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Investigation:

ND-01 (Roberts / Barreto / Soares)

LBA Dataset ID:

ND01_STREAM_CHEMISTRY

Originator(s):

1. BIGGS, T.W.
2. DUNNE, T.
      3. DOMINGUES, T.F.
4. MARTINELLI, L.A.

Point(s) of Contact:

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

Dataset Abstract:

These data were collected under the EOS Amazon project, 1998-1999, but are being provided for the archive to be included as part of the LBA collection.
We use a synoptic sampling of stream water to quantify the effect of soil type, rock type, deforestation extent determined by Landsat TM imagery, and urban population density on stream solute concentrations for 60 different watersheds in the dry season and 49 in the wet season in the southwestern Brazilian Amazon basin.

Beginning Date:

1998-08-02

Ending Date:

1999-01-28

Metadata Last Updated on:

2012-09-14

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 ND-01 Streamwater and Watershed Characteristics, Rondonia, Brazil: 1998-1999 :  http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1119

Documentation/Other Supporting Documents:

LBA-ECO ND-01 Streamwater and Watershed Characteristics, Rondonia, Brazil: 1998-1999 :  http://daac.ornl.gov/LBA/guides/ND01_Stream_Chemistry.html

Citation Information - Other Details:

Biggs, T.W., T. Dunne, T.F. Domingues, and L.A. Martinelli. 2012. LBA-ECO ND-01 Streamwater and Watershed Characteristics, Rondonia, Brazil: 1998-1999. 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/1119

Keywords - Theme:

Parameter Topic Term Source Sensor
BIOGEOCHEMISTRY BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION ANALYSIS
CALCIUM BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION ANALYSIS
CHLORIDE BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION ANALYSIS
DISSOLVED SOLIDS BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION ANALYSIS
POTASSIUM BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION ANALYSIS
SEDIMENT CHEMISTRY BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION ANALYSIS
SEDIMENT TRANSPORT BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION ANALYSIS
SODIUM BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION ANALYSIS
SULFATE BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION ANALYSIS
WATER ION CONCENTRATION BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION ANALYSIS
WATERSHED CHARACTERISTICS BIOSPHERE TERRESTRIAL ECOSYSTEMS FIELD INVESTIGATION LANDSAT TM (LANDSAT THEMATIC MAPPER)

Uncontrolled Theme Keyword(s):  LITHOLOGY, LYSIMETERS, SECONDARY FOREST, STREAM WATER, TROPICAL FORESTS, WATERSHEDS

Keywords - Place (with associated coordinates):

Region
(click to view profile)
Site
(click to view profile)
North South East West
  BRAZILIAN AMAZON -8.00000 -12.63000 -60.70100 -64.43000

Related Publication(s):

Biggs, T.W., T. Dunne, T.F. Domingues, and L.A. Martinelli. 2002. Relative influence of natural watershed properties and human disturbance on stream solute concentrations in the southwestern Brazilian Amazon basin. Water Resources Research 38(8).

Data Characteristics (Entity and Attribute Overview):

Data Characteristics:

Data are provided in three ASCII comma-separated files:

File #1: ND01_Watershed_Characterization_Rondonia.csv

File #2: ND01_Dry_season_Stream_solutes_Rondonia.csv

File #3: ND01_Wet_season_Stream_solutes_Rondonia.csv



Filename: ND01_Watershed_Characterization_Rondonia.csv

Data contact: Trent W. Biggs

LBA Dataset ID: ND01_Stream_Chemistry



Column,Column_heading,Units/format,Description

1,Watershed_ID,,Watershed identification code. F indicates forested watersheds used for BKG regressions

2,Latitude,decimal degrees,Sampling point latitude in decimal degrees

3,Longitude,decimal degrees,Sampling point longitude in decimal degrees

4,Area, km2,Watershed area in square kilometers

5,Defor,%,Percent of watershed area classified as deforested

6,Urban,persons per km2,Number of persons living in urban areas in the watershed divided bytotal watershed area.

7,Na,kmol/ha,Soil cation contents - Sodium in kmol/ha upper 1.3 m

8,Ca,kmol/ha,Soil cation contents - Calcium in kmol/ha upper 1.3 m

9,Mg,kmol/ha,Soil cation contents - Magnesium in kmol/ha upper 1.3 m

10,K,kmol/ha,Soil cation contents -Potassium in kmol/ha upper 1.3 m

11,TZ,kmol/ha,Soil exchangable cation content calculated as the sum of Na, Ca, Mg and K contents

12,Soil_pH,pH units,Soil pH

13,AR,,Fraction of watershed area consisting of rock type: arenties (AR)

14,TS,,Fraction of watershed area consisting of rock type: tertiary sediments (TS)

15,GN,,Fraction of watershed area consisting of rock type: gneiss (GN)

16,GR,,Fraction of watershed area consisting of rock type: granite (GR)

17,BSC,,Fraction of watershed area consisting of rock type: ultramafic rock

18,CLC,,Fraction of watershed area consisting of rock type: calcareous shale (CLC)

19,MS,,Fraction of watershed area consisting of rock type: mica schist.



Example data from File #1:ND01_Watershed_Characterization_Rondonia.csv

Watershed_ID,Latitude,Longitude,Area,Defor,Urban,Na,Ca,Mg,K,ANC,Soil_pH,AR,TS,GN,GR,BSC,CLC,MS

F1,-9.242,-64.326,834,2,0,2.3,41,19,9,72,4.5,0.13,0,0.01,0.87,0,0,0

F2,-9.188,-62.948,279,4,0,2,45,21,12,80,4.5,0,0,0.58,0.42,0,0,0

F3,-10.383,-63.137,80,5,0,3.4,510,137,39,689,5.6,0,0,0.98,0.02,0,0,0

F4,-12.339,-60.745,113,7,0,1.8,37,14,5,58,4.7,1,0,0,0,0,0,0

F5,-12.42,-60.803,191,7,0,1.9,83,25,8,118,4.8,1,0,0,0,0,0,0

F6,-12.375,-60.762,119,7,0,2,48,24,8,82,4.7,1,0,0,0,0,0,0

F7,-9.188,-62.936,1023,10,0,1.9,46,21,12,81,4.5,0,0,0.56,0.44,0,0,0

F8,-11.968,-60.701,3268,11,0,2,39,16,6,63,4.6,0.9,0.1,0,0,0,0,0

F9,-10.386,-63.069,516,13,0,3.2,485,127,38,652,5.6,0,0,0.81,0.19,0,0,0

F10,-12.014,-60.859,161,14,0,1.7,36,12,5,55,4.7,1,0,0,0,0,0,0

F11,-8.799,-63.716,12538,11,4,3.2,80,33,12,129,4.6,0.02,0.11,0.4,0.46,0,0.01,0







Filename: ND01_Dry_season_Stream_solutes_Rondonia.csv

Data contact: Trent W. Biggs

LBA Dataset ID: ND01_Stream_Chemistry





Column,Column_heading,Units/format,Description

1,Watershed_ID,,Watershed identification code

2,Sample_date,YYYYMMDD,Sampling date

3,Latitude,decimal degrees,Latitude of sampling location in decimal degrees: negative values indicate S

4,Longitude,decimal degrees,Longitude of sampling location in decimal degrees: negative values indicate W

5,Na,uM,Streamwater sodium concentration in micromoles per liter (uM)

6,Ca,uM,Streamwater calcium concentration in micromoles per liter (uM)

7,Mg,uM,Streamwater magnesium concentration in micromoles per liter (uM)

8,K,uM,Streamwater potassium concentration in micromoles per liter (uM)

9,Si,uM,Streamwater silica concentration in micromoles per liter (uM)

10,Cl,uM,Streamwater chloride concentration in micromoles per liter (uM)

11,SO4,uM,Streamwater sulfate concentration in micromoles per liter (uM)

12,ANC,ueq per L,Streamwater acid neutralizing capacity measured via titration and reported in microequivalents per liter

13,pH,,Streamwater pH



,Missing data are represented by -9999



Example date for File #2: ND01_Dry_season_Stream_solutes_Rondonia.csv

Watershed,Sample_date,Latitude,Longitude,Na,Ca,Mg,K,Si,Cl,SO4,ANC,pH

F1,19980819,-9.242,-64.326,-9999,3,2.1,6.2,12.9,5.1,4.1,36.9,5.8

F2,19980821,-9.188,-62.948,11.1,3.1,2.7,5.6,2.2,5.5,2,26.5,-9999

F3,19980803,-10.383,-63.137,145.8,55.7,43.5,96,342.3,1.2,2.1,406.2,7.1

F4,19980807,-12.339,-60.745,12.8,4.4,3.7,10.9,3.4,3.7,3.3,27.2,6.3

F5,19980808,-12.42,-60.803,38.5,25,28,20.1,90.3,5.7,6.3,156.6,6.7

F6,19980808,-12.375,-60.762,15.6,5.6,5.5,19.6,7,5.3,2.4,48.3,6.1

F7,19980821,-9.188,-62.936,23.2,16.5,10.3,21.3,5.1,9.6,1.7,94.1,-9999

F8,19980807,-11.968,-60.701,14.3,3.5,1,4.2,3.7,3.1,2.9,29.8,6.6

F9,19980803,-10.386,-63.069,129.1,81.7,49,84.8,298.2,15.5,4.2,461.4,7

F10,19980807,-12.014,-60.859,14.7,2.2,19,15.9,2.7,5.6,2.8,24.2,6.4

F11,19980823,-8.799,-63.716,31.5,12.8,7,20.8,81.4,6.2,4.2,94.5,6.1

F12,19980819,-9.259,-64.389,-9999,13.1,8.3,4.1,118,5.2,8.2,105.8,6.7





Filename: ND01_Wet_season_Stream_solutes_Rondonia.csv

Data contact: Trent W. Biggs

LBA Dataset ID: ND01_Stream_Chemistry





Column,Column_heading,Units/format,Description

1,Watershed_ID,,Watershed identification code

2,Sample_date,YYYYMMDD,Sampling date

3,Latitude,decimal degrees,Latitude of sampling location in decimal degrees: negative values indicate S

4,Longitude,decimal degrees,Longitude of sampling location in decimal degrees: negative values indicate W

5,Na,uM,Streamwater sodium concentration in micromoles per liter (uM)

6,Ca,uM,Streamwater calcium concentration in micromoles per liter (uM)

7,Mg,uM,Streamwater magnesium concentration in micromoles per liter (uM)

8,K,uM,Streamwater potassium concentration in micromoles per liter (uM)

9,Si,uM,Streamwater silica concentration in micromoles per liter (uM)

10,Cl,uM,Streamwater chloride concentration in micromoles per liter (uM)

11,SO4,uM,Streamwater sulfate concentration in micromoles per liter (uM)

12,ANC,ueq per L,Streamwater acid neutralizing capacity measured via titration and reported in microequivalents per liter

13,pH,,Streamwater pH



,Missing data are represented by -9999



Example date for File #3: ND01_Wet_season_Stream_solutes_Rondonia.csv

Watershed,Sample_date,Latitude,Longitude,Na,Ca,Mg,K,Si,Cl,SO4,ANC,pH

F1,19990208,-9.242,-64.326,9.9,4.4,1.8,2.3,11.7,2.4,2.6,36.3,-9999

F5,19990201,-12.42,-60.803,20.1,24.3,31.7,37.4,190.2,6,1.8,156.1,-9999

F6,19990201,-12.375,-60.762,7.2,3.1,2.7,5.2,31.4,5,1.1,38.7,-9999

F7,19990206,-9.188,-62.936,10,3.3,6.2,11.3,24.4,2.7,1.6,55.7,-9999

F8,19990202,-11.968,-60.701,7.7,7.8,5.4,20.5,33.5,3.9,1.3,41.7,-9999

F9,19990124,-10.386,-63.069,86.1,53.5,27,63,271.5,7.8,2.5,245,6.8

F10,19990202,-12.014,-60.859,6.2,4.3,3.8,20.4,25,4.4,0.8,22.8,-9999

F11,19990123,-8.799,-63.716,10.3,15.3,10.1,28.9,49.8,4.8,2.3,74.6,6

F12,19990208,-9.259,-64.389,41.8,16,11.3,14.4,-9999,4.1,3.6,-9999,-9999

F13,19990205,-10.118,-63.175,66,37,20.8,34.6,303.6,6.4,2.6,235,-9999

F14,19990127,-11.196,-62.852,31.4,10,9,19.4,75.2,2.5,2.9,99.1,6.3

F15,19990208,-8.074,-62.895,10.1,6,3.5,2.5,24.8,2.9,3.7,22,-9999

17,19990208,-9.31,-64.43,10,4.9,1.8,2.4,19.8,2.3,4.6,17.6,-9999

Data Application and Derivation:

These data in combination with rainfall and streamflow data provide essential information to help quantify the effect of soil type, rock type,

deforestation extent and urban population density on nutrient dynamics.

Quality Assessment (Data Quality Attribute Accuracy Report):

Quality Assessment:

Eighty-seven percent of dry season samples and 76% of wet season samples had <10% error in cation-anion balance, and samples in both seasons had high correlation between total cations and total anions (r2 = 0.98 dry season, 0.94 wet season).

Process Description:

Data Acquisition Materials and Methods:

Field site:

The Brazilian State of Rondonia lies in the southwestern Amazon basin on the Brazilian craton, which has a basement of pre-Cambrian gneiss. Plutons dominated by biotite-amphibole granites, quartz syenites and quartz monzonites intrude into the craton throughout the state\'s center (27% of the sampled

catchments area). Tertiary sediments overlie the craton in the north. In the southeastern part of the state, carbonate shale with interbedded sandstone covers 3.5% of the study area, and white quartz sandstone with no carbonates cover 20% [CPRM 1997]. Mica-schist and localized intrusions of gabbro cover 3.7% and 2.8% of the study area, respectively, also in the southeast. The Tertiary sediments form a dissected plain, with elevations between 60 and 160 m. On the

craton, topography is gently undulating (average slopes 2 to 5%) with occasional rocky hills and small massifs up to 600m in elevation [RADAMBRASIL, 1978]. Hillslopes range between 590 to 1200 m long [Ballantine, 2001], which is typical of humid tropical areas with low relief and dense vegetation cover [Moglen et al., 1998].



Soil types in the state include Oxisols (as described by Natural Resources Conservation Service (NRCS)[1999]), Latossolo distrofico in the Brazilian Soil Classification System, [Camargo et al., 1987]), Entisols (Solos Aluvias Distroficos) and Inceptisols (Cambissolos) in the north on the Tertiary sediments. Oxisols, Ultisols (Podzolico distrofico) and Alfisols (Solos eutroficos) occur on the craton, and Entisols (Areias Quartzosas Distroficas) on white quartz sands in the southeast [EMBRAPA, 1983].



Rainfall in the study area averages 1930 to 2690 mm/yr with a distinct wet season lasting from October to April, and average runoff ranges from 563 to 926 mm/yr. The streams of the state are dilute, with total cations ranging from 126 to 243 meq/L for the Jamari and Jiparana rivers [Mortatti et al., 1992], compared to 200 to 450 meq/L for other streams on siliceous terrain in the Amazon basin and up to 422 meq/L for the Amazon main stem at Obidos [Stallard,1983]. Dissolved silicon and bicarbonate comprise between 74 and 80% of total dissolved solids by mass. Calcium and sodium are the dominant cations, ranging between 26 and 35% (Ca) and 22 and 39% (Na) of total cations on an equivalent basis [Mortatti et al., 1992].



The undisturbed vegetation includes dense tropical rain forest (Floresta Densa, 17% of Rondonia state area) similar to that found in the central Amazon basin and open moist tropical forest (Floresta Ombrofila Aberta, 61% of state area), which is often dominated by palms and has a more open canopy than dense tropical rain forest [RADAMBRASIL,1978]. Savannas are present but limited, covering up to 5 to 8% of 3 catchments in the southeast.



The first modern wave of colonization in Rondonia began in the early 1970s. By 1998, 53,275 km2, or 22% of the Stateâ�ââ�žÂ¢s area had been deforested, representing 9.6% of the deforested area of the Amazon Basin [INPE, 2000]. Land use has been dominated by replacement of forest with grassland for cattle ranching[Pedlowski et al., 1997]. Up to 50% of the cleared area is in some stage of regrowth [Pedlowski et al., 1997; Rignot et al., 1997]



Sampling



Stream Samples

Stream water samples were collected at 60 different sites in the dry season (August 1998) and at 49 different sites in the wet season (late January through early February 1999). Each stream was sampled only once along its course, so each watershed represents an independent sample. The pH and conductivity were measured on the unfiltered samples using an Orion 250A pH meter and an

Orion 115 conductivity meter. The samples were then filtered in the field with Gelman GFF 0.7 um filters, kept at 4 degrees C and then frozen prior to transport from the state for analysis. Cations were analyzed by flame atomic absorption spectrometry (Varian model AA6), dissolved silica by the colorimetric acid-molybdate method, acid-neutralizing capacity (ANC) by Gran-titration [Stumm and Morgan,1981], and chloride, nitrate and sulfate by ion chromatography (Dionex model DX500).



Watershed Properties

Watershed boundaries were digitized into a geographic information system using 1:100,000 scale topographic maps and the coordinates of collection points recorded in the field with a global positioning system. Land use was determined from a mosaic of eight Landsat Thematic Mapper (TM) images from 1996 classified using spectral mixture analysis (SMA) as described by Roberts et al. [1998]. Spectral end-members for soil, shade, nonphotosynthetic vegetation, and green vegetation were selected from the image to generate end-member fraction

images. Training areas were then selected to develop a decision classification tree that used end-member fraction values to assign pixels to one of five categories: pasture, regenerating forest, mature forest, urban/bare and water.

Natural grasslands were classified manually via image interpretation. Due to the difficulty of spectrally separating pasture from regenerating vegetation, the designation \'deforested\' for this study includes both pasture and

regenerating vegetation. This definition represents a complex mosaic of clearings of different ages and regenerating forest in various stages of regrowth as recognized by SMA and includes no information about the successional status of vegetation in the watershed.



Soil exchangeable cation contents were calculated for each watershed from digitized soil maps and soil profile analyses from the Sigteron project [Cochrane, 1998]. The methodology used in the Sigteron project delineates soil terrain units that contain \'a distinctive, often repetitive, pattern of landform, lithology, surface form, slope, parent material, and soil.\' [FAO, 1993] Each soil-terrain unit is assigned multiple soil types and the percentage cover of each soil type within the unit. The soil exchangeable cation content for a given watershed and cation is calculated as a weighted average of the soil exchangeable cation contents for each soil type



The percent of each watershed covered by each of 24 different lithologies was calculated using a 1:1,000,000 geologic map from CPRM [1997]. The 24 different rock types were aggregated into groups of pre-Cambrian gneiss, biotite-amphibole granitic intrusions, carbonate shale, arenitic sandstone with no carbonates, Tertiary sediments, mica-schist, and mafic rocks. These groups were further aggregated into acid lithology (gneiss, granite, sandstone, Tertiary sediments) and basic lithology (mica-schist, mafic rocks, and carbonate shale).



Urban population density was calculated as the number of persons living in urban areas in the catchment divided by watershed area to yield urban population/km2. The urban population included all persons living in areas

designated as urban by the IBGE in the 1996 census.

References:

Ballantine, J. A. 2001. The response of groundwater flow to topography and

deforestation in humid tropical regions, M.A. thesis, Department of Geography,

Univ. of Calif., Santa Barbara.



Camargo, M. N., E. Klamt, and J. H. Kauffman,. 1987. Sistema Brasileiro de

Classificacao de Solos, Separata B. Inf. Soc. Bras. Ci. Solo Campinas,

12: 11-33.



CPRM.1997. Mapa Geologico do Estado de Rondonia, Ministerio de Minas e Energia, Porto Velho,Brazil.



EMBRAPA. 1983. Mapa de Levantamento de Reconhecimento de Media Intensidade dos Solos do Estado de Rondonia, Porto Velho, Brazil.



INPE. 2000. Monitoring of the Brazilian Amazonian forest by satellite, 1998-1999, Sao Jose dos Campos,Brazil.



Moglen, G. E., E. A. B. Eltahir, and R. L. Bras, 1998. On the sensitivity of drainage density to climate change, Water Resour. Res., 34: 855-862.



Mortatti, J., J. L. Probst, and J. R. Ferreira. 1992. Hydrological and geochemical characteristics of the Jamari and Jiparana River basins (Rondonia, Brazil), GeoJ., 26: 287-296.



NRCS. 1999. Soil Taxonomy: A Basic System of Soil Classification for Making and Interpreting Soil Surveys, 2nd ed., U.S. Dep. of Agric., Washington, D.C.



Pedlowski, M. A., V. H. Dale, E. A. T. Matricardi, and E. P. da Silva Filho. 1997. Patterns and impacts of deforestation in Rondonia, Brazil, Landscape

Urban Plann., 38: 149-157.



RADAMBRASIL. 1978. Levantamento de recursos naturais, Ministerio das

Minas e Energia, Dep. Nac. de Producao Miner., Rio de Janeiro, Brazil.



Rignot, E., W. A. Salas, and D. L. Skole.1997. Mapping deforestation and

secondary growth in Rondonia, Brazil, using imaging radar and thematic

mapper data, Remote Sens. Environ., 59: 167-179.



Stallard, R. F. 1983. Geochemistry of the Amazon, 2, The influence of geology

and weathering environment on the dissolved load, J. Geophys. Res., 88: 9671-9688,

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