Carbon Sequestration in a LargeHydroelectric Reservoir: An

Integrative Seismic Approach

Raquel Mendonca,1,2* Sarian Kosten,2,3,4 Sebastian Sobek,5

Jonathan J. Cole,6 Alex C. Bastos,7 Ana Luiza Albuquerque,8

Simone J. Cardoso,1 and Fabio Roland1

1Laboratory of Aquatic Ecology, Federal University of Juiz de Fora, Rua Jose Lourenco Kelmer, s/n, Campus Universitario, Juiz deFora, MG 36036-900, Brazil; 2Department of Aquatic Ecology and Water Quality Management, Wageningen University, Wageningen,The Netherlands; 3Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin/Neuglobsow, Germany; 4Department ofAquatic Ecology and Environmental Biology, Institute for Water and Wetland Research, Radboud University Nijmegen, Nijmegen, TheNetherlands; 5Department of Ecology and Genetics, Limnology, Uppsala University, Uppsala, Sweden; 6Cary Institute of EcosystemStudies, Millbrook, New York, USA; 7Department of Oceanography and Ecology, Universidade Federal do Espırito Santo, Vitoria, ES,

Brazil; 8Departamento de Geoquımica, Universidade Federal Fluminense, Niteroi, RJ, Brazil

ABSTRACT

Artificial reservoirs likely accumulate more carbonthan natural lakes due to their unusually highsedimentation rates. Nevertheless, the actual mag-nitude of carbon accumulating in reservoirs ispoorly known due to a lack of whole-systemstudies of carbon burial. We determined the or-ganic carbon (OC) burial rate and the total OCstock in the sediments of a tropical hydroelectricreservoir by combining a seismic survey with sed-iment core sampling. Our data suggest that nosediment accumulation occurs along the margins of

the reservoir and that irregular bottom morphologyleads to irregular sediment deposition. Such het-erogeneous sedimentation resulted in high spatialvariation in OC burial—from 0 to 209 g C m-2 y-1.Based on a regression between sediment accumu-lation and OC burial rates (R2 = 0.94), and on themean reservoir sediment accumulation rate(0.51 cm y-1, from the seismic survey), the whole-reservoir OC burial rate was estimated at42.2 g C m-2 y-1. This rate was equivalent to 70%of the reported carbon emissions from the reservoirsurface to the atmosphere and corresponded to atotal sediment OC accumulation of 0.62 Tg C sincethe reservoir was created. The approach we proposehere allows an inexpensive and integrative assess-ment of OC burial in reservoirs by taking into ac-count the high degree of spatial variability andbased on a single assessment. Because burial can beassessed shortly after the survey, the approachcombining a seismic survey and coring could, ifapplied on a larger scale, contribute to a morecomplete estimate of carbon stocks in freshwatersystems in a relatively short period of time.

Key words: hydroelectric reservoir; carbon cycle;organic carbon burial; seismic survey; sedimenta-tion; tropical ecosystem.

Received 24 May 2013; accepted 15 October 2013

Electronic supplementary material: The online version of this article

(doi:10.1007/s10021-013-9735-3) contains supplementary material,

which is available to authorized users.

Author Contributions: RM, FR, SK, ACB, and ALA designed the study;

RM, SK, SJC, and ACB performed the field work; RM, SK, SS, and JJC

wrote the manuscript; all authors participated in the data analysis and

reviewed the paper.

*Corresponding author; e-mail: fm.raquel@yahoo.com.br

EcosystemsDOI: 10.1007/s10021-013-9735-3

! 2013 Springer Science+Business Media New York

INTRODUCTION

Organic carbon (OC) burial in the sediments offreshwater ecosystems represents an important sinkin the global carbon cycle (Cole and others 2007;Tranvik and others 2009). Although burial in riversand streams may be considered negligible due towater column instability (Allan and Castillo 2007),lakes and reservoirs accumulate more carbon perunit of area than the ocean or the terrestrial envi-ronment (Schlesinger 1990; Stallard 1998; Coleand others 2007). Furthermore, it has been esti-mated that artificial reservoirs accumulate three tofour times more carbon than natural lakes due tothe usually high sedimentation rates (Dean andGorham 1998). The efficient sediment trapping dueto damming is caused by the increase in waterresidence time and reduced hydrodynamicsenhancing the sedimentation of suspended mattercarried in by the river. Globally, dams are estimatedto intercept about 30% of the sediment originallytransported to the ocean (Vorosmarty and others2003).

Roughly 3.4 9 105 km2 of the globe is coveredby hydroelectric reservoirs (ICOLD 2003), an areaas large as Germany or the Caspian Sea, and morethan three times larger than Lake Superior. Thisarea is still increasing as more reservoirs are beingbuilt due to the increasing demand for freshwaterand hydroelectricity, implying that the role of res-ervoirs as global carbon sinks will increase inimportance as well. Whereas the carbon emissionsof reservoirs has been widely discussed (St. Louisand others 2000; Barros and others 2011; Fearnsideand Pueyo 2012), the carbon burial in their sedi-ments remains poorly known.

Reported rates of carbon burial in artificial res-ervoirs vary by three orders of magnitude. For in-stance, although Lake Kariba, a large oligotrophichydroelectric reservoir located on the boarder ofZambia and Zimbabwe, accumulates 23 g C m-2

y-1 (Kunz and others 2011), small eutrophicagricultural reservoirs from the USA accumulate upto 17,000 g C m-2 y-1 (Downing and others2008). The potential of a freshwater system to actas a carbon sink depends on the OC depositionrates, the OC preservation efficiency, and the life-span of a system. As a consequence of higher OCdeposition rates, OC burial tends to be higher inmore productive (for example, Downing and others2008) and in smaller systems (for example, Ka-stowski and others 2011). OC preservation effi-ciency, on the other hand, strongly depends onsediment source (Gudasz and others 2012), oxy-gen exposure time (Sobek and others 2009), and

temperature (Gudasz and others 2010; Cardoso andothers 2014).

Despite the significant advances toward under-standing the factors that control OC burial infreshwater sediments, the magnitude of the carbonsink in artificial reservoirs is still unclear (Battinand others 2009; Tranvik and others 2009). Al-though there are numerous studies in natural lakes(for example, Einsele and others 2001; Kastowskiand others 2011) the number of assessments of OCburial rates in artificial reservoirs is low (Mulhol-land and Elwood 1982; Stallard 1998; Dean andGorham 1998; Downing and others 2008; Kunzand others 2011; Sobek and others 2012). Most ofthese OC burial estimates combine data on sedi-ment deposition rates with OC content and sedi-ment density measurements. The acquisition ofaccurate data on sediment deposition rates, whichare usually derived from radioisotope chronology(Kunz and others 2011) or from bathymetric sur-veys repeated over time (Downing and others2008; Sobek and others 2012), remains a challenge.Radioisotope dating of reservoir sediments involvesa series of complications, such as spatial heteroge-neity, young sediment deposits, sediment mixingand relocation, and is, thus, often problematic oreven impossible (Olsson 1991, 2009). Accuratehistoric bathymetric data are usually not available.

The objective of this study was to determine theOC burial rate and the total OC stock accumulatedin the sediments of a tropical reservoir by com-bining sediment sample analyses and a seismicsurvey. Seismic surveys entail the acoustic profilingof sediments and permit the determination of thecumulative depth of deposited sediment since riverimpoundment (Dunbar and others 1999). Thisnovel combined approach represents an importantadvance in assessing carbon stocks in reservoirs, asit takes into account the high heterogeneity insediment and carbon accumulation in reservoirswhilst it is relatively fast because of the one-time-only spatially explicit measurements.

MATERIALS AND METHODS

Reservoir Description

This study was conducted in Mascarenhas deMoraes (MSM), a large (272 km2) and deep(maximum depth 60 m) hydroelectric reservoirlocated in southeastern Brazil (Figure 1), in theCerrado (savannah-type) biome. The reservoir wasformed by damming the Rio Grande in 1957. Thereservoir watershed is currently dominated byagriculture (mainly coffee, corn, and soybean),

R. Mendonca and others

with some remnant of original Cerrado forests.Water residence time in the MSM reservoir is rel-atively short (approximately 51 days, Rangel andothers 2012). Total phosphorus concentrationsrange from 15 to 168 lg P l-1 and chlorophyllconcentrations are low (from 2.6 to 3.9 lg l-1;Rangel and others 2012). Water transparency ishigh (Secchi disk depth of 4–8 m near the dam;Rangel and others 2012) and the bottom water isoxygenated year-round, even though the watercolumn is often stratified near the dam (Huszarpersonal communication).

Sampling

We combined the geophysical technique of seismicsurvey with sediment coring down to the pre-impoundment stratum (further referred to as a‘‘combined approach’’) to acquire integrativemeasurements of OC burial. Field work was

conducted in March 2011. Patterns of sedimentaccumulation were determined with a portablehigh resolution sub-bottom seismic profiler equip-ped with a 10 kHz acoustic source/receiver (Strat-aBox, SyQuest). The sound waves penetrate intothe soft and fine post-flooding sediment but notinto the more compact pre-flooding reservoir bot-tom, or sub-bottom (sandy river sediment, soil orbedrock) which makes it possible to assess thethickness of the post-flooding sediment (see Od-hiambo and Boss 2004; Figure 2). Similar seismicsurveys, albeit with lower frequencies (<1 kHz),are performed in lakes (Mullins and others 1991;Adams and others 2001; Hilbe and others 2011;Heirman and others 2011; Lyons and others 2011).Although lower frequencies penetrate deeper intothe sediment, their use results in a lower resolutionof the sediment profile and most likely does notpermit the identification of the upper and lowerlimits of post-flooding sediment layers in reservoirs.

Figure 1. Location of the MSM reservoir in Brazil. Solid lines indicate the seismic survey transects. Numbers and dotted linesindicate the coring sites. Underlined numbers correspond to sites by the margins.

Carbon Sequestration in a Large Hydroelectric Reservoir

More information regarding the application ofseismic surveys on artificial reservoirs can be foundin the literature (for example, Dunbar and others1999; Bennett and others 2005; Odhiambo andBoss 2004). Survey profiles were collected along 16transects perpendicular on the main tributary–damaxis, roughly 5 km apart and including three of thereservoir arms (more protected bays, Figure 1).Positioning data (acquired with a GPS) and real-time seismic signals were recorded on a portablecomputer for further analysis.

Sediment cores were sampled from 16 sitescoinciding with some of the seismic transects. Insome transects sediment cores were sampled fromlittoral and also pelagic sites (Figure 1; Table S1 inSupplementary Material). One sediment core wasretrieved from each site using a gravity corerequipped with a hammer device (6 cm internaldiameter, UWITEC, Mondsee, Austria). The corewas hammered into the sediment as deep as pos-sible resulting in cores containing the entire sedi-ment layer at the sampling site and preferentiallypre-flooding sediment/soil as well. After retrievalthe cores were sealed with plastic caps and trans-ported to the field station for slicing. Sedimentcores (including pre-flooded material) were sub-sampled in 2 cm thick slices which were stored inair tight plastic containers at -5"C until further labanalysis.

Seismic Profile Analysis

Seismic data were processed and interpreted usingthe software SonarWiz (version 4, ChesapeakeTechnology, Inc., California, USA). Sedimentthickness was computed assuming an acoustic

wave propagation of 1,500 m s-1 typical for muddysediments. Profiles of sediment thickness were thenacquired by digitizing the present bottom of thereservoir and the pre-flooding surface (resolutionof 5 cm). The acoustically determined sedimentthickness was validated by comparison with coringresults. Subsequently, the sediment thicknessdetermined along the seismic transects were inter-polated using the ‘‘inverse distance to a power’’algorithm (Surfer 9.0, Golden Software, Inc., Col-orado, USA) resulting in a grid of 130 rows and 192columns. Sediment thickness at the reservoir con-tours were set to zero, because sediment does notaccumulate at the margins in the reservoir (see‘‘Results’’ section). Based on the interpolated sed-iment thickness map, we calculated the total vol-ume of sediment (m3) accumulated in the reservoirfrom the date of its flooding until the present.

Sediment Core Analysis

The transition between pre-flooded substrate andreservoir sediment was visually identified in thefield. Physical and chemical analysis of sedimentprofiles corroborated the visual observations (seeSupplementary Methods). Dry sediment mass ofeach slice was measured gravimetrically. Organiccarbon (OC) content, nitrogen content and carbonisotopic composition (d13C) were determined usinga CN analyzer (ANCA-GSL, PDZ Europa, Ltd.,Sandbach, UK) coupled to a mass spectrometer(Sercon Ltd., Cheshire, UK). These analyses wereperformed for each core in the two top slices, in thetwo bottom post-flooding sediment slices, in thetwo top pre-flooding slices, and in one slice every10 cm along the entire core. OC content in thenon-analyzed slices was estimated by assuminglinear variation. We assumed particulate inorganiccarbon deposition to be negligible because waterpH in the MSM reservoir varies between 6.6 and7.8 (Rangel and others 2012) and sediment samplesdid not react when exposed to acid atmosphere(HCl).

Calculations

OC mass (g C) in each sediment slice was measuredas the product of OC content (g g-1) and dry sed-iment mass (g). Total OC mass (g C) in each corewas measured by the sum of carbon mass in allpost-flooding sediment slices. Areal OC burial rates(g C m-2 y-1) for each core were calculated fromtotal OC mass (g C), core surface area (2.8 9 10-3

m2) and the total reservoir age (54 years in 2011).Sediment accumulation rate (SAR cm y-1; ratiobetween post-flooding sediment thickness and

Figure 2. Section of a seismic profile. The sedimentthickness at a certain geographic position can be derivedfrom the distance between the surface of pre-floodingsubstrate and the surface of the sediment.

R. Mendonca and others

reservoir age) was positively correlated to areal OCburial rate in the coring sites (see ‘‘Results’’ sec-tion). Using the regression model between SAR andOC burial (see ‘‘Results’’ section), we estimated thewhole-reservoir OC burial rate (g C m-2 y-1)based on the reservoir-integrated SAR (the ratiobetween the total reservoir sediment volume andtotal reservoir area and age). Finally, the total OCstock (g C) in the reservoir sediment was calculatedas the product of the whole-reservoir OC burialrate, total reservoir area and reservoir age.

RESULTS

Seismic Survey

The sediment profiling analysis revealed a hetero-geneous pattern of sediment deposition in the MSMreservoir. Sediment thicknesses varied from 0 to105 cm, equivalent to mean sediment depositionrates of 0–1.9 cm y-1 since the year of impound-ment. Sediment deposition varied not only among

the seismic transects, but also within transects, as aneffect of sub-bottom topography. There was no sed-iment accumulation at the margins, along the entirereservoir; higher sedimentation rates occurred indeeper parts of the transects (Figure 3A, B). More-over, irregularities of the bottom prior to impound-ment resulted in irregular sediment accumulation(Figure 3C–F), whereas sedimentation was regularin flatter sub-bottom areas (Figure 3B).

The isopach map, that is, the map illustrating thevariation of sediment thickness, showed no clearpattern of sediment deposition in the main tribu-tary–dam axis (Figure 4). From this interpolation,total sediment accumulated in the MSM reservoirwithin the 52 years after impoundment was esti-mated to be 7.53 9 107 m3. The resulting meansediment deposition rate (extrapolated to the totalreservoir area) was 0.51 cm y-1.

Sediment Cores

Sediment accumulation as determined from sedi-ment coring was zero in one site, located in the

Figure 3. Sections of two seismic profiles (P1 and P2) showing: no sediment accumulation in the margins (A); sedimentaccumulation in deeper regions (B); regular sediment accumulation along a flat sub-bottom (that is, pre-flooding sub-strate, part of B) and irregular sediment accumulation along irregular sub-bottom (C–F).

Carbon Sequestration in a Large Hydroelectric Reservoir

reservoir margin (site 11), corroborating the seis-mic observations. At the other 15 sites, post-flooding sediment thickness varied from 2 to98 cm, corresponding to a maximum sedimentdeposition rate of 1.81 cm y-1.

Mean OC content by dry weight of post-floodingsediment samples was 2.3% (0.5% standard devi-ation) and mean C:N ratio was 10.6 (0.8 standarddeviation; Table 1). Mean d13C of post-floodingsediment varied from -31.3 to -19.8& (Table 1).Areal OC burial varied as a function of sedimentthickness in each core (Figure 5A). The lowest OCburial rates were registered at points close to themargin (sites 03, 07, and 10, Table 1). In general,the accumulation rates were higher at the up-stream part of the reservoir and decreased towardthe dam (Figure 5B). The highest OC burial ratewas recorded in a protected bay (209.4 g C m-2 y-1

at site 12, Table 1).Based on the regression model relating SAR to

the OC burial (OC burial = -11.4 + 104.5 9 SAR;R2 = 0.94; Figure 5A) and on the mean reservoirsediment accumulation rate (0.51 cm y-1), thereservoir-integrated OC burial rate was estimated at42.2 g C m-2 y-1 or 1.2 9 1010 g C y-1. This ratecorresponded to a total OC accumulation of0.62 Tg C since the reservoir was created.

DISCUSSION

Spatial Heterogeneity in SedimentAccumulation

Our data reinforce the importance of basin mor-phometry in determining the patterns of sedimentdeposition and accumulation in freshwater systems(Blais and Kalff 1995; Kortelainen and Pajunen2000; James and Barko 1993). The results of the

geophysical survey suggested that along the mar-gins of the MSM reservoir no sediment accumula-tion occurs (Figure 3), a point further confirmed bya sediment core taken in the margin fully com-posed of compact sandy soil (site 11, Table 1). Thispattern is likely caused by the resuspension ofsediments in shallower zones by waves and watercurrents, with subsequent settling in deeper zonesand by downslope gravitational transport (‘‘sedi-ment focusing,’’ Davis and Ford 1982; Blais andKalff 1995). Sediment focusing in reservoirs is alsoaffected by fluctuating water level for energy gen-eration, water supply or discharge regulation(Shotbolt and others 2005). For example, at lowwater level, fine sediments deposited in deeperwaters may become subjected to surface waves,resuspension and re-deposition elsewhere.

As sediment distribution is influenced by differ-ent factors, the extension of the marginal areawhere no sediment accumulates varies within andamong reservoirs. Calculating total reservoir OCburial based on burial rates determined in thedeeper parts of reservoirs and thereby neglectingthe reduced sediment deposition along the marginswill, therefore, lead to an overestimation of OCburial rates (see ‘‘Toward More Robust CarbonBudgets in Reservoirs’’ section) particularly in thecase of reservoirs with high shoreline developmentindexes (Kent and Wong 1982). We also observedthe effect of sediment focusing on smaller spatialscales in the absence of wind and water flow vari-ability: irregular reservoir bottom morphologyleads to irregular sediment deposition such thatlocations that were only a few centimeters elevatedhad a low sediment accumulation compared to theadjacent (few meters distant) lower areas (Fig-ure 3). Although these small scale irregularitiesmay have a negligible influence on the reservoirwide carbon burial estimation when using our ap-proach (for example, sedimentation map in Fig-ure 4), the extrapolation of results from a singledated core from a slightly elevated area to a largerpart of the reservoir may result in a large under-estimation of sediment accumulation.

Sediment accumulation rates at the samplingsites were positively correlated to distance from thedam (P = 0.005, r = 0.74), reflecting the frequentobservation that reservoirs tend to have highersuspended sediment concentrations near the inletthan near the dam (Thornton and others 1990).However, the overall sediment deposition in theMSM reservoir, as given by the seismic surveyinterpolation, showed a heterogeneous and irreg-ular picture with no clear trend (Figure 4). The lackof a clear sedimentation gradient along the main

Figure 4. Isopach map showing the distribution of total(cm) and mean yearly sediment accumulation (cm y-1)in the MSM reservoir.

R. Mendonca and others

Tab

le1.

Post

-floodin

gSedim

en

tC

om

posi

tion

,Sedim

en

tA

ccu

mu

lati

on

Rate

,an

dO

CB

uri

al

Rate

Sit

eS

ed

imen

tth

ick

ness

(m)

OC

(%)

C:N

rati

od1

3C

(&)

Sed

imen

tacc

um

ula

tion

rate

(cm

y-

1)

OC

bu

rial

(gC

m-

2y

-1)

Mean

SD

Mean

SD

Mean

SD

01

0.3

02.6

0.3

9.6

0.7

-22.7

1.3

0.5

634.4

02

0.4

42.7

0.3

11.2

1.9

-22.4

2.0

0.8

156.0

03

10.0

21.8

–10.8

–-

21.9

–0.0

43.1

04

0.2

22.6

0.6

9.8

0.8

-21.3

2.1

0.4

137.7

05

0.2

22.9

0.5

9.7

0.9

-23.3

1.1

0.4

131.9

06

0.4

03.1

0.3

11.2

2.3

-21.0

2.9

0.7

458.2

07

10.0

22.5

–9.6

–-

20.9

–0.0

43.3

08

0.6

22.1

0.4

10.9

1.2

-19.8

2.6

1.1

592.9

09

0.4

62.4

0.4

10.0

0.5

-22.1

1.3

0.8

560.3

10

10.0

41.9

0.1

10.6

0.9

-21.7

0.4

0.0

77.4

11

1–

––

––

––

––

12

0.9

82.7

0.4

9.7

0.7

-22.0

1.1

1.8

1209.4

13

0.4

62.2

0.4

12.1

1.9

-20.1

2.7

0.8

569.8

14

0.8

42.1

0.5

11.2

0.8

-20.6

1.7

1.5

6141.1

15

0.7

42.1

0.5

11.8

1.1

-21.8

1.8

1.3

7140.2

16

0.5

41.2

0.6

11.3

1.8

-20.2

2.0

1.0

0102.5

Pela

gic

Mean

0.5

02

.41

0.7

-2

1.4

0.9

68

6.2

SD

0.2

40.5

0.9

1.1

0.4

454.0

All

site

sM

ean

0.4

22

.31

0.6

-2

1.4

0.7

86

9.9

SD

0.2

90.5

0.8

1.0

0.5

458.6

Sei

smic

an

dC

orin

g0

.28

0.5

14

2.2

Data

der

ived

from

the

sedim

ent

core

sfu

rth

erco

mpare

dto

the

resu

lts

der

ived

from

the

seis

mic

surv

eys

(bot

tom

row

,it

ali

cs).

1Sit

escl

ose

toth

em

arg

ins.

Carbon Sequestration in a Large Hydroelectric Reservoir

axis in the MSM reservoir is likely due to the inputof sediment from many different tributaries to theMSM reservoir, creating several gradients of sedi-ment deposition that overlap with the main river–dam gradient.

The large-scale heterogeneity in sedimentationrates in the MSM reservoir implies that manyseismic transects are needed to get insight in localvariation. This becomes clear, for instance, whenthe interpolation of seismic transects suggests highsediment accumulation on parts of the reservoirmargins, where—as deducted from measurementsat other sites in the margin—no accumulation oc-curs. Although the interpolation technique couldclearly further be improved, for example, byincluding correlations with bathymetry, and byincreasing the number of seismic transects, theseismic approach has strong advantages over othermethods (see ‘‘Toward More Robust Carbon Bud-gets in Reservoirs’’ section).

Sediment Source and Composition

The usually intense deposition of inorganic fluvialmaterial leads to low sediment OC contents inreservoirs. The mean OC content in MSM sedi-ments was 2.3% (0.5 standard deviation, Table 1),similar to sediment OC content found in sets ofreservoirs in the USA (1.5–2% in Mulholland andElwood 1982, and 0.3–5.6% in Ritchie 1989). Moreeutrophic reservoirs, just as natural lakes, however,tend to exhibit higher OC due to autochthonousprimary production (for example, mean of 5% forreservoirs in Downing and others 2008, and meanof 12% for lakes in Dean 1999).

Our data suggest that the sediment of the MSMreservoir is dominated by terrestrial OC. In addition

to the low chlorophyll a concentrations in the water(Rangel and others 2012) and the high sedimentC:N ratios (9.6 to 12.1 typical for terrestrial matter;Elser and others 2000; Table 1), the isotopic com-position of the top sediment (-24.6 to -20.0&) wassimilar to that of pre-flooding terrestrial material(-23.2 to -19.8&) in the MSM reservoir.

Spatial Variability of OC Burial Rates

Sediment composition may affect the patterns be-tween sediment accumulation and OC burial. Vari-ations in sediment composition may be caused, onthe one hand, by differences in the quality of settlingmaterial (often coarse inorganic material at the in-flow and lighter, more organic material near thedam) and, on the other hand, by local differences inmineralization of sedimented organic material (of-ten highest at well oxygenated sites). In the MSMreservoir, however, the areal OC burial rates werestrongly correlated to sedimentation rates(P < 0.0001, r = 0.99; Figure 5A) and to distance tothe dam (P < 0.001, r = 0.82; Figure 5B). The arealOC burial rates were, however, not correlated tomean OC content (P = 0.15, r = -0.38) or to meanC:N ratio (P = 0.65, r = 0.12). This indicates that thesedimentation map generated from the geophysicalsurvey (Figure 4) is an indirect representation of theOC burial in the MSM reservoir.

Differences in OC Burial AmongReservoirs

The average OC burial rate in the MSM reservoir(42.2 g C m-2 y-1) was low compared to valuesreported for reservoirs located in temperate/borealclimate regions (up to 3,300 g C m-2 y-1, Mul-

Figure 5. A Relationship between OC burial rate and sediment accumulation rate (SAR) in the sampling sites. The dashedline represents the linear regression: OC burial = -11. 4 + 104.5 9 SAR; R2 = 0.94; P < 0.0001. B Relationship betweenOC burial rates and distance to the dam in the sampling sites, excluding the sites located by the reservoir margins.Correlation coefficient (Spearman) between these variables was significant (r = 0.82; P < 0.001).

R. Mendonca and others

holland and Elwood 1982; 1,110 g C m-2 y-1, So-bek and others 2012) and particularly low whencompared to small eutrophic reservoirs (148–17,392 g C m-2 y-1, Downing and others 2008).On the other hand, the OC burial rate in the MSMreservoir was similar to the burial rate in a largeAfrican tropical oligotrophic reservoir (mean23 g C m-2 y-1, Kunz and others 2011). Althoughthe large variations in OC burial have a variety ofunderlying causes ranging from differences insediment and organic matter delivery to variabilitymeasurement methods, temperature may play animport role. Higher temperatures strongly enhanceOC mineralization resulting in warmer sedimentsburying carbon less efficiently (Pace and Prairie2004; Gudasz and others 2010; Cardoso and others2014). A compilation of OC burial data from glob-ally distributed lakes indicated that OC burial effi-ciency increases exponentially with latitude (Alinand Johnson 2007).

Although the insights into reservoir OC burialrates are growing, an important remaining questionis the net effect of river damming on global OCburial. OC burial in hydroelectric reservoirs repre-sents an additional (and anthropogenic) carbon sinkif: (i) in the absence of the dams, the OC accumu-lated in reservoirs would not be buried downstream(for example, in floodplain lakes) or in the ocean(that is, the OC would be mineralized during thefluvial transport, in lakes or in the ocean) or (ii) theOC accumulated in reservoirs represents an addi-tional carbon input to the aquatic environment.Freshwater sediments tend to be less oxygenatedthan ocean sediments, resulting in lower OC min-eralization (Sobek and others 2009). In addition,the rapid accumulation of inorganic sediment,typical of hydroelectric reservoirs, causes oxygenexposure time in sediments to decrease, increasingOC burial efficiency (Sobek and others 2012).Hence, it is likely that the suspended OC load of theriver is buried more effectively in a reservoir than inthe ocean. Finally, the burial of autochthonous OCin hydroelectric reservoir represents an additionalsink of atmospheric CO2 even though autochtho-nous material is more efficiently mineralized (Gu-dasz and others 2012). Despite the evidence foradditional OC sink in reservoirs, determining themagnitude of this addition remains a challenge.

Reservoirs as Carbon Sources and Sinks?

MSM, like the majority of reservoirs and lakes, is anet source of CO2 and CH4 to the atmosphere. And,like most reservoirs and lakes, MSM also sequestersconsiderable amounts of carbon into its sediments.

The magnitude of both the sources and sinks canchange dramatically over the life-time of a reservoir.The present-day carbon emission to the atmospherefrom the MSM reservoir was estimated to be61 g C m-2 y-1, of which 55 g C m-2 y-1 is emittedas CO2 (data from 2006, Roland and others 2010)and 6 g C m-2 y-1 as CH4 (data from 2006, Omettoand others 2013). Accounting for a 25 times higherglobal warming potential (GWP) of CH4 compared toCO2 (IPCC 2007) returns a total greenhousegas emission of 400 g CO2-equivalent m-2 y-1.Assuming that OC burial corresponds to a removal ofCO2 equivalents, we can compare it with the GWPcaused by contemporary carbon emissions. Thus, theburial of 42.2 g C m-2 y-1 in the MSM reservoirwould correspond to 153 g CO2-equivalent m-2 y-1,suggesting a 2.5 times lower burial than emission.A similar evaluation for a temperate hydroelectricreservoir (Lake Wohlen: carbon emission of1,520 g CO2-equivalent m-2 y-1; OC burial of4,070 g CO2-equivalent m-2 y-1; Sobek and others2012) resulted in a 2.5 times higher burial thanemissions. Both processes take place simultaneouslywith reservoirs both accumulating carbon and out-gassing it, and the magnitude of each flux stronglyvaries among reservoirs (Mendonca and others2012). Two important factors are the trophic state(Hanson and others 2003) and the sediment load(Sobek and others 2009). High primary productionin eutrophic reservoirs tends to increase carbonburial and decrease CO2 emissions. At the same time,the high availability of labile organic carbon ineutrophic sediments may lead to strong oxygendepletion and increase in CH4 production. However,despite the somewhat higher production in themesotrophic–eutrophic Lake Wohlen when com-pared to the oligotrophic MSM reservoir, produc-tivity does not seem to be able to explain thedifferences in carbon fluxes. Water residence time inLake Wohlen is extremely low (2 days), minimizingthe importance of internal production as comparedto riverine inflow. The high sediment load to LakeWohlen results in a mean SAR (7.8 cm y-1; Sobekand others 2012) 15 times higher than that in theMSM reservoir. High SAR implies not only in higherOC burial rates, but also in a large supply of substrateto sediment and therefore a potentially highermineralization and higher carbon emissions.

Toward More Robust Carbon Budgets inReservoirs

Although the two elements of our combined ap-proach have been used separately before, to ourknowledge, this is the first time coring down to the

Carbon Sequestration in a Large Hydroelectric Reservoir

pre-flooding substrate (for example, Kunz andothers 2011) and a seismic survey (for example,Dunbar and others 1999) have been combined toestimate carbon burial in reservoirs. Seismicassessments of the bottom of aquatic systems arefrequently applied for other purposes, for instanceto study the loss in reservoirs’ water storagecapacity (for example, Dunbar and others 1999;Odhiambo and Boss 2004; Bennett and others2005) or to assess sediment deposition patterns inlakes (Mullins and others 1991; Adams and others2001; Hilbe and others 2011; Heirman and others2011; Lyons and others 2011). In lakes, however,seismic assessments have been used as well toestimate the total sediment or total carbon accu-mulation in the sediments (Kortelainen and others2004; Ferland and others 2012; Tunnicliffe andothers 2012).

The significance of applying a seismic assessmentto the MSM reservoir is evident because sedimentthickness varies strongly spatially. Extrapolatingsedimentation rates and OC burial rates from the16 sediment cores, or from the pelagic sedimentcores only, to the MSM reservoir area would haveled to approximate 45 or 95% higher estimates ascompared to the seismic approach (Table 1). Thisoverestimation is similar to those found in smalllakes, where it was estimated that single site-basedcalculations may lead to overestimation of OCburial rates of up to 54% (Mackay and others2012). It should be noted, however, that becausereservoirs are known to be highly heterogeneous,all OC burial assessments, to our knowledge, havesomehow accounted for spatial heterogeneity insedimentation. For example, the recent assessmentof OC burial in the large Lake Kariba was based oncore data, but in combination with a sedimentationmodel that considers the system morphology andits different sedimentation zones (Kunz and others2011).

Reservoir heterogeneity has traditionally beenaccounted for by estimating sediment accumula-tion rates from loss in water storage volume. Al-though the first and most commonly citedassessments of OC burial in reservoirs (Mulhollandand Elwood 1982; Dean and Gorham 1998) did notdescribe in detail the methods used, other studiesestimated loss in water storage volume throughbathymetric surveys repeated over time (forexample, Downing and others 2008; Sobek andothers 2012). Seismic surveys have advantagescompared to traditional approaches. Seismic pro-files do not require previous bathymetric surveys.Although bathymetric maps are affected by unac-counted variations in water levels or in transducer

elevation (Byrnes and others 2002), these variableshave no effect on seismic measurements. More-over, the bathymetric approach needs historicaldata which are rarely available and often lessaccurate. In contrast, the seismic approach is basedon a one-time only assessment and the sedimentaccumulation can be assessed immediately after thesurvey. The further assessment of OC burial re-quires analysis of sediment dry mass accumulationand OC content only (see ‘‘Materials and Methods’’section) and does not require the more laboriousmeasurements of sediment dry bulk density or themore expensive measurement of radioisotopes.Additionally, the results are not affected by theoccurrence of sediment disturbance, for example,by wind-driven mixing, which is common inhydroelectric reservoirs. In short, the combinedapproach results in a relatively fast time-integratedassessment of the reservoir wide OC burial.

The combined approach is potentially applicableto any kind of artificial reservoir, as long as there isa shift in sediment characteristics (for example,density and grain size) following impoundment,which is likely the case for most reservoirs. Low-frequency acoustic sources (3.5–18 kHz), as wasused in this study (10 kHz), are capable of pene-trating up to 10 m into muddy reservoir sediments.In the case of thicker sediment layers, though, itmight be necessary to combine lower-frequency(<3.5 kHz; for an optimum penetration) withhigher-frequency acoustic sources (>3.5 kHz; for abetter resolution on the top sediment) (see Dunbarand others 1999 for a multifrequency profilingapproach). Importantly, seismic profiling requires aminimum water column depth of two meters dueto interfering sound waves, hampering its applica-bility in shallow reservoirs or reservoirs with largeshallow areas where important sediment accumu-lation takes place.

Because the seismic analysis depends on theexistence of a precisely dated shift in sedimentcomposition, it is, however, not directly suitable forestimating accumulation rates in natural lakes.Another limitation of our approach is that it onlyestimates the total accumulation from the date ofreservoir impoundment to the present and does notpermit a detailed analysis of the changes in accu-mulation rates over time unless it is combined withother dating proxies such as radioisotopes.

The number of transects and cores needed tomake a reliable assessment depends on the size andthe heterogeneity of the study area. In the case ofstrong sediment sorting (for example, the extremecase of up to 100% organic sediment in shelteredplaces and up to 100% sand in higher velocity

R. Mendonca and others

places) different SAR-OC regression models shouldbe applied to different subareas of the reservoir.The very good fit of the SAR-OC model for theMSM reservoir (Figure 5A) suggests that fewerthan 16 cores would have been sufficient. This wasconfirmed by simple sample size selection analysissimulating the decreasing number of sedimentcores (see Supplementary Material for details). Asimilar analysis simulating the effect of the numberof seismic transects suggests that a reduction from16 to 12 transects still identifies the major spatialheterogeneities in sedimentation with only a minordifference (15%) in total sediment volume (seeSupplementary Material for details). Hence, al-though earlier work suggests that seismic transectsshould be spaced 500 m apart or less in smallerreservoirs (for example, Dunbar and others 1999;Bennett and others 2005), the 5 km spacing ap-plied in the large MSM reservoir seemed to result inrelatively robust assessment of the spatial distribu-tion of sediment. Nevertheless, we encourage theacquisition of denser seismic surveys, with lessspacing among transects and including the mouthof tributaries and protected bays, where sedimen-tation can vary depending on the local sedimentload and hydrodynamics.

CONCLUSION

Even though the relative amount of carbon beingoutgassed and buried varies among systems, it isclear that OC burial in hydroelectric reservoirs canrepresent an important additional (and anthropo-genic) carbon sink. The combination of a geo-physical seismic survey and whole sediment layeranalysis as described in this study allows a rela-tively fast, inexpensive, and integrative assessmentof OC burial in reservoirs. Because this combinedapproach permits the immediate assessment ofburial after the survey, it may contribute to morecomplete estimations of the amount of carbonstored in reservoirs in a relatively short period oftime. Additionally, it leads to more insight intolocal variables influencing the carbon burial basedon a few sample points only. If repeated in otherreservoirs of varying characteristics and located indifferent biomes, this assessment may lead to betterworld wide estimations of carbon burial in fresh-water systems.

ACKNOWLEDGMENTS

We are thankful to Marten Scheffer for the insightsand critical discussions, to Carlos Henrique Estradaand Anderson Freitas for the support in the field and

laboratory analysis, and to Marcio Malafaia for help-ing with the maps. The authors acknowledge supportfrom Coordenacao de Aperfeicoamento de Pessoal deNıvel Superior—CAPES (Raquel Mendonca), NWO-VENI grant 86312012 (Sarian Kosten), The SwedishResearch Council Formas (Sebastian Sobek), andConselho Nacional de Investigacao Cientıfica e Tec-nologica—CNPq (Fabio Roland). This research wasalso supported by Grants from Furnas.

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