MétaCan
Menu
Back to cohort
Record W1914069691 · doi:10.1029/2006wr005645

On the relation between dynamic storage and runoff: A discussion on thresholds, efficiency, and function

2007· article· en· W1914069691 on OpenAlex

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

VenueWater Resources Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsSurface runoffHydrographRunoff modelEnvironmental scienceHydrology (agriculture)Runoff curve numberDrainage basinSnowmeltStructural basinFunction (biology)GeologyGeographyGeotechnical engineering

Abstract

fetched live from OpenAlex

Unit hydrograph theory as derived by Nash (1957), Dooge (1959), and Wooding (1965) provides a foundation for evaluating the function controlling catchment runoff. Past literature has often investigated this function converting catchment storage to runoff with probabilistic or statistical approaches. A geophysically based framework is missing. The objective of the research reported here is to evaluate this function explicitly, using empirical nested measurements of surface storage and runoff in a Canadian Prairie catchment during the 2006 spring snowmelt. Variation in the value of this function, K at the basin scale, or k at the sub‐basin scale, was found to embody the hydrological processes acting upon a catchment. It is the relative difference between the runoff rate and the change in storage that indicates the hydrological function of a sub‐basin, and k is indicative of the efficiency of this functioning. Field results show that previous assumptions of instantaneously responding reservoirs within catchments are not applicable in this landscape. Storage thresholds control the value of the transfer function by influencing when runoff production occurs. In doing so, storage thresholds play a crucial role in the efficiency with which a catchment can transfer water to its outlet. The transfer function and storage threshold, by dictating runoff, can be considered hydrological signatures. Applying these signatures within a geophysically based framework has proven to be successful in predicting the efficiency of runoff production in this particular catchment and is proposed as an approach to evaluate the interrelationships between catchment stores and runoff production. Furthermore, if hydrological processes or physioclimatic predictors can be related to these hydrological signatures in a dimensionally consistent framework, this framework could be tested as a bridging mechanism between hydrological processes at the sub‐basin scale and prediction of runoff at the basin scale.

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)0.003
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 score0.099
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.024
GPT teacher head0.283
Teacher spread0.259 · 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