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Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to...

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The Role of Rivers in the The Role of Rivers in the Global Carbon Cycle: Global Carbon Cycle: Landscape-Hydrology- Landscape-Hydrology- Biogeochemistry Connections Biogeochemistry Connections Ocean 582/529 Fall ‘03 I. Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific global view
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Page 1: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

The Role of Rivers in the Global The Role of Rivers in the Global Carbon Cycle: Landscape-Hydrology-Carbon Cycle: Landscape-Hydrology-

Biogeochemistry ConnectionsBiogeochemistry Connections

Ocean 582/529 Fall ‘03

I. Review of overall Rivers cycle

II. In depth analysis of components, to ….

III. … derive functional models of a geographic-specific global view

Page 2: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

VEGETATION

SOILS (+)

ATMOSPHERIC CO2

Active SOM,NP (1-2y)

Int. SOM,NP (20-40y)

Pass, SOM,NP (1000y)

Litter

COASTALOCEAN

SHELF SEDIMENTS

~.4 aw

DOC UV Ox?

.1 cw, ~.4aw

.1 cw,~.4aw

.2

.2

MCO3

.2S&S

gigatons/ycw = conventional wisdomaw = alternate wisdomS&S = sensu Sarmiento & Sundquist(+) anthro. effect

RIVERS

GLOBAL RIVER C CYCLE

ESTUARIE

S

ANTHROPOGENICN,P, Toxics

(+:1.8+1.1)

(P Desorp)

PPR

PPT->Q

DAMSRIP

ARIAN

(1)CO2+H20+M(C,Si)O3->M+2HCO3(2) SOM->CO2

erosion, PPr

leaching

DIC (pCO2,HCO3)

POC (.5uM - 1mm)

DOC (%s < .5uM)

Q (N,P,Toxics)

.4 (+)

.2 cw .5aw(++)

.2 (~)

.1 cw, ~.4aw

COASTALOCEAN

Page 3: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

THE RIVER CONTINUUM

Page 4: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

0

4

8

0

102030

0

600

1,200

0

200

400

0

200

400

-10

-20

-30

0

10

20

0

0.6

1.2

DOC (mg/l)

pCO2 (uM) O2 (uM)

DON (uM)

NO3 (uM) PO4 (uM)

DIC (uM)

DIC13 (permil)

FSS (mg/l) CSS (mg/l)

0

400

800

050

100150

50,000

100,000

150,000

200,000

250,000June 2

Oct 20

Dis

cha

rge

(m

3/s

)

Time over a water year

Time (water year)

OBIDOS: “New Orleans”

Page 5: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

Amazon

Zaire

Orinoco

Yangsei

Brahmaputra

Yenisei

Lena

Mississippi

Ganges

Mekong

Page 6: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

0

50,000

100,000

150,000

200,000

250,000Amazon

ZaireOrinoco

Yangsei

Brahmaputra Yenisei Lena

Mississippi

Ganges Mekong

195,000

40,00035,000

28,000

19,000 18,00016,300

15,80015,600

14,800

0

2

4

6

8Amazon

Zaire

Orinoco Yangsei

Brahmaputra

Yenisei Lena Mississippi

Ganges Mekong

6.10

3.80

0.991.90

0.61

2.60 2.503.30

0.980.79

Discharge (m3/s)

Basin Area (Mkm2)

0

300

600

900

1,200

1,500Amazon

Huanghe

Brahmaputra Ganges

Yangsei

Irrawaddy

Magdalena Mississippi

Godavari Mekong

1,200

1,100

540 520 480

260220 210

170 160

Sediments (MT/y)

Top 10 Rivers

Page 7: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

TOP 10, REST OF RIVERS

Discharge 1.3 M m3/s Sediment Transport: 31,000 MT/y

2456 78 13

10 9

23 456

78

10 19

Amazon (1) Zaire (2) Orinoco (3) Yangsei (4)Brahmaputra (5) Yenisei (6) Lena (7) Mississippi (8) Ganges (9) Mekong (10)

Amazon (1) Huanghe (2) Brahmaputra (3) Ganges (4) Yangsei (5) Irrawaddy (6) Magdalena (7) Mississippi (8) Godavari (9) Mekong (10)

Page 8: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

Amazon

AsSE

Ocn

ErsA

AfrW

AsE

NAmENAmW NAmA

SAmE

EurW

SAmW

CAmAfrE

EurEAus

Ocn

AsE

AsSE CAmSAmE Amazon

SAmW

NAmANAmEEurENAmW

AfrWAfrEErsA

EurWAus

Discharge

Sediment Transport

1.3 M m3/s

31,000 MT/y

GEOGRAPHIC ZONES

Page 9: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

Oce

AsE

AsSE

SA NE

SA W

SA SENA W

NA At

NA EGEA At

Eur

Afr W

Afr E

Aust

0

50

100

150

200

250

300

350

"Traditional": 200

Area-loading: 350

Calc. Yield: 800

POC Loading by Geographic Region

"Best Guess: ~500 ish"

Tg/y

Consequences for different assumptions in computation of POC yield by geographic zone, ranging from the conventional wisdom of .2 Gt/y , to an area-loading function (.35 Gt/y), and a calculated yield function (.8 Gt/y). ZonesInclude Oceania (Oce), East and Southeast Asia (AsE, AsSE), South America (North-east SA NE, western SA W, southeast SA SE), North America (West NA W, Atlantic NA ATL, East and Gulf NA EG), Europe & Artic (Atlantic EA At, Eur), Africa (West W, East Afr E) and Australia (Aust).

Page 10: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

SPO

Ica

Jut Jur

JapPur

Neg Mad

Tro

Tap Xin

Par

0

10,000

20,000

30,000

40,000

50,000

par = sum "parana"Tap, Xin approxTocantins not incl

AMAZON TRIBUTARIES

Page 11: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

FLUVIAL SYSTEMS BOX MODEL

SOILS

RIVERS

STREAMS

ATMOSPHERE

DAMS CoastalZone

FLOODPLAINS

RIPARIAN

Page 12: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

Soils

Rivers

Streams

Atmosphere

DamsCoastal Zone

FloodplainsRiparian

PATHWAYS OF ATMOSPHERIC CO2 THROUGH FLUVIAL SYSTEMS

Richey, J.E. (in press). Ch. 15. Field et al (eds) A SCOPE/GCP Rapid Assessment Project. Island Press.

Conventional Wisdom

- 0.6

0.6 River← Atm

POC → sea

DOC → sea

DIC → sea

Δ Net Atm

Cont Sed

Outgassing

-2.0 -1.0 0.0 1.0 2.0 Gt C/y

- 1.1

1.3

CW + Continent Sediment

↓ ↓

- 1.6

1.8

2.5x

2x

?

CW+CS+(POC,DOC)

2.5x

2x

CW+CS+OC+OG

- 0.2

2.6

?

Transient

- 0.3

1.3

Page 13: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

STRUCTURE OF LAND-FLUVIAL SYSTEMS

River Routing and Sediment Transport NetworkGas Exchange

FloodplainErosion

Deposition

Estuary/Delta

Reservoirs Free-Flowing

Land Surface Processes (Grid)

Surface Water

River Routing

mineral soil

Water and dissolved

Fresh OM Particulate

Riparian/FloodplainUpland

Page 14: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

SCALINGAmazon Floodplain from Aircraft: ‘eye’

Amazon Floodplain from Landsat TM: 30 m

Xingu (Amazon trib) from AVHRR: 1 km

Taiwan: AVHRR to Global 1-degree (~100 km)

Page 15: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

“HYDROLOGY” IN A REGIONAL NPP MODEL (e.g., CASA)

Water Stress Scalar Formulation:We(t) = 0.5 [1 + ET(t) / PET(t)] From hydrology model

NPP(t) = emax * Te (t) * We (t) * FPAR (t) * PAR(t)

FPARGlobal CASAcalibration Sn Albedo

Surf. Temperature Sn, Temp., Rain,Ln, Soils, Roots

Page 16: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

INTERANNUAL NPP MODEL (CASA Potter et al)

Tg C 8-km-1 mo-1

-1.0 -0.5 0 0.5 1.0

INIT 82 83 84 85 86 87 88 89 90

0 25 50 75 100

0

125

250

375

500

col

row

-1000000-500000 0 500000 1000000

6 N

20 S

La

titu

de

1983 1985 1987 1990

g C m-2 yr-1

-500 -250 0 250 500

Page 17: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

RIVERS & FLOODPLAINS (> 100 m in width)

Page 18: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

$

$

$

$$

$

$

$$

$

$

$

$$$

PB-1

PB-2

JaruJIP-3

COM-1

COM-2

JIP-1

Rolim

UrupáJIP-2

JIP-4

JIP-5Preto

Machadinho

Streams (< 100 m) STREAMS & RIPARIAN (< 100 m)

Page 19: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

15

0

5

10

20

25

30

J F M A M J J A S O N D

CO

2 E

vas

ion

(T

g C

mo

-1)

T (>100m)

S (<100 m)MF

MC

: 1.2 ± . 3 Mg C ha-1 y-1 (basin ~ .5 Gt y-1)

CO2 EVASION: FROM WATER → ATMOSPHERE

Low-ElevationHigh-Elevation

DIC - UDOC -FPOC -CPOC

14C

14C: Downstream Translocation

Space & Time

Soil CO2

SoilDOC

Litter-fall

Macro-phytes

0%

10%

20%

30%

40%

Plankton

Sources & Implicit Dynamics?

Page 20: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

Central Amazon Basin (1.77 million km2)

Methane Emission CO2 Evasion Tg C y-1 Tg C y-1

7.6 + 2.3 210 + 60

Lowland Amazon Basin (5.19 million km2)Methane Emission 25 + 8 Tg C y-1

Greenhouse gas potential ~ 0.5 Pg C y-1

as CO2

CH4 and CO2 Emissions

Page 21: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.
Page 22: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

IMPORTANCE OF EPISODIC EVENTS

ENSO-Orchestrated Sediment Accumulation on Bolivian Amazon floodplains (Aalto et al. Nature 2003) [& utility of SRTM]

Page 23: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

NORTH AMERICA: “ambiguous, but provocative”

Increase in the export of alkalinity from North America’s largest river (Raymond & Cole, Science, 2003)

Long-term decline in carbon dioxide super-saturation in rivers across the contiguous United States. (Jones et al, Geophys Res Lett in press)

Page 24: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

RECENT GBC Publications on Trace Gas Sources & Sinks in Peatlands, Tundra, Rice paddies, Savannas; as f(water table depth, flow regimes…)

Torben Christensen “….a good understanding of local controls … does not necessarily explain large scale gradients…..”

Progress, but not there yet…….

Page 25: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

NAGA Version 2 (1-km)Physical Template, Dynamic Modeling, Drivers

Page 26: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

BIOPHYSICAL DATA LAYERS

Page 27: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

(REGIONAL) HYDROLOGY ←→BGC: Q= ΣR = P – ET + ΔSM

Page 28: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

HYDROLOGY MODEL “FIELDS”

Soil Moisture→ Discharge→ Trace Gas Biogeochemistry

Rn

LAI

T

Page 29: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.
Page 30: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

UNCERTAINTIES IN POC LOADING BY GEOGRAPHIC REGION

Oce

AsE

AsSE

SA NE

SA W

SA SENA W

NA At

NA EGEA At

Eur

Afr W

Afr E

Aust

0

50

100

150

200

250

300

350

"Traditional": 200

Area-loading: 350Calc. Yield: 800

"Best Guess: ~500 ish"

Tg/y

Average OC concentration of Fly-Strickland river samples ~ 3.75% (June ’03)

Page 31: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

IMPORTANCE OF EPISODIC EVENTS

ENSO-Orchestrated Sediment Accumulation on Bolivian Amazon floodplains (Aalto et al. Nature 2003) [& utility of SRTM]

Page 32: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.
Page 33: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

physical forcing via remote sensing

(solar radiation, FPAR, rainfall, temperature)

terrestrial NPP

and biomass turnover

via CASA ecosystem model

hydrology

via VIC model

soil biogeochemistry

via ROMBUS model

aquatic biogeochemistry

via ROMBUS model

geographical properties via GIS

(vegetation, soil, topography, river network, etc.)

DOC, DIC

CO2

evasion

heterotrophicrespiration

DOC

POCDIC

CO2

fixation

water flux

carbon flux

autotrophicrespiration

ROMBUS (River basin Organic Matter and Biogeochemistry Synthesis Model)

HMW DOC(1-30 kDa)

LMW DOC(<1 kDa)

CH4

Mineral-Associated OM(FPOM) (0.1 µm - 63 µm)

HMW FPOC(1-30 kDa)

LMW FPOC(<1 kDa)

Detrital Particulate Organic Matter (>2mm)

Production via Terrestrial Biosphere Model

Living Organic Carbon

CPOC

CO2CO2, CH4

Black C (soot and charcoal)

DOM (>0.1 µm)

CPOM (63 um - 2 mm)DIC

VHMW DOC(>30 kDa)

VHMW FPOC(>30 kDa)

Structural C(insoluble)

Metabolic C(soluble)

LMW DON(200-1000Da)

VLMW DON(<200Da)

NH4

LMW FPON(200-1000Da)

VLMW FPON(<200Da)

Detrital Particulate Organic Matter (>2 mm)

Structural N(insoluble)

Metabolic N(soluble)

Production via Terrestrial Biosphere Model

Living Organic Nitrogen

CPON

Sorbed NH4

CPOM (63 um - 2 mm)

NO3

N2, NOx

NH3

Mineral-Associated OM (FPOM)

(0.1 µm - 63 µm)VHMW DON

(>30 kDa)VHMW FPON

(>30 kDa)

DOM (>0.1 µm)

Carbon Nitrogen

Biotic fluxes

Abiotic fluxes

Page 34: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

NESTED AND COUPLED MODELS; e.g.

Page 35: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

FLOODS OF THE MEKONG (2000)

Page 36: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.
Page 37: Ocean 582/529 Fall ‘03 I.Review of overall Rivers cycle II. In depth analysis of components, to …. III. … derive functional models of a geographic- specific.

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