Some Uses of Channel Bed Sediment Concentration Data - PowerPoint PPT Presentation

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Title: Some Uses of Channel Bed Sediment Concentration Data


1
Some Uses of Channel Bed Sediment Concentration
Data
  • Determine the spatial distribution of trace
    metals
  • Identify point and non-point sources of pollution
  • Assessment of the rates and patterns of
    contaminant dispersal
  • First approximation of potential ecological and
    human health effects (and regional water quality
    surveys)
  • Monitoring of potential impacts of waste waters
    from industrial or municipal sites
  • Geochemical exploration (surveys)

2
Downstream Trends in Channel Bed
From Salomons Forstner, 1984
  • Where point sources are present the
    concentrations generally decline from the point
    of input.

3
Concentrations of Cu and Ni in the lt63 um
fraction of channel bed sediments from the Po
River, Italy. Samples were collected in the
summer (grey bars) and winter (black bars).
Acronyms along x-axis represent successive
downstream sampling sites. Note minimal
variations in concentration between seasons.
Viganò, L., and 14 others, 2003. Quality
assessment of bed sediments of the Po River
(Italy). Water Research, 37501-518. (from 2 of 8
graphs from figure 3, page 507)
4
Downstream Trends in Channel Bed
From Salomons Forstner, 1984
  • Where point sources are present the
    concentrations generally decline from the point
    of input.

5
Scale Characteristic
Transitory deposits Micro-forms Meso-forms Bedload temporarily at rest Coherent structures such as ripples with ? ranging from 10-2 to 100 m Features with ? from 100 to 102 m includes dunes, pebble clusters and transverse ribs
Alluvial bars Macro-forms Mega-forms From by lag deposition of coarse-grained sediment Structures with ? from 101 to 103 m such as riffles, point bars, alternate bars, and mid-channel bars Structures with ? gt 103 m such as sedimentation zones
Characteristics of channel deposits (adapted from
Knighton 1998 Church and Jones 1982 Hoey 1992)
6
Figure from Huggett, J.R., 2003. Fundamental of
Geomorphology, Routledge Fundamentals in Physical
Geography, Routledge, London, fig. 7.7, p. 185.
7
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8
From Markham, A.J. and Thorne, C.R., 1992.
Geomorphology of gravel-bed river bends. In P.
Billi, R.D. Hey, C.R. Thorne, and P. Tacconi,
(eds.), Dynamics of Gravel-bed Rivers, pp.
433-456, New York, Jonh Wiley and Sons, Ldt.,
figure 22.2, p. 436.
9
From Thompson, A., 1986. Secondary Flows and the
Pool-Riffle, Earth Surface Processes and
Landforms, 11631-641., Figure 4, p. 636.
10
Reading, H.G., 1978. Sedimentary Environments and
Facies, Blackwell Publications, New York, Fig.
3.26, page 34. Company may have been purchased
by Elsevier?
11
Figure 20. Laremie River, Wyoming (photo by J.R.
Balsley) obtained from USGS Photo Library
12
Knighton, D., 1998. Fluvial Form and Processes A
New Perspective, Arnold, London. Fig. 5.23, p.
233.
13
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14
Grain-Size Compositional Variations
  • Ladd et al. 1998
  • Examined trace metal concentrations in 7
    morphological units in Soda Butte Creek, Montana
  • (lateral scour pools, eddy drop zones, glides,
    low gradient riffles, high gradient riffles,
    attached bars, and detached bars)
  • Highest concentrations in eddy drop zones and
    attached lateral bars with largest amount of fine
    sediment

15
Density-Dependent Variations
  • Slingerland and Smith (1986) define a placer as
    a deposit of residual or detrital mineral grains
    in which a valuable mineral has been concentrated
    by a mechanical agent,
  • A contaminant placer is defined here as a
    concentration of metal enriched particles by the
    hydraulic action of the river. Where they occur,
    trace metal concentrations will be locally
    elevated in comparison to other areas (Miller
    Orbock Miller, 2007)

16
Guilbert, J.M. and Park, C.F., Jr., 1986. The
Geology of Ore Deposits. New York, W.H. Freemand
and Company, figures 16-1, p. 746 and 16-4b p.749.
17
Bateman, A.M., 1950. Economic mineral deposits,
2nd edition. New York, Wiley and Sons.
18



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19
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20
Eureka Mill, Brunswick Canyon
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24
Variations Dependent on Time and Frequency of
Inundation
  • Examples
  • Queens Creek, Arizona
  • Rio Pilcomayo, Bolivia

25
Graf, W.L., Clark, S.L., Kammerer, M.T., Lehman,
T., Randall, K., Tempe, R., and Schroeder, A.,
1991. Geomorphology of heavy metals in the
sediments of Queen Creek, Arizona, USA. Catena,
18567-582, figures 2, p. 572 and 6, p. 578.
26
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27
Floatation Process
Modern Mine
Pb Zn Concentrate
Ball Mill
28
Sampling Site RP-1 1.5 miles from Mills
Floatation Mill, Potosi
Effluent
You want me to live where?
20 miles from Mills
29
60 miles from Mills
20 miles from Mills
30
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31
Rio Pilcomayo, southern Bolvia near Uyuni. Photo
taken in July during the dry season.
32
Implications to Sampling
  • Local variations referred to as small scale or
    field variance (Birch et al. 2001)
  • Can be on the order of 10 to 25 relative
    standard deviation and may be significantly
    greater than analytical variation (error)
  • May hinder ability to decipher differences in
    contaminant levels between sample sites
  • Reconnaissance level surveys and sample
    stratification by morphological units ?
  • Sampling of specific units only?
  • Composite sampling to minimize within unit
    variations

33
Changes in Sediment Composition Can
  • Influence the spatial and temporal concentration
    patterns observed in aquatic systems
  • Hinder the determination of localized inputs of
    trace metals from either natural sources (e.g.,
    ore bodies) or anthropogenic sources (e.g.,
    mining operations or industrial complexes).
  • Changes in grain-size have a particularly
    significant influence on metal concentrations.

34
Types of Mathematical Manipulations Commonly
Applied to Bulk Metal DataAfter Horowitz, 1991
  • Corrections for Grain-size differences
  • Normalization to a single grain-size range
  • Carbonate content corrections
  • Recalculation of concentration data on a
    carbonate-free basis
  • Normalization to a conservative elemental
  • Use of multiple Normalizations

35
Methods of Handling the Grain Size Effect
  • Analysis of a specific grain-size fraction which
    is considered to be the chemical active phase
  • Does not provide for an understanding of the
    actual concentrations that exist in the bulk
    sample
  • Inhibits the calculation of total trace metal
    transport rates
  • Normalize the metal concentration data obtained
    for the bulk (lt 2mm or sand) sized fraction using
    some form of mathematical equation and grain size
    data obtained from a separate sample
  • Provides actual concentration found in bulk
    sample
  • Poorly documents the concentrations that would
    actually be measured in the finer-grain size
    fractions

36
Designation of Chemical Active Sediment Phase
  • Numerous size fractions have been used as the
    chemical active phase including lt2 µm, lt16 µm,
    lt20 µm, lt63 µm, lt70 µm, lt155 µm, lt200 µm
    (Horowitz, 1991)
  • Argument for using lt 63 µm fraction
  • It can be extracted from the bulk sample via
    sieving, a process which does not alter trace
    metal chemistry
  • It is the particle size most commonly carried in
    suspension by rivers and streams and may
    therefore be the most readily distributed through
    the aquatic environment

37
Grain Size Normalization
  • Normalized
  • Concentration


(DF Bulk Metal Concentration)
Where, DF Dilution Factor 100/(100 - of
sediment gt size range of Interest)
38
Concentration vs. Quantity of Fine Sediment
  • Sizes Frequently Used
  • 2 µm
  • 16 µm
  • 62.5 µm
  • 63 µm
  • 70 µm
  • 125 µm
  • 200 µm

Data from deGroot et al., 1982
39
Data from Horowitz and Elrik, 1988
40
Differences between Measured and Normalized Values
  • Selected chemical active phase (grain size
    fraction) may not contain all of the trace metals
  • Differences in concentration are not solely due
    to grain size variations
  • Data contain analytical errors associated with
    grain size or geochemical analyses

41
Concentration Concentration Concentration Percent Contribution Percent Contribution
Constituent (mg/kg) lt63 µm fraction gt63 µm fraction Total Sample lt63 µm fraction gt63 µm fraction
Arkansas River (sampled 5/11/87)a,b Arkansas River (sampled 5/11/87)a,b Arkansas River (sampled 5/11/87)a,b Arkansas River (sampled 5/11/87)a,b Arkansas River (sampled 5/11/87)a,b
Mn 1100 600 800 50 50
Cu 51 22 33 58 42
Zn 325 110 190 63 37
Pb 52 25 35 54 46
Cr 56 44 49 43 57
Ni 32 16 22 55 45
Co 15 11 12.5 45 55
Cowlitz River (sampled 4/20/87)a,c Cowlitz River (sampled 4/20/87)a,c Cowlitz River (sampled 4/20/87)a,c Cowlitz River (sampled 4/20/87)a,c Cowlitz River (sampled 4/20/87)a,c
Mn 650 670 660 40 60
Cu 63 33 46 57 43
Zn 62 68 59 42 58
Pb 12 10 10.8 45 55
Cr 35 19 25 56 44
Ni 25 16 19 53 47
Co 14 14 14 41 59
aThe represents the mean of the initial and final composite samples obtained at these sampling sites. blt63 µm fraction equaled 37 , gt63 µm fraction equaled 63 , c lt63 µm fraction equaled 41 , gt63 µm equaled 59 . aThe represents the mean of the initial and final composite samples obtained at these sampling sites. blt63 µm fraction equaled 37 , gt63 µm fraction equaled 63 , c lt63 µm fraction equaled 41 , gt63 µm equaled 59 . aThe represents the mean of the initial and final composite samples obtained at these sampling sites. blt63 µm fraction equaled 37 , gt63 µm fraction equaled 63 , c lt63 µm fraction equaled 41 , gt63 µm equaled 59 . aThe represents the mean of the initial and final composite samples obtained at these sampling sites. blt63 µm fraction equaled 37 , gt63 µm fraction equaled 63 , c lt63 µm fraction equaled 41 , gt63 µm equaled 59 . aThe represents the mean of the initial and final composite samples obtained at these sampling sites. blt63 µm fraction equaled 37 , gt63 µm fraction equaled 63 , c lt63 µm fraction equaled 41 , gt63 µm equaled 59 . aThe represents the mean of the initial and final composite samples obtained at these sampling sites. blt63 µm fraction equaled 37 , gt63 µm fraction equaled 63 , c lt63 µm fraction equaled 41 , gt63 µm equaled 59 .
Fractional Contributions of Selected Metals in
Suspended Sediments
(modified from Horowitz et al., 1990)
42
Carbonate Correction
  • Assumes Carbonate does not contain substantial
    quantities of trace metals and, thus, acts as a
    diluent. May not be true of Cd and Pb.
  • Generally applied to streams in calcareous
    terrains, particularly those in areas with karst.

Where, DF Dilution Factor 100/(100 - of
carbonate in sample)
43
Conservative Element Corrections
  • Assumes that some elements have had a uniform
    flux from crustal rocks. Thus, normalization to
    these elements provides a measure (or level) of
    dilution that has occurred.
  • Elements most commonly used are Al, Ti, and to a
    lesser extent, Cs and Li.
  • Normalized
  • value (Concentration of
    Trace Metal)
  • (Concentration of
    conservative element)

Note this generates a ratio, not a concentration
as did the previous procedures
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