6
- 3 7 .5
- 1 1 .5
13.0
Souza et al. (2009)
A ltam aha Sound (US)b
10
- 8 1 .3
31.3
32.4
Jiang et al. (2008)
Bellam y (US)b
10
- 7 0 .9
43.2
3.6
H unt et al. (2011)
Cocheco (US)b
D oboy Sound (US)b
10
10
- 7 0 .9
- 8 1 .3
43.2
31.4
3.1
13.9
H unt et al. (2011)
Jiang et al. (2008)
G reat Bay (US)b
10
- 7 0 .9
43.1
3.6
H unt et al. (2011)
L ittle Bay (US)b
10
- 7 0 .9
43.1
2.4
H unt et al. (2011)
O yster (US)b
10
- 7 0 .9
43.1
4.0
H unt et al. (2011)
Parker River estuary (US)b
10
- 7 0 .8
42.8
1.1
Sapelo Sound (US)b
10
- 8 1 .3
31.6
13.5
Satilla River (US)b
10
- 8 1 .5
31
42.5
York River (US)b
10
- 7 6 .4
37.2
6 .2
Raym ond et al. (2000)
H udson River (tidal) (US)b
10
-7 4
40.6
13.5
Raym ond et al. (1997)
Florida Bay (US)b
10
-8 0 .6 8
24.96
1.4
Elbe (DE)b
17
8 .8
53.9
53.0
Frankignoulle et al. (1998)
Em s (DE)b
17
6.9
53.4
67.3
Frankignoulle et al. (1998)
Rhine (NL)b
Scheldt (BE/N L)b
17
17
4.1
3.5
52
51.4
39.7
63.0
Frankignoulle et al. (1998)
Frankignoulle et al. (1998)
Tham es (UK)b
D ouro (PT)b
17
19
0.9
- 8 .7
51.5
41.1
73.6
76.0
Frankignoulle et al. (1998)
Frankignoulle et al. (1998)
Gironde (FR)b
19
-
G uadalquivir (ES)b
19
Loire (FR)b
19
-
Sado (PT)b
Raym ond and H opkinson (2003)
Jiang et al. (2008)
Cai and W ang (1998)
D ufore (2012) (MSc. Thesis)
1.1
45.6
30.8
Frankignoulle et al. (1998)
- 6
37.4
31.1
de La Paz et al. (2007)
2 .2
47.2
27.1
B ozec et al. (2012)
19
- 8 .9
38.5
31.3
Frankignoulle et al. (1998)
S aja—B esaya (ES)b
19
- 2 .7
43.4
52.2
Ortega et al. (2005)
Tam ar (UK)b
Betsiboka (MG)
Tana (KE)
19
26
27
- 4 .2
46.3
40.1
50.4
- 1 5 .7
- 2.1
74.8
3.3
47.9
Frankignoulle et al. (1998)
R alison et al. (2008)
B ouillon et al. (2007b)
B haratakulzab
30
75.9
10 .8
4.3
Sarm a et al. (2012)
M andovi-Zuari (IN)b
30
73.5
15.3
14.2
Sarm a et al. (2011)
N arm ada (IN)b
30
72.8
21.7
3.2
Sarm a et al. (2012)
Sabarm ati (IN)b
30
73
21
3.7
Sarm a et al. (2012)
Sabarm ati (IN)b
30
73
21
5.1
Sarm a et al. (2012)
Tapti (IN)b
30
72.8
21 .2
132.3
Sarm a et al. (2012)
H aldia E stuary (IN)b
31
88
22
4.5
Sarm a et al. (2012)
H ooghly (IN)b
31
88
22
5.1
M ukhopadhyay et al. (2002)
Subarnalekhab
Godavari (IN)b
31
31
88.3
82.3
21.5
16.7
0 .0
52.6
Sarm a et al. (2012)
Sarm a et al. (2011)
C am den Haven (Aus)b
H astings River (Aus)b
35
35
152.83
152.91
-3 1 .6 3
- 3 1 .4
- 5 .0
- 1 .0
M aher and Eyre (2012)
M aher and Eyre (2012)
W allis Lake (Aus)b
35
152.5
-3 2 .1 8
- 5 .0
M aher and Eyre (2012)
M ekong (VN)b
38
106.5
10
30.8
Borges (unpublished data)
Zhujiang (Pearl River) (CN)b
C hangjiang (Yangtze) (CN)
38
39
113.5
120.5
22.5
31.5
6.9
24.9
Guo et al. (2009)
Zhai et al. (2007)
Apex, NY B ight (US)b
10
- 7 3 .2
40.1
OO
Garside and M alone (1978)
Chesapeake Bay, Jug B ay (US)b
10
- 7 6 .0
37.0
30.9a
Caffrey (2004)
Chesapeake Bay, Patuxent Park (US)b
10
- 7 6 .0
37.0
14.0a
Caffrey (2004)
Chesapeake Bay, G oodw in Island (US)b
10
- 7 6 .0
37.0
2 0
. a
Caffrey (2004)
Chesapeake Bay, Taskinas Creek (US)b
Delaware Bay, Blackw ater Landing (US)b
10
- 7 6 .0
- 7 5 .2
37.0
39.1
2.4a
17.4a
Caffrey (2004)
Caffrey (2004)
www.hydrol-earth-syst-sci.net/17/2029/2013/
10
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
2044
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
Table 5. C ontinued.
fco2
Site
M A RCA TS
Long.
Lat.
D elaw are Bay, Scotton L anding (U S)b
10
- 7 5 .2
39.1
1 2
D ouro (PT)b
19
- 8 .7
41.1
15.1a
E m s—D ollar (G E)b
17
6.9
53.4
1 0
.1 a
Van Es (1977)
G reat Bay, G reat Bay B uoy (U S)b
10
- 7 0 .9
43.1
5.4a
C affrey (2004)
G reat Bay, Squam scott R iver (U S)b
10
- 7 0 .9
43.1
7.3a
C affrey (2004)
Eludson River, Tivoli S outh (U S)b
10
- 7 4 .0
40.7
.1 a
C affrey (2004)
M ullica River, B uoy 126 (U S)b
10
75.8
39.8
4.8a
C affrey (2004)
M ullica River, L ow er B ank (U S)b
10
75.8
39.8
14.5a
C affrey (2004)
N arragansett Bay, Potters Cove (U S)b
10
- 7 1 .6
41.6
1 2 6
. a
C affrey (2004)
N arragansett Bay, T —w h a rf (US)b
10
- 7 1 .6
41.6
1 1 2
. a
C affrey (2004)
N ew port R iver estuary (U S)b
10
- 7 6 .7
34.8
5.7a
N orth C arolina, M asonboro Inlet (U S)b
10
- 7 7 .2
34.3
15.0a
C affrey (2004)
N orth C arolina, Z ek e ’s Island (US)b
10
- 7 7 .8
34.2
18.4a
C affrey (2004)
N orth In let—W inyah B ay (U S)b
10
- 7 9 .3
33.3
8.7a
C affrey (2004)
O osterschelde (NL)b
17
3.5
51.4
5.3a
Schölten et al. (1990)
Ria de Vigo (ES)b
19
-
8 .8
42.3
3.5a
Prego (1993)
Ria F orm osa (PT)b
19
- 7 .9
37.0
2.5a
Santos et al. (2004)
2
- 1 2 2 .3
37.7
14.0a
Jassb y et al. (1993)
Jassb y et al. (1993)
San F rancisco Bay, N orth B ay (U S)b
San F rancisco Bay, S outh B ay (U S)b
(mol C m - 2 y r- 1 )
1 2
.1 a
R eference
C affrey (2004)
A zevedo et al. (2006)
K enney et al. (1988)
2
- 1 2 2 .3
37.7
5.1a
Scheldt E stuary (B E /N L)b
17
3.5
51.4
10.3a
Southam pton W ater (U K )b
19
- 1 .4
50.9
9.5a
U rdaibai (ES)b
19
- 2 .7
43.4
- 6 .3 a
W aquoit Bay, C entral B asin (U S)b
10
- 7 0 .6
41.6
15.0a
C affrey (2004)
W aquoit Bay, M etoxit Point (U S)b
10
- 7 0 .6
41.6
1 2
.1 a
C affrey (2004)
W ells Plead o f Tide (U S)b
10
- 7 0 .6
43.3
2 1 8
. a
C affrey (2004)
W ells Inlet (U S)b
10
- 7 0 .6
43.3
3.4a
C affrey (2004)
avg.
18.2
- 9 4 .8
29.4
6 .6
- 7 6 .4
- 8 .7
35.2
40.7
4.7
12.4
F C O 2 , tidal system s
G azeau et al. (2005a)
C ollins (1978)
R evilla et al. (2002)
Lagoons
B razos R iver (BR)b
9
Z eng et al. (2011)
N euse R iver (U S)b
Aveiro L agoon (PT)
10
s ’A lbufera des G rau (ES)
20
4.2
40
- 3 .0
C rossw ell et al. (2012)
B orges and Frankignoulle
(unpublished data)
O brador and Pretus (2012)
A by L agoon (CI)b
23
- 3 .3
4.4
- 3 .9
K oné et al. (2009)
Ebrié L agoon (CI)b
23
- 4 .3
4.5
31.1
K oné et al. (2009)
Potou L agoon (CI)b
23
- 3 .8
4.6
40.9
K oné et al. (2009)
Tagba L agoon (CI)b
23
-5
4.4
18.4
K oné et al. (2009)
Tendo L agoon (CI)b
23
- 3 .2
4.3
5.1
K oné et al. (2009)
C halakudi (IN)b
30
76.3
4.7
Sarm a et al. (2012)
C ochin (IN)b
30
76
9.5
55.1
G upta et al. (2009)
C hilka (IN)b
31
85.5
19.1
31.2
M uduli et al. (2012)
P onnayaar (IN)b
31
79.8
1 1 .8
35.2
Sarm a et al. (2012)
ACE, B ig Bay C reek (U S)b
10
- 8 0 .3
32.5
30.9a
C affrey (2004)
ACE, St. Pierre (U S)b
10
- 8 0 .4
32.5
17.4a
C affrey (2004)
C affrey (2004)
19
1 0 .2
A palachicola, B ottom (U S)b
9
- 8 5 .0
29.7
16.4a
A palachicola, S urface (US)b
B ojorquez L agoon (MX)
9
- 8 5 .0
-8 7
29.7
.1 a
- 1 7 .6 a
C ochin (IN)b
8
2 1 .0
1 2
30
76.0
9.5
6.3a
Copano B ay (US)b
9
- 9 7 .1
28.1
13.5a
Estero Pargo (M X )b
9
- 9 1 .6
18.6
6.5a
Four league Bay (U S)b
9
- 9 1 .2
29.3
8 8
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
. a
C affrey (2004)
R eyes and M erino (1991)
G upta et al. (2009)
R ussell and M ontagna (2007)
D ay Jr. et al. (1988)
R andall and D ay Jr. (1987)
www.hydrol-earth-syst-sci.net/17/2029/2013/
G. G. Laruelle et al.: Global multi-scale segmentation of continental and coastal waters
2045
Table 5. C ontinued.
fco2
Site
M A RCA TS
Long.
Lat.
(mol C m - 2 y r- 1 )
L aguna M adre (U S)b
9
- 9 7 .4
26.5
5.7a
L avaca B ay (US)b
M itla L agoon (MX)
9
3
- 9 6 .6
- 9 6 .4
28.7
16.9
N ueces B ay (US)b
9
- 9 7 .4
27.3
O chlockonee B ay (U S)b
9
- 8 4 .4
30.0
R edfish B ay (US)b
9
- 9 7 .1
27.9
2 0
R ookery Bay, B lackw ater R iver (US)b
9
- 8 1 .4
26.0
41.1a
C affrey (2004)
R ookery Bay, U pper H enderson (US)b
9
- 8 1 .4
26.0
33.4a
C affrey (2004)
San A ntonio Bay (U S)b
9
- 9 6 .7
28.3
9.8a
O dum and H oskin (1958),
O dum and W ilson (1962),
Z iegler and B enner (1998)
. a
13.1a
R ussell and M ontagna (2007)
M ee (1977)
.1 a
R ussell and M ontagna (2007)
1 1 2
-
R eference
0
4.5a
K aul and Froelich (1984)
.2 a
O dum and H oskin (1958)
R ussell and M ontagna (2007)
Sapelo Flum e D ock (US)b
10
- 8 1 .2
31.5
22.3a
C affrey (2004)
Sapelo M arsh L anding (U S)b
Saquarem a L agoon (BR)
10
- 8 1 .2
- 4 2 .5
31.5
- 2 2 .9
13.6a
3.9a
C affrey (2004)
C arm ouze et al. (1991)
- 9 1 .6
12.3
18.6
45.4
4.4a
51.0a
D ay Jr. et al. (1988)
C iavatta et al. (2008)
Term inos L agoon (M X )b
Venice L agoon (IT)
6
9
2 0
W eeks Bay, F ish R iver (US)b
9
- 8 7 .8
30.4
2.9a
C affrey (2004)
W eeks Bay, W eeks B ay (US)b
9
- 8 7 .8
30.4
4.8a
C affrey (2004)
avg.
15.1
3.1
- 7 .9 5
F C O 2 , lagoons
Fjords
B othnian B ay (FI)b
G odthâbsfjord (GL)
18
15
- 5 1 .7
63
64
L im inganlahti B ay (FI)b
18
25.4
64.9
7.5
R anders Fjord (D K )b
N ordasvannet Fjord (NO)
Padilla Bay, Bay View (US)
R anders Fjord (DK)
18
17
10.3
5.3
- 1 2 2 .5
10.3
56.6
60.3
48.5
56.6
17.5
3.8a
5.8a
4.9a
avg.
5.0
2
18
21
FCO 2 , fjords
In MARCATS for which the number of available local
F CO2 per estuarine type is less than two, the average emis­
sion rate solely reflects the relative distribution in estuarine
types. The regions where fjords dominate, such as in the
northern parts of America and Europe (LAB, HUD, CAN,
NCR, SCR, Fig. 7b), are those where emission rates per unit
surface area are the lowest (< 10 mol C m-2 yr-1 ). North­
western Russia (BKS) and North Pacific (NEP, WEP) estuar­
ies are characterized by a mix of fjords and tidal systems, and
their emission rates exceed 10 mol C m-2 yr-1 . In the rest of
the world, the average emission rates are usually comprised
between 15 and 18 mol C m-2 yr- 1 .
Global average F CO 2 per unit surface area for small
deltas, tidal systems, lagoons and fjords is 14.7, 18.2, 15.1
and 5.0 mol C m- 2 yr- 1 , respectively. The CO2 emissions in
the first three estuarine types are not significantly different
from each other. However, they may vary markedly at the
regional scale of MARCATS, for instance, by a factor of 6
in BEN where small deltas exhibit average emission rates of
5.1 mol C m- 2 yr-1 compared to 33.2 mol C m- 2 yr-1 for la­
goons. Other MARCATS where this regional difference is
www.hydrol-earth-syst-sci.net/17/2029/2013/
A lgesten et al. (2004)
R ysgaard et al. (2012)
S ilvennoinen et al. (2008)
G azeau et al. (2005a)
W assm ann et al. (1986)
C affrey (2004)
G azeau et al. (2005b)
significant include IBE and NEA, where F CO 2 rates per sur­
face area in tidal systems are two times higher than those
of other systems. In SEA, on the other hand, small delta
outgassing rate is as high as 41.8 mol C m- 2 yr-1 compared
to 18.9 molC m- 2 yr-1 for tidal systems. These differences
support a regionalized analysis of estuarine CO 2 emissions.
Our calculations yield a global CO 2 evasion of
0.15PgC yr-1 for all estuaries. In order of decreasing im­
portance, tidal systems, lagoons, fjords and small deltas
contribute 0.063 P gC yr- 1 , 0.046 P gC yr- 1 , 0.025 P g C y r-1
and 0.019 Pg C yr- 1 , respectively. The global evasion es­
timate corresponds to an averaged emission rate per unit
surface area of 13m olC m - 2 yr-1 , which is higher than
the mean rate of 6.9 mol C m-2 yr-1 proposed by Maher
and Eyre (2012) but lower than previous estimates based
on direct FC O 2 measurements (e.g. 21 ± 18 mol C m-2 yr-1
for Laruelle et al., 2010), although still falling within the
range of uncertainty. The smaller CO 2 evasion from fjords
calculated here (5.1 molC m- 2 yr- 1 , averaged over 7 val­
ues) largely explains most of the difference between our
estimate and the one reported from a single measurement
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
2046
G. G. Laruelle et al.: Global multi-scale segmentation o f continental and coastal waters
(17.5m olCm - 2 yr-1 ) in Laruelle et al. (2010). Our anal­
ysis reveals that the spatial coverage of field data remains
very coarse for accurate CO 2 flux estimations at the global
scale, but the spatial resolution of the MARCATS units is
well adapted to this scarcity and allows a first regionalized
analysis.
4
Conclusions and outlook
In this study, a three-level segmentation of the land-ocean
continuum extending from the watersheds to the shelf break
has been proposed. The spatial resolution of our level I seg­
mentation (0.5 degrees) is similar to those of most widely
used global hydrological and watershed GIS models. It cor­
responds to the finest resolution currently available for such
models. At this resolution, the routing amongst the vast ma­
jority of river networks is properly represented, and terres­
trial GIS models are able to produce reliable riverine dis­
charge estimates for large- and medium-sized rivers (water­
sheds > ten terrestrial cells, Beusen et al., 2005; Vörösmarty
et al., 2000b). In addition, important terrestrial and coastal
global databases cluster information at the same resolution
of 0.5-1 degree (e.g. World Ocean Atlas, Da Silva, 1994,
Hexacoral), making combination and meta-analysis between
data sets relatively easy. Recent coastal analyses (LOICZ,
Buddemeier et al., 2008; Crossland et al., 2005) and typolo­
gies (Dürr et al., 2011) as well as CIS models such as the
GlobalNEWS initiative (Mayorga et al., 2010; Seitzinger et
al., 1995) have also been developed at 0.5-1°. However, with
the exception of a few areas around the world (e.g. COSCAT
827 along the east coast of the US), the network of biogeochemically relevant observations of the aquatic continuum is
not dense enough at this resolution and calls for an analysis
at a coarser resolution (Regnier et al., 2013).
Levels II and III are used to construct large regional en­
tities which retain the most important climatic, morpholog­
ical and hydrological characteristics of continental waters
and the coastal ocean. The resulting number of segments
(149 COSCATs and 45 MARCATS) can easily be manip­
ulated and compared to existing segmentations such as the
large marine ecosystems (Sherman, 1991) or that of Seiter
et al. (2005). The segments provide globally consistent es­
timates of hypsometric profiles, surface areas and volumes
that can be used in combination with databases to establish
regional and global biogeochemical budgets. In addition, the
inter-compatibility between the three levels allows combin­
ing databases compiled at different spatial scales. Here, the
segmentation is used to establish regionalized estuarine CO 2
flux through the air-water interface. As data are progres­
sively building up, the procedure could easily be extended to
inland waters and the coastal ocean. The spatially resolved
representation of the hydrological cycle from the river net­
work to the coastal ocean allows also for a quantitative treat­
ment of the water flow routing through the different estuarine
Hydrol. Earth Syst. Sei., 17, 2029-2051, 2013
types. Both freshwater flow and CO 2 budgets are performed
at the scale of the MARCATS. In the future, our calcula­
tion could also address lateral fluxes of terrestrial carbon,
nutrients and further elements relevant in Earth system sci­
ence. The multi-scale segmentation of the aquatic continuum
from land to ocean thus provides appropriate support for the
optimal use of global biogeochemical databases (Cai, 2011;
Chen et al., 2012; Crossland et al., 2005; Gordon et al., 1996;
Laruelle et al., 2010; Nixon et al., 1996; Regnier et al., 2013)
and will allow the construction of increasingly robust region­
alized budgets of relevance to environmental and climate re­
search.
Supplementary material related to this article is
available online at: http://www.hydrol-earth-syst-sci.net/
17/2029/2013/hess- 17-2029-2013-supplement.zip.
Acknowledgements. The research leading to these results has
received funding from the E uropean U n io n ’s Seventh Fram ew ork
Program (FP7/2007 2013) under grant agreem ent no. 283080,
project G E O C A R B O N , by K ing A bdullah U niversity o f Science
and T echnology (KAUST) C enter-in-D evelopm ent A w ard to
U trecht U niversity: project No. K U K -C 1-017-12; by the govern­
m ent o f the B russels-C apital R egion (Brains B ack to B russels
aw ard to PR), by the G erm an Science Foundation D F G (DFGproject H A 4472/6-1) and the C luster o f E xcellence “C liS A P ”
(DFG, E X C 177), U niversität H am burg. H. H. D ürr received
funding from N S E R C (C anada E xcellence R esearch C hair in
E cohydrology - Philippe van C appellen). N. G oossens is funded
by a FR IA (FRS-FN RS) grant.
E dited by: G. D i B aldassarre
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