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Record W4388229126 · doi:10.1002/rra.4222

Identifying ice‐jam flooding events through the application of dendrogeomorphological methods

2023· article· en· W4388229126 on OpenAlexafffund
Teagan Lubiniecki, Colin P. Laroque, Karl‐Erich Lindenschmidt

Bibliographic record

VenueRiver Research and Applications · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlooding (psychology)Hydrology (agriculture)Physical geographyEnvironmental scienceDendrochronologyGeologyGeographyPaleontology

Abstract

fetched live from OpenAlex

Abstract In this research, we explore whether a dendrogeomorphological assessment of tree scarring can accurately summarize past ice‐jam flooding events occurring at a given reach of a river. A sample site was chosen with a history of ice‐jam flooding located in close proximity to a river gauge station. Samples were collected along a 200‐m stretch of riverbank to capture the variation in elevations and possible different ice‐jam flooding events. Disk samples were collected from trees with visual scarring evidence that indicated they had endured a past ice‐jam event. Tree cores from an adjacent stand were collected to create a master chronology for each of the sampled species. Tree disks and cores were analyzed under a microscope using a Velmex stage system, then visually and statistically crossdated using the program COFECHA. Based on the last year of tree growth, years of individual injury events were established. The years of injury event dates were compared against the years of highest instantaneous maximum water elevations from gauged river data. The two data sets correlated, as the years with the highest recorded injury event dates were also the years of highest instantaneous water level elevations. The most common years of injury event dates were directly reflected in the top 5 years of the highest river instantaneous water level elevations. In addition, the year of 2020 had the highest water elevations in the past 27 years, which was again reflected in the dendrogeomorphological data as the injury event year of 2020 was recorded on over 90% of the sampled tree disks. The correlation found between the gauged river data and the dendrogeomorphological data strongly suggests that past ice‐jam flooding event dates can accurately be determined through the analysis of trees in riverbank stretches that have been impacted by ice jams. The relationship of the gauged river data to the dendrogeomorphological data will therefore allow researchers to determine ice‐jam site histories in remote areas where no gauged data exist. The site histories can provide information such as the years or heights that past ice‐jam flooding occurred, which could then be used in ice‐jam flooding hazard assessments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.201
GPT teacher head0.455
Teacher spread0.254 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2023
Admission routes2
Has abstractyes

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