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Record W2030183079 · doi:10.1002/hyp.8036

Water storage dynamics and runoff response of a boreal Shield headwater catchment

2011· article· en· W2030183079 on OpenAlex
Claire Oswald, Murray Richardson, Brian A. Branfireun

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHydrological Processes · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsWestern UniversityCarleton UniversityUniversity of Toronto
Fundersnot available
KeywordsSurface runoffHydrology (agriculture)Water storageEnvironmental scienceDrainage basinBedrockDischargeGeologyGeographyGeomorphology

Abstract

fetched live from OpenAlex

Abstract Thresholds in terrestrial water storage were quantified to explain differences in observed rainfall‐runoff relationships for a 71·5 ha research catchment in northwestern Ontario, Canada. Using terrain analysis techniques, the catchment was partitioned into discrete hydrologic response units (HRUs). Unsaturated and saturated water storage was calculated for depression and midslope HRUs using continuous hydrometric measurements and a depth function for drainable porosity. The relationship between total water storage in these HRUs and catchment discharge was then examined for evidence of threshold behaviour. Piecewise regression analysis (PRA) was used to quantify a breakpoint in the nonlinear storage‐discharge relationship, with separate linear regressions explaining the change in discharge with storage above and below this value. Above the breakpoint, a large increase in discharge is associated with a small increase in storage. Our results show that event‐scale hydrologic response displays a threshold relationship with antecedent storage and maximum event storage in the terminal depression in the catchment. Our results also suggest that predictions of event runoff improve when storage excesses from upslope depressions are explicitly routed through the catchment taking into consideration storage deficits in downslope HRUs that may impede flow. The application of landscape delineation, hydrometric monitoring and PRA to model S‐Q relationships is demonstrated to be an objective means of quantifying the transition between the two distinct hydrologic regimes in this catchment and provides new insight into how S‐Q dynamics govern the hydrologic functioning of bedrock‐dominated catchments. Copyright © 2011 John Wiley & Sons, Ltd.

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.

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 score0.116
Threshold uncertainty score0.983

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.220
Teacher spread0.201 · 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