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Record W3085774746

Descriptor variables of the root zone storage capacity in Canada

2020· article· en· W3085774746 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResearch Repository (Delft University of Technology) · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsnot available
Fundersnot available
KeywordsSnowEnvironmental scienceSurface runoffDNS root zoneWater storageHydrology (agriculture)PrecipitationAridity indexSoil scienceSoil waterMeteorologyEcologyGeographyGeologyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

The root zone storage capacity is a critical determinant in hydrology, playing a major role in the partitioning of precipitation into evaporation and runoff. Besides, it is an important parameter in climatological and hydrological models. Understanding of the root zone storage capacity and its major determining processes is therefore fundamental in environmental sciences. Several studies have investigated root zone storage capacity magnitude and its descriptor variables, but mainly in snow absent regions. Computation and analysis of root zone storage capacities in snow dominant regions is therefore underexposed. As such, additional understanding of the major descriptor variables of the root zone storage capacity in boreal regions and in particular the influence of snow on the root zone storage capacity is desired. The aim of this study is therefore to quantify catchment average root zone storage capacities, identify its main descriptor variables and their regional variability and determine the influence of snow on root zone storage capacities in Canada. Root zone storage capacities were computed for 230 Canadian catchments using a simple water balance approach with additional snow module and were found to be normally distributed with mean magnitude of 183 mm and a standard deviation of 70 mm. Individual correlation of climate, discharge and landscape variables showed most relevant relationship between root zone storage capacities and yearly potential evaporation, runoff coefficient and seasonality index, although with considerable variance. Subsequent investigation on the mutual effect of several variables showed that the aridity index, runoff coefficient and seasonality timing index are major descriptor variables of the root zone storage capacity, by how they indicate the allocation of water for transpiration in a catchment and describe the degree of synchronisation between liquid input and atmospheric water demand. Application of a multiple linear regression model using the aridity index, runoff coefficient and seasonality timing index showed these variables can be used to predict root zone storage capacities in Canada with an R2 of 0.72. Subsequent tests of the predictive capability of this model Finland resulted in an R2 of 0.62. The influence of snow on the root zone storage capacity in Canada was identified by comparing its magnitude computed with and without a snow module. Whenever significantly present, snow effects showed a decrease in root zone storage capacity magnitude, caused by increased overlap between liquid input and transpiration output in a catchment. These effects are encapsulated by the seasonality timing index. To determine the regional variability of root zone storage capacity descriptors in Canada, catchments were clustered based on similar functioning. The results indicated that different variables have an effect on the root zone storage capacity in different functionally comparable regions and that a large part of the functional behaviour of the clusters can be explained by the geographical location of their catchments. The influence of these regionally dependent variables on the root zone storage capacity is encapsulated in the earlier defined main descriptor variables aridity index, runoff coefficient and seasonality timing index.

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 score0.275
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.028
GPT teacher head0.193
Teacher spread0.165 · 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