The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.
Fluvial Facies Models: Recent Developments
Abstract
Abstract Recent development of fluvial facies models has been due to improved description of natural river and floodplain processes and deposits using: (1) ground-penetrating radar (GPR) combined with cores and trenches to describe modern deposits in 3D; (2) study of frozen rivers to allow easy access to the entire channel belt and procurement of undisturbed cores; (3) optically stimulated luminescence (OSL) for improved dating of deposits; (4) high-resolution remote sensing over large areas and at short time intervals in order to determine temporal changes in channel and floodplain geometry due to erosion and deposition; (5) new measuring equipment such as acoustic Doppler current profilers (ADCP), high-resolution multibeam sonar, and GPS, for measuring surface topography, flow, and sedimentary processes. However, there is still a lack of studies of river geometry, flow, and sedimentary processes at the all-important high flow stages, especially on big rivers and floodplains. Laboratory studies of bed geometry, flow, and sediment transport, erosion, and deposition have been undertaken for a range of scales, from small bedforms such as ripples, dunes, and antidunes, to bars and channels, to whole channel belt–floodplain systems. Controls on river and floodplain mechanics such as sediment supply, base level, and tectonism have also been evaluated. However, there are scaling problems with laboratory experiments that become more acute as the scale of the system increases. The new field and laboratory data have allowed development of new qualitative and quantitative fluvial depositional models. Such models account for the fact that: (1) there are different superimposed scales of fluvial forms and associated stratasets in rivers and floodplains; (2) the geometry and mode of migration of any scale of fluvial form (e.g., dune, bar, channel, channel-belt) is closely related to the geometry and internal character of the associated strataset, which allows development of generalized depositional models for the different scales; (3) changes in flow stage over various time scales affect the nature of deposits. These new models use consistent descriptive terminology and dispel many of the extant misconceptions about fluvial deposits. Quantitative, process-based models of fluvial deposits exist, but are not well developed, especially for the longer-term and larger-scale processes and deposits. Process-based models of the effects of tectonism, climate, and base-level change on fluvial deposits are in their infancy. Furthermore, most models are difficult to test. These problems with quantitative models are due to lack of appropriate quantitative data, and difficulties in mathematical modeling of complex natural systems. As a result of this, stochastic models are commonly used to represent fluvial stratigraphy, given initial data from wells, cores, and geophysical surveys. Development of quantitative models is essential if we are to understand and predict the nature and spatial distribution of ancient fluvial deposits, and to characterize aquifers and hydrocarbon reservoirs for subsurface fluid flow simulations. Such development will require more studies of rivers and floodplains during floods, and more mathematical sophistication.
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Aitken, M. J. (1998) · doi:10.1093/oso/9780198540922.001.0001 · Cited by 1,898
GEOCARB II; a revised model of atmospheric CO 2 over Phanerozoic time
Berner, R. A. (1994) · American Journal of Science · doi:10.2475/ajs.294.1.56 · Cited by 1,683
GEOCARB III: A revised model of atmospheric CO2 over Phanerozoic time
Berner, R. A. (2001) · American Journal of Science · doi:10.2475/ajs.301.2.182 · Cited by 1,323
Fluvial responses to climate and sea‐level change: a review and look forward
Blum, M. D., & Törnqvist, T. E. (2000) · Sedimentology · doi:10.1046/j.1365-3091.2000.00008.x · Cited by 1,250
Brahmaputra river: Channel processes and sedimentation
Coleman, J. M. (1969) · Sedimentary Geology · doi:10.1016/0037-0738(69)90010-4 · Cited by 1,123
A REVIEW OF THE ORIGIN AND CHARACTERISTICS OF RECENT ALLUVIAL SEDIMENTS
ALLEN, J. R. L. (1965) · Sedimentology · doi:10.1111/j.1365-3091.1965.tb01561.x · Cited by 1,001
Perspectives on the Sequence Stratigraphy of Continental Strata
Shanley, K. W., & McCabe, P. J. (1994) · AAPG Bulletin · doi:10.1306/bdff9258-1718-11d7-8645000102c1865d · Cited by 866
A model for atmospheric CO 2 over Phanerozoic time
Berner, R. A. (1991) · American Journal of Science · doi:10.2475/ajs.291.4.339 · Cited by 747
Paleosols in clastic sedimentary rocks: their geologic applications
Kraus, M. J. (1999) · Earth-Science Reviews · doi:10.1016/s0012-8252(99)00026-4 · Cited by 662
A simulation model of alluvial stratigraphy
BRIDGE, J. S., & LEEDER, M. R. (1979) · Sedimentology · doi:10.1111/j.1365-3091.1979.tb00935.x · Cited by 654
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Paleovalley systems: Insights from Quaternary analogs and experiments
Blum, M., Martin, J., Milliken, K., & Garvin, M. (2013) · Earth-Science Reviews · doi:10.1016/j.earscirev.2012.09.003 · Cited by 451
Davies, N. S., & Gibling, M. R. (2010) · Earth-Science Reviews · doi:10.1016/j.earscirev.2009.11.002 · Cited by 337
Weissmann, G. S., Hartley, A. J., Scuderi, L. A., Nichols, G. J., Owen, A., Wright, S., Felicia, A. L., Holland, F., & Anaya, F. M. L. (2015) · Geomorphology · doi:10.1016/j.geomorph.2015.09.005 · Cited by 134
Edwards, D., Cherns, L., & Raven, J. A. (2015) · Palaeontology · doi:10.1111/pala.12187 · Cited by 82
Metadata
- Authors
- BRIDGE, J. S.
- Venue
- Facies Models Revisited
- Published
- 2006
- Pages
- 85-170
- OpenAlex
- W2476623835
- Cited by
- 339
- References
- 73
- FWCI
- 9.11
- Type
- book chapter
- Language
- en
- Open access
- closed
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