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Luca Colombera, Nigel P. Mountney, William D. McCaffrey

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. Alluvial architecture models.

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Luca Colombera, Nigel P. Mountney, William D. McCaffrey

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  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) Allen’s (1978) model did not consider aggradation rate as a predictor of sedimentary architecture. Following models did.

  3. Fluvial sequence stratigraphy models Catuneanu et al. (2009) Wright & Marriott (1993) Dalrymple (2001) 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 Catuneanu (2006)

  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). Heller & Paola (1996) Bristow & Best (1993) Some scale models contradict LAB model predictions concerning aggradation rate and channel density. Strong (2006)

  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 Part of panel from Olsen (1995) Depositional elements classified as channel-complex or floodplain element, and distinguished geometrically. Published summary data also included. Part of panel from Dalrymple (2001) Part of panel from Hirst (1991) Labourdette (2011) Part of panel from Hajek et al. (2010) 118 case studies including 32,647 classified genetic units: 7,522 classified depositional elements 3,479 classifified architectural elements 21,646 classified facies units 178 unit groups with descriptive statistics

  8. Database output ← GENETIC-UNIT PROPORTIONS GENETIC-UNIT GEOMETRIES → ← GENETIC-UNIT SPATIAL RELATIONSHIPS ↑ SYSTEM SPATIAL/TEMPORAL EVOLUTION

  9. Database method: limitations Part of panel from Dalrymple (2001) • 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. Labourdette (2011)

  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. Posamentier & Vail (1988) Muto & Steel (2000) Martinsen et al. (1999)

  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. Catuneanu et al. (2009) ? Dalrymple (2001) Catuneanu (2006) ? ? ? Martinsen et al. (1999)

  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. Reijenstein et al. (2011) after Posamentier & Allen (1999) Dalrymple et al. (1998)

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