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Investigation:

CD-06 (Richey / Victoria)

LBA Dataset ID:

CD06_OUTGASSING

Originator(s):

1. RICHEY, J.E.
2. MELACK, J.M.
3. AUFDENKAMPE, A.K.
      4. BALLESTER, M.V.R.
5. HESS, L.L.

Point(s) of Contact:

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (ornldaac@ornl.gov)

Dataset Abstract:

Whereas global estimates of atmospheric CO2 exchange indicate that the tropics are near equilibrium or are a source with respect to carbon, ground-based estimates indicate that the amount of carbon that is being absorbed by mature rainforests is similar to or greater than that being released by tropical deforestation (about 1.6 Gt C per yr). Estimates of the magnitude of carbon sequestration are uncertain, however, depending on whether they are derived from measurements of gas fluxes above forests or of biomass accumulation in vegetation and soils. It is also possible that methodological errors may overestimate rates of carbon uptake or that other loss processes have yet to be identified. Here we demonstrate that outgassing (evasion) of CO2 from rivers and wetlands of the central Amazon basin constitutes an important carbon loss process, equal to 1.26 0.3Mg C per ha per yr. This carbon probably originates from organic matter transported from upland and flooded forests, which is then respired and outgassed downstream. Extrapolated across the entire basin, this flux at 0.5 GtC per yr is an order of magnitude greater than fluvial export of organic carbon to the ocean. From these findings, we suggest that the overall carbon budget of rainforests, summed across terrestrial and aquatic environments, appears closer to being in balance than would be inferred from studies of uplands alone.

Beginning Date:

1982-04-01

Ending Date:

1996-06-30

Metadata Last Updated on:

2013-03-27

Data Status:

Archived

Access Constraints:

PUBLIC

Data Center URL:

http://daac.ornl.gov/

Distribution Contact(s):

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (ornldaac@ornl.gov)

Access Instructions:

PUBLIC

Data Access:

IMPORTANT: The LBA-ECO Project website is no longer being supported. Links to external websites may be inactive. Final data products from the LBA project can be found at the ORNL DAAC. Please follow the fair use guidelines found in the dataset documentation when using or citing LBA data.
Datafile(s):

LBA-ECO CD-06 Flux of CO2 from Amazon Mainstem Rivers, Tributaries, and Floodplains:  http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1151

Documentation/Other Supporting Documents:

LBA-ECO CD-06 Flux of CO2 from Amazon Mainstem Rivers, Tributaries, and Floodplains:  http://daac.ornl.gov/LBA/guides/CD06_Outgassing.html

Citation Information - Other Details:

Richey, J.E., J.M. Melack, A.K. Aufdenkampe, V.M. Ballester and L.L. Hess. 2013. LBA-ECO CD-06 Flux of CO2 from Amazon Mainstem Rivers, Tributaries, and Floodplains. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A. http://dx.doi.org/10.3334/ORNLDAAC/1151

Keywords - Theme:

Parameter Topic Term Source Sensor
CARBON DIOXIDE BIOSPHERE AQUATIC ECOSYSTEMS COMPUTER MODEL ANALYSIS

Uncontrolled Theme Keyword(s):  CO2 OUTGASSING, MAINSTEM, PCO2, SEASONAL FLOODING, VARZEA

Keywords - Place (with associated coordinates):

Region
(click to view profile)
Site
(click to view profile)
North South East West
  AMAZON BASIN 0.00000 -7.50000 -52.00000 -72.00000

Related Publication(s):

Richey, J.E., J.M. Melack, A.K. Aufdenkampe, V.M. Ballester and L.L. Hess. 2002. Outgassing from Amazonian rivers and wetlands as a large tropical source of atmospheric CO2.Nature 416:617-619.

Data Characteristics (Entity and Attribute Overview):

Data Characteristics:

Data are available in five comma separated ASCII files:



File #1: Monthly_mean_hydrograph.csv

File #2: Outgassing_river_area_basin_scale.csv

File #3: Varzea_pCO2.csv

File #4: Calculated_CO2_fluxes_basins.csv

File #5: Calculated_CO2_fluxes_reaches.csv



File #1:

File name:,Monthly_mean_hydrograph.csv,,

File date:,1/10/2012,,

Associated LME:,CD06_Outgassing,,

,,,

Column,Column_heading,Units/format,Explanation

1,River_basin,,River basin name

2,Month,,Month of the year

3,Mean_monthly_dischage ,m3/s,Monthly average discharge reported in meters cubed per second (m3/s)

4,Percent_max,%,Percent of maximum monthly average discharge

,,,

,Missing data are indicated by -9999,,



Sample data for File #1:

River_basin,Month,Mean_monthly_discharge ,Percent_max

SPO,January,46495,73

Ica,January,5582,57

Jutai,January,4911,84

Jurua,January,6856,88

...

Madeira,December,20281,37

Trombetas,December,760,17

Obidos,December,110769,-9999



File#2:

File name:,Outgassing_river_area_basin_scale.csv,,,,

File date:,1-Oct-12,,,,

Associated LME file:,CD06_Outgassing,,,,

,,,,,

Column,Column_heading,Units/format,Explanation,,

1,Basin_name,,Basin name

2,Basin_ID,,Basin identification: each basin is assigned a unique numeric identifier (see accompanying map),,

3,Total_basin_area,km2,Total land area in the delineated basin reported in square kilometers (km2).,,

4,Month,,Month of the year,,

5,Area_large_rivers,km2,Calculated area of rivers with a width greater than or equal to 100 m reported in square kilometers (km2). These rivers were detectable in satellite images,,

6,Area_small_rivers,km2,Calculated area of rivers with a width less than 100 m reported in square kilometers (km2). Area was derived by a stream density function since these were too small to be detected in imagery,,

,,,,,

,Missing data are represented by -9999,



Sample data for File #2:

Basin_name,Basin_ID,Total_basin_area,Month,Area_large_rivers,Area_small_rivers

central varzea/channel,Basin 1 ,152830,Jan,28814,-9999

central varzea/channel,Basin 1 ,152830,Feb,28149,-9999

central varzea/channel,Basin 1 ,152830,Mar,38418,-9999

...

Japura,Basin 24,121041.25,Jan,8248,3704

Japura,Basin 24,121041.25,Feb,7435,3339

Japura,Basin 24,121041.25,Mar,9002,4042

...

Xingu,Basin 5,56195.15,Oct,353,506

Xingu,Basin 5,56195.15,Nov,353,506

Xingu,Basin 5,56195.15,Dec,464,770



File #3:

File name:,Varzea_pCO2.csv,,,,

File date:,21-Nov-12,,,,

Associated LME:,CD06_Outgassing,,,,

,,,,,

Column,Column_heading,Units/format,Explanation,,

1,Location,,General description of the sampling location,,

2,Reaches,,The identity of the reaches included in the general sampling location see accompanying information for more detail about the reaches,,

3,Sampling_location,,Description of the sample location: surface depth and sides are locations within lakes while all includes all samples from lakes and paranas (side channels) ,,

4,pCO2_mean,uM,Partial pressure of CO2 reported in micromoles of CO2 per liter of water,,

5,pCO2_Stdev,uM,Standard deviation of the mean value of pCO2 reported in micromoles of CO2 per liter of water,,

6,N,,Number of samples included in the calculation of the mean and standard deviation,,



Sample data File #3:

Location,Reaches,Sampling_location,pCO2_mean,pCO2_Stdev,N

Upriver,1 through10,All,488,352,316

Upriver,1 through10,Surface,392,269,121

Upriver,1 through10,Depth,572,382,89

...

Downstream,17 through 18,Depth,298,152,30

Downstream,17 through 18,Sides,218,146,57

Downstream,17 through 18,Paranas (side channels) and tributaries,246,174,44



File #4:

File name,Calculated_CO2_fluxes_basins.csv,,,,,,,,,,,,,

File date,28-Sep-12,,,,,,,,,,,,,

Associated LME,CD06_Outgassing, ,,,,,,,,,,,,

,,,,,,,,,,,,,,

Column,Column_heading,Units/fomat,Explanation,,,,,,,,,,,

1,Basin_name,,Basin name,,,,,,,,,,,

2,Basin_ID,,Basin_ID,,,,,,,,,,,

3,Month,,Month of the year,,,,,,,,,,,

4,SA_large_rivers,km2,Surface area of large ( greater than 100 m width) rivers in the basin reported in square kilometers (km2),,,,,,,,,,,

5,pCO2_large_rivers,uM CO2,Mean pCO2 for the month from the CAMREX data reported in micromoles of CO2 per liter (uM CO2): where no direct measurements are available values for the nearest location were used,,,,,,,,,,,

6,z_large_rivers,um,Surface boundary layer for the large rivers reported in microns (um),,,,,,,,,,,

7,CO2_flux_m2_large_rivers,umoles CO2/m2/s,Evasion of CO2 from the large rivers reported in micromoles of CO2 per meter squared per second (umol CO2/m2/s),,,,,,,,,,,

8,CO2_flux_km2_large_rivers,t CO2/km2/month,Evasion of CO2 from the large rivers reported in metric tons of CO2 per kilometer squared per month (t CO2/km2/month),,,,,,,,,,,

9,CO2_flux_basin_large_rivers,Tg CO2/month ,Evasion of CO2 from the large rivers reported in teragrams of CO2 per month for the entire basin (Tg CO2/month),,,,,,,,,,,

10,SA_small_rivers,km2,Surface area of small ( less than 100 m width) rivers in the basin reported in square kilometers (km2),,,,,,,,,,,

11,pCO2_small_rivers,uM CO2,Mean pCO2 for the month from the CAMREX data reported in micromoles of CO2 per liter (uM CO2): where no direct measurements are available values for the nearest location were used,,,,,,,,,,,

12,z_small_rivers,um,Surface boundary layer for the small rivers reported in microns (um),,,,,,,,,,,

13,CO2_flux_m2_small_rivers,umoles CO2/m2/s,Evasion of CO2 from the small rivers reported in micromoles of CO2 per meter squared per second (umol CO2/m2/s),,,,,,,,,,,

14,CO2_flux_km2_small_rivers,t CO2/km2/month,Evasion of CO2 from the small rivers reported in metric tons of CO2 per kilometer squared per month (t CO2/km2/month),,,,,,,,,,,

15,CO2_flux_basin_small_rivers,Tg CO2/month,Evasion of CO2 from the small rivers reported in teragrams of CO2 per month for the entire basin (Tg CO2/month ),,,,,,,,,,,

,,,,,,,,,,,,,,

Sample data for File #4:

Basin_name,Basin_ID,Month,SA_large_rivers,pCO2_large_rivers,z_large_rivers,CO2_flux_m2_large_rivers,CO2_flux_km2_large_rivers,CO2_flux_basin_large_rivers,SA_small_rivers,pCO2_small_rivers,z_small_rivers,CO2_flux_m2_small_rivers,CO2_flux_km2_small_rivers,CO2_flux_basin_small_rivers

Javari,Basin 29,Jan,2734,159,183,1.82,57,0.16,2697,159,180,1.85,58,0.16

Javari,Basin 29,Feb,2931,174,183,1.99,63,0.18,2892,174,180,2.03,64,0.18

Javari,Basin 29,Mar,3208,163,183,1.88,59,0.19,3164,163,180,1.91,60,0.19

Javari,Basin 29,Apr,3607,147,183,1.68,53,0.19,3558,147,180,1.71,54,0.19

...

Purus,Basin 20,Dec,9321,95,183,1.09,34,0.32,3617,95,180,1.11,35,0.13

Manacapura,Basin 19,Jan,783,85,183,0.98,31,0.02,221,85,180,0.99,31,0.01

Manacapura,Basin 19,Feb,783,118,183,1.35,43,0.03,229,118,180,1.38,43,0.01

Manacapura,Basin 19,Mar,1008,147,183,1.69,53,0.05,304,147,180,1.72,54,0.02

...

Xingu,Basin 5,Oct,353,112,183,1.29,41,0.01,506,112,180,1.31,41,0.02

Xingu,Basin 5,Nov,353,105,183,1.2,38,0.01,506,105,180,1.22,39,0.02

Xingu,Basin 5,Dec,464,81,183,0.92,29,0.01,770,81,180,0.94,30,0.02



File #5:

File name,Calculated_CO2_fluxes_reaches.csv,,,,,,,,,,,,,

File date,28-Sep-12,,,,,,,,,,,,,

Associated LME,CD06_Outgassing,,,,,,,,,,,,,

,,,,,,,,,,,,,,

Column,Column_heading,Units/format,Explanation,,,,,,,,,,,

1,Reach Name,,Name of mainstem river reach ,,,,,,,,,,,

2,Reach_ID,,Numeric identification of river reach defining the mainstem (see associated documentation),,,,,,,,,,,

3,Month,,Month ,,,,,,,,,,,

4,Area_mainstem ,km2,Area of the mainstem river in kilometers squared (km2),,,,,,,,,,,

5,pCO2_mainstem ,uM CO2,Mean monthly pCO2 concentrations for each mainstem river reach based on measured values from CAMREX cruises reported in micromoles of CO2 per liter (uMCO2),,,,,,,,,,,

6,Z_mainstem,um,Surface boundary layer for the mainstem river reported in microns (um),,,,,,,,,,,

7,CO2_flux_m2_mainstem,umoles CO2 /m2/s,Calculated rate of CO2 outgassing from the mainstem river surface reported in micromoles of CO2 per square meter per second,,,,,,,,,,,

8,CO2_flux_km2_mainstem,tons of CO2/km2/month,Calculated rate of CO2 outgassing from the mainstem river surface reported in metric tons of CO2 per square kilometer per month,,,,,,,,,,,

9,CO2_flux_reach_mainstem,Tg CO2/month by reach,Total amount of CO2 outgassing from the mainstem river surface reported in teragrams of CO2 per delineated reach of the river per month,,,,,,,,,,,

10,Area_ varzea ,km2,Area of the varzea region calculated from satellite images and reported in kilometers squared (km2),,,,,,,,,,,

11,pCO2_varzea,uM CO2,Mean pCO2 concentrations for the varzea regions based on measured values from CAMREX cruises reported in micromoles of CO2 per liter (uM CO2). Mean values were calculated for three regions: upriver; midriver and lower river,,,,,,,,,,,

12,Z_varzea,um,Surface boundy layer for the varzea reported in microns (um),,,,,,,,,,,

13,CO2_flux_m2_varzea,umoles CO2 /m2/s,Calculated rate of CO2 outgassing from the varzea surface reported in micromoles of CO2 per square meter per second,,,,,,,,,,,

14,CO2_flux_km2_varzea,tons of CO2/km2/month,Calculated rate of CO2 outgassing from the varzea surface reported in metric tons of CO2 per square kilometer per month,,,,,,,,,,,

15,CO2_flux_reach_varzea,Tg CO2/month by reach,Total amount of CO2 outgassing from the varzea surface reported in teragrams of CO2 per delineated reach of the river per month,,,,,,,,,,,

,,,,,,,,,,,,,,

Sample data File #5:

Reach Name,Reach_ID,Month,Area_mainstem ,pCO2_mainstem ,Z_mainstem,CO2_flux_m2_mainstem,CO2_flux_km2_mainstem,CO2_flux_reach_mainstem,Area_ varzea ,pCO2_varzea,Z_varzea,CO2_flux_m2_varzea,CO2_flux_km2_varzea,CO2_flux_reach_varzea

Border-SPO,R0,Jan,648,69,100,1.46,46,0.03,661,488,310,3.31,104,0.07

Border-SPO,R0,Feb,648,77,100,1.61,51,0.03,825,488,310,3.31,104,0.09

Border-SPO,R0,Mar,648,89,100,1.86,59,0.04,1120,488,310,3.31,104,0.12

...

Alvaraes,R8,May,296,95,84,2.38,75,0.02,2214,488,310,3.31,104,0.23

Alvaraes,R8,Jun,296,117,84,2.93,92,0.03,2489,488,310,3.31,104,0.26

Alvaraes,R8,Jul,296,147,84,3.69,116,0.03,2364,488,310,3.31,104,0.25

...

Obidos,R21,Oct,1332,169,58,6.11,192,0.26,3340,217,310,1.47,46,0.15

Obidos,R21,Nov,1332,131,58,4.74,149,0.2,2905,217,310,1.47,46,0.13

Obidos,R21,Dec,1332,86,58,3.13,99,0.13,2714,217,310,1.47,46,0.13

Data Application and Derivation:

CO2 evasion fluxes were calculated based on the gas transfer model, F = K* (Cs minus Co), where F is the evasive flux, Cs is the surface water concentration, Co is the atmospheric equilibrium, and K is the exchange coefficient. We determined K from direct measurements of O2 and 222Rn accumulation in free-floating chambers on the mainstem (K = 2.3 plus or minus 0. 9 m per d) and primary tributaries (K = 1. 2 plus or minus 0.5 m per d) and of CO2 and CH4 accumulation on the floodplain (K = 0.65 plus or minus 0.25 m per d)(Devol et al. 1987).

Quality Assessment (Data Quality Attribute Accuracy Report):

Quality Assessment:

Discussions of quality assessment and associated error for each component are included in the methods section below.



In brief they are summarized here:



Area coverage and inundation:

The uncertainty of the procedure was estimated using high-resolution airborne, digital videography (Hess et al 2002) to be plus or minus 5% at high water and plus or minus 10 to 15% at low water.



pCO2 concentrations

The standard deviation ranged from 16% to 37% of mean monthly values. Annual profiles for each tributary were similarly constructed, with assumed standard deviations of 40% for each month. For regions not directly sampled, profiles were used from the nearest neighbour with data, with assumed uncertainties of 80%.

Process Description:

Data Acquisition Materials and Methods:

Areal coverage of surface waters and flooding regime

Data from the Japanese Earth Resources Satellite-1 (JERS-1) L-band synthetic aperture radar were used to estimate the areal coverage and inundation status of rivers and floodplains over 100m in width. Data were compiled into mosaics for periods of high water (May through June 1996) and low water (October 1995)(Siqueira et al. 2000). For each mosaic, the study area was classified into either flooded or non-flooded areas based on radar backscatter intensities as delineated by image segmentation (Barbosa et al 2000), and was divided into 25 tributary subbasins from the river network. The uncertainty of the procedure was estimated using high-resolution airborne, digital videography (Hess et al 2002) to be plus or minus 5% at high water and plus or minus 10 to 15% at low water. To account for river corridors less than 100m in width, we computed an area density function by extending a geometric series relating stream length

and width to stream order from the river network for the whole basin, and applied it to the study area. Mean monthly stage data from multiyear hydrographic records within each tributary sub-basin (Richey et al. 2004) were used to estimate tributary flooding sequences by assuming a temporal correspondence between stage height and areal extent of inundation. For five sub-basins without gauging records, the normalized hydrograph for the nearest neighbor with similar climatology was used. The temporal sequence of inundation within the mainstem and its floodplain was computed from multi-year monthly composite Scanning Multichannel Microwave Radiometer (SMMR) data (Sippel et al 1998).



CO2 distributions

The seasonal and spatial distributions of pCO2 within each hydrographic region were described from over 1,800 samples taken on 13 expeditions at different water stages throughout a 2,000 km reach of the central Amazon mainstem, tributary, and floodplain waters (Degens et al 1991, Devol et al. 1995, Richey et al 1988). A ten-year time series (Devol et al. 1995) at the Marchantaria mainstem station gave a statistically robust picture of seasonal trends in pCO2. The standard deviation ranged from 16% to 37% of mean monthly values. Annual profiles for each tributary were similarly constructed, with assumed standard deviations of 40% for each month. For regions not directly sampled, profiles were used from the nearest neighbour with data, with assumed uncertainties of 80%. Floodplain measurements exhibited no obvious seasonal trends but a pronounced gradient from higher concentrations upriver to

intermediate and then lower concentrations downriver. Hence we aggregated results by up-, mid-, and downriver sections.



Gas evasion

We computed evasion from the gas transfer model, F = K* (Cs minus Co), where F is the evasive flux, Cs is the surface water concentration, Co is the atmospheric equilibrium, and K is the exchange coefficient. We determined K from direct measurements of O2 and 222Rn accumulation in free-floating chambers on the mainstem (K = 2.3 plus or minus 0. 9 m per d) and primary tributaries (K = 1. 2 plus or minus 0.5 m per d) and of CO2 and CH4 accumulation on the floodplain (K = 0.65 plus or minus 0.25 m per d)(Devol et al. 1987). Chambers have been criticized on the basis that they may inhibit wind shear and alter the near-surface turbulence, but we assume that in the generally low wind environments of the Amazon and with the internal turbulence of large rivers of considerable flow velocity (1 to 3m per s) this model yields a reasonable, if conservative, approximation of K. These values are comparable to values derived elsewhere not only with chambers but also with purposeful injections of inert gases, calculations with surface renewal models, and eddy covariance techniques (Cole et al. 2001, Clark et al. 1994, MacIntyre et al. 2001)

References:

Barbosa, C., Hess, L.,Melack, J. & Novo, E.Mapping Amazon Basin wetlands through region-growing segmentation and segmented-based classification of JERS-1 data. IX Latin Am. Symp. Remote Sensing (6 to10 November 2000) 1168 to 1176 (Universidad Nacional de Lujan, Puerto Iguazu, Argentina, 2000);

see also http://www.selper.org.



Clark, J. F., Wanninkhof, R., Schlosser, P. & Simpson, H. J. 1994. Gas exchange rates in the tidal Hudson River using a dual tracer technique. Tellus B 46, 264-285.



Cole, J. J. & Caraco, N. F. 2001. Carbon in catchments: Connecting terrestrial carbon losses with aquatic metabolism. Mar. Freshwat. Res. 52, 101-110.



Degens, E. T., Kempe, S. & Richey, J. E. (eds) 1991. Biogeochemistry of Major World Rivers 323-397 (Wiley,Chichester).



Devol, A. H., Forsberg, B. R., Richey, J. E. & Pimentel, T. P. 1995. Seasonal variation in chemical distributions in the Amazon (Solimoes) River: a multiyear time series. Glob. Biogeochem. Cycles 9, 307-328.



Devol, A. H., Quay, P. D., Richey, J. E. & Martinelli, L. A. 1987. The role of gas exchange in the inorganic carbon, oxygen and 222 radon budgets of the Amazon River. Limnol. Oceanogr. 32, 235-248.



Hess, L. L. E.M.L.M. Novo, D.M. Slaymaker, J. Holt, C. Steffen, D.M. Valeriano, L.A.K. Mertes, T. Krug, J.M. Melack, M. Gastil, C. Holmes & C. Hayward 2002. Geocoded digital videography for validation of land cover mapping in the Amazon Basin. Int. J. Remote Sensing DOI:10.1080/01431160110092687



MacIntyre, S., Eugster, W. & Kling, G. W. 2001. in Gas Transfer at Water Surfaces (eds Donelan, M. A., Drennan, W. M., Saltzman, E. S. & Wanninkhof, R.) 135-139 (American Geophysical Union, Washington).



Richey, J. E., Devol, A. H., Wofsy, S. C., Victoria, R. & Ribeiro, M. N. G. 1988. Biogenic gases and the oxidation and reduction of carbon in the Amazon River and floodplain waters. Limnol. Oceanogr. 33,551-561.



Richey, J. E., Victoria, R. L., Mayorga, E., Martinelli, L. A. & Meade, R. H. 2004. Integrated Analysis in a Humid Tropical Region- The Amazon Basin. Pages 415-428 in Vegetation, Water, Humans and the Climate(ed. Kabat, P. et al) Springer, Berlin.



Sippel, S. J., Hamilton, S. K., Melack, J. M. & Novo, E. M. 1998. Passive microwave observations of inundation area and the area/stage relation in the Amazon River floodplain. Int. J. Remote Sensing 19,3055-3074.



Siqueira, P. et al. 2000. A continental-scale mosaic of the Amazon Basin using JERS-1 SAR. IEEE Trans. Geosci. Remote Sensing 38, 2638â�â�œ2644.

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