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Record W2621923636 · doi:10.2110/jsr.2017.23

SOURCE-TO-SINK SEDIMENT BUDGET ANALYSIS OF THE CRETACEOUS FERRON SANDSTONE, UTAH, U.S.A., USING THE FULCRUM APPROACH

2017· article· en· W2621923636 on OpenAlexafffund
Sandeep Sharma, Janok P. Bhattacharya, Benjamin H. Richards

Bibliographic record

VenueJournal of Sedimentary Research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsGeologyCretaceousSink (geography)GeochemistrySedimentGeomorphologyPaleontologyCartography

Abstract

fetched live from OpenAlex

Abstract This paper matches sediment fluxes, estimated to have passed through an ancient river system, with mapped downstream sediment volumes in a deltaic sink, providing a test of the recently developed fulcrum approach to source-to-sink analysis. This paper uses field measurements (such as channel depth, width, and grain size) to estimate paleodischarge in an ancient trunk channel of the Cretaceous Ferron Sandstone in central Utah. The estimates of instantaneous discharge are then integrated over the geological duration of the river to estimate the total sediment volume delivered to downstream deltaic sinks in an attempt to balance the estimated sediment flux with the mapped deltaic deposits in the sink. The bankfull channel depths, calculated using the scaling relationship between the flow depth and the mean dune height, vary from 3.3 to 5.5 m with an average depth of 4.4 m. The corresponding bankfull channel width estimates vary from 50 to 80 m, with an average value of 65 m, calculated using scaling relationship between channel width and the width of accretion surfaces. Water discharge calculated for these bankfull dimensions vary from 2.7 × 102 m3/s to 8.6 × 102 m3/s, also indicating that these rivers were routinely capable of generating hyperpycnal flows. The instantaneous sediment discharge reaching the fulcrum was calculated using established sediment transport equations. These instantaneous discharge values were first converted to mean annual sediment volume using the bankfull event durations, recurrence intervals, and a factor for the proportion of the total annual sediment load transported during the bankfull period, based on empirical relationships from modern climate analogs, and then projected over the average time duration of individual parasequences in the Ferron Notom clastic wedge, which is approximately 14 kyr. The mass balance across the fulcrum reveals that the average bedload sediment volume derived from the source (about 3 km3) matches with that deposited in the sink within a factor of two. However, underestimation of the bedload volume in the sink suggests sediment escape beyond the limits of currently mapped sink area. Previous models for the Ferron indicate significant SE deflection of sediment due to wave reworking, which may account for the missing sandy sediment. It is also possible that there is an overestimation of time duration for individual valleys, resulting in higher sink-volume estimation and larger source-to-sink mass imbalance. Monte Carlo simulations, based on probabilistic estimation, were used to test the sensitivity of key parameters used in converting bankfull discharge to mean annual discharge. The P10, P50 (median), and P90 values for the average annual bedload volume ( Qmas ) are 9.1 × 104 m3, 1.7 × 105 m3, and 3.7 × 105 m3, respectively. A Qmas value between P50 and P90 yields a source-to-sink balance for bedload volume. The current study establishes a mass balance across the fulcrum with a reduced range of uncertainty for the various parameters used. Uncertainty associated with bankfull channel dimensions has been reduced through inclusion of detailed outcrop data. The uncertainty in estimating average annual sediment volume ( Qmas ) from bankfull events is less than a factor of three. This uncertainty can be further reduced by incorporating a more robust global-discharge dataset from modern analog river systems. Despite many assumptions and uncertainties, our study shows that the fulcrum method appears to be capable of balancing sediment budgets to within at least an order of magnitude in deep-time sedimentary systems.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059
GPT teacher head0.343
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2017
Admission routes2
Has abstractyes

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