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Record W3184736946 · doi:10.1002/hyp.14321

Naturalizing the freezeup regimes of regulated rivers and exploring implications to spring ice‐jam flooding

2021· article· en· W3184736946 on OpenAlexafffundabout
Spyros Beltaos, Daniel L. Peters

Bibliographic record

VenueHydrological Processes · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of VictoriaEnvironment and Climate Change Canada
FundersEnvironment and Climate Change Canada
KeywordsHydrology (agriculture)Flooding (psychology)Flood mythEnvironmental scienceHydropowerSpring (device)HydrographDeltaHabitatGroundwater rechargeGeographyEcologyGeologyGroundwaterAquifer

Abstract

fetched live from OpenAlex

Abstract Naturalization of the flow hydrograph and ice regime is a key step in assessment of ecological and socioeconomic impacts of regulation across large portions of Europe, Asia and North America, where many rivers are dammed for hydropower generation. Building on previous naturalization of early‐freshet flows that influence the nature of breakup and jamming events, novel methodology is developed to estimate natural freezeup flows and thence determine associated water levels, also known to influence subsequent breakup events. Using reservoir inflows, the new methodology is applied to the lower portion of the regulated Peace River, Canada, which forms the northern boundary of the Peace‐Athabasca Delta (PAD), a Ramsar wetland of international importance that partially depends on spring ice‐jam flooding for recharge of its high‐elevation, or “perched” basins. The PAD provides habitat for numerous aquatic, terrestrial and avian species and is vital to the maintenance of indigenous culture and lifeways. Naturalized freezeup levels in the lower Peace River are shown to be nearly always lower than corresponding regulated values, with the difference averaging ~1.6 m. Consistent with known physics of river ice breakup processes, the present results suggest that ice‐jam flood frequency would likely have been greater under natural conditions. Though potentially adverse from the ecological standpoint, reduction of spring ice‐jam flooding can benefit riverside communities. Implications of the present results to and comparison with, other Canadian and international rivers are discussed.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

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

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 head0.042
GPT teacher head0.230
Teacher spread0.189 · 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

Citations11
Published2021
Admission routes3
Has abstractyes

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