A quantitative comparative study to investigate aggradation rate as a predictor of fluvial architecture: implications for fluvial sequence stratigraphy - PowerPoint PPT Presentation

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A quantitative comparative study to investigate aggradation rate as a predictor of fluvial architecture: implications for fluvial sequence stratigraphy

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Title: A quantitative comparative study to investigate aggradation rate as a predictor of fluvial architecture: implications for fluvial sequence stratigraphy


1
A quantitative comparative study to investigate
aggradation rate as a predictor of fluvial
architecture implications for fluvial sequence
stratigraphy
  • Luca Colombera, Nigel P. Mountney, William D.
    McCaffrey

Fluvial Eolian Research Group University of
Leeds
2
Alluvial architecture models
Allen (1978)
LAB (Leeder-Allen-Bridge) models describing
large-scale fluvial architecture in terms of
channel belts distributed in floodplain
background. Fundamental implication with
supposed predictive value channel-body density
is inversely correlated to aggradation rate,
hence controlling channel-deposit connectedness
and geometries.
subsidence rate
Bridge Leeder (1979)
Allens (1978) model did not consider aggradation
rate as a predictor of sedimentary architecture.
Following models did.
3
Fluvial sequence stratigraphy models
Wright Marriott (1993)
LAB model relationship between channel density
and aggradation incorporated in continental
Sequence Stratigraphy concepts, models and
practice.
  • RSL-based systems tracts
  • informal accommodation-based
  • systems tracts
  • accommodation-based settings

4
Alluvial architecture models limitations
Bryant et al. (1995)
LAB models do not consider the complex manner in
which several controls may interplay in
determining variations in fluvial channel-body
proportions and geometries (e.g. role of
aggradation rate as a control on avulsion
frequency concurrent variation in channel
avulsion and mobility with changes in
aggradation).
Bristow Best (1993)
Some scale models contradict LAB model
predictions concerning aggradation rate and
channel density.
5
Comparative study overview
SCOPE investigate relationships between
deposystem aggradation rates (and its temporal
variations) and large-scale fluvial sedimentary
architecture (and its temporal
variations). METHOD comparative study of
large-scale sedimentary architecture of several
fluvial successions for which constraints on
overall aggradation rate are available.
6
FAKTS database
Relational database for the digitization of the
sedimentary and geomorphic architecture of
classified fluvial systems. Stored data include
types, geometries, spatial relationships and
hierarchical relationships of three order of
genetic units. Here, focus is on large-scale
depositional elements.
after Colombera et al. (2012)
7
Data Entry
Depositional elements classified as
channel-complex or floodplain element, and
distinguished geometrically. Published summary
data also included.
8
Database output
? GENETIC-UNIT PROPORTIONS
GENETIC-UNIT GEOMETRIES ?
? GENETIC-UNIT SPATIAL RELATIONSHIPS
? SYSTEM SPATIAL/TEMPORAL
EVOLUTION
9
Database method limitations
  • geometrical approach to the definition of
    channel complexes (not representing
    inter-avulsion channel belts)
  • common lack of 3D control for element
    definition
  • source works having variable cut-offs of size of
    smallest mappable units
  • necessity to include also summary data (e.g.
    channel-complex W/T scatterplot)
  • common lack of control on down- and cross-system
    variability
  • simplistic qualitative classification in
    proximal-distal framework, or case-specific
    quantification
  • subset attributes referring to average
    conditions through time, even over different time
    scales.

10
Results channel-complex proportions
  • Cases for which temporal evolution is tracked
  • Omingonde Fm. (Holzförster et al., 1999)
  • Chinji Fm.
  • (McRae, 1990)
  • Blackhawk Fm.
  • (Hampson et al., 2012)
  • Price River/North Horn Fm.
  • (Olsen, 1995)
  • No system displays a temporal evolution in
    agreement with LAB model predictions
  • a weak positive relationships between mean
    aggradation rate and channel-complex proportion
    is observed across all case studies.

11
Results channel-complex geometries
  • Channel-complex maximum thickness considered
    width distributions include real cross-stream
    widths, uncorrected apparent widths and
    incompletely observed widths
  • no clear trend is observed between the central
    tendency or dispersion of channel-complex
    thickness and the mean aggradation rates of the
    stratigraphic volume
  • although a positive trend between
    channel-complex median width and mean aggradation
    rate is seen, this is not statistically
    significant.

12
Results channel-complex geometries
  • Five out of six temporal changes show a positive
    relationship between changes in channel-complex
    thickness and changes in average aggradation rate
  • the same temporal changes show a positive
    relationship between changes in channel-complex
    width and changes in average aggradation rate
  • evolution likely related to effect of
    channel-body clustering.

13
Results channel-complex geometries
Correction on empirical relationships linking
proportions with geometries to consider effect of
channel clustering
  • Lack of any significant relationship between
    aggradation rates and channel-complex normalized
    geometrical parameters, when these two parameters
    are considered together.

14
Results channel-complex connectivity
  • No particular relationship is seen between the
    mean or maximum connected thickness and the mean
    aggradation rate, when evaluated across different
    systems
  • a positive relationship between variations in
    mean connected thickness and mean aggradation
    rate are observed within systems for which
    evolution is tracked.

15
Results channel-complex spacing
  • A weak positive relationship is seen between
    mean channel-complex spacing and mean aggradation
    rate, but it is not statistically significant
  • negative relationships between variations in
    mean channel-complex spacing and mean aggradation
    rate are observed within systems for which
    evolution is tracked.

16
Discussion
  • Lack of agreement on the univocal definition of
    the concept of subaerial accommodation space
  • problems overlook of its three-dimensional
    character, or the consideration of it as a pure
    control on stratal organization
  • here accommodation as the volume within the
    elevation difference between the long-term river
    equilibrium profile and the topography
    practically quantified as a vertical distance
    rates of creation of accommodation inferred on
    the basis of aggradation rates implication
    difficulty in treating accommodation as a
    variable that is independent of sediment supply.

17
Discussion
Results do not support the use of aggradation
rate as a predictor of architectural style as
implied by the LAB models. Sequence stratigraphy
models and practice considering temporal changes
in channel proportions and geometry as indicative
of changes in the rate of creation of
accommodation (e.g. the use of accommodation-based
systems tracts) need to be re-evaluated. Evidence
is against the practicability of inferring low-
or high-accommodation settings from
channel-deposit proportions and geometries alone.
?
?
?
?
18
Conclusions future work
  • aaaa
  • Current work exposes the inadequacy of
    established models and sequence stratigraphy
    practice
  • necessity to substantiate results with more case
    studies
  • necessity to focus this type of investigations
    on architectural response to controls causing
    changes in aggradation rate
  • necessity to evaluate architectural repsonses at
    different time-scales.
  • All this requires a continuing effort in field
    studies combining architectural characterization
    with derivation of constraints on system boundary
    conditions.

19
Thank you for your attention!
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