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Record W7033626762

Re-conceptualizing the soil and water assessment tool to better predict subsurface water flow through macroporous soils

2013· dissertation· en· W7033626762 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.

fundA Canadian funder is recorded on the 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

VenueeScholarship@McGill (McGill) · 2013
Typedissertation
Languageen
FieldSocial Sciences
TopicComparative International Legal Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMacroporeTile drainageSubsurface flowSurface runoffSoil waterHydrology (agriculture)Soil and Water Assessment ToolInfiltration (HVAC)SWAT model
DOInot available

Abstract

fetched live from OpenAlex

Efforts to manage eutrophication of surface waters should recognize that macropore flow transports significantly more phosphorus (P) to surface waters via tile drains than water that percolates through the soil matrix.For the watershedscale SWAT (Soil and Water Assessment Tool) model to describe phosphorus transport through tile drains, SWAT needs to partition percolation into macropore flow and matrix flow.The objective of this study was to evaluate the effects of a new macropore flow algorithm on the partitioning of hydrological flows, using input data that are readily available, consistent with the current approach to SWAT modeling.The algorithm was evaluated in a proof of concept outside of SWAT and within a re-conceptualized version, SWAT-QC2.The proof of concept reproduced episodic macropore flows, which increased with greater daily rainfall if infiltration exceeded a threshold that was lower for finer-textured soils.Although the algorithm did not improve predictions of streamflow of an agricultural subwatershed in southern Quebec (30 km 2 ), the algorithm improved SWAT's partitioning between surface runoff and subsurface flow.SWAT-QC2 also predicted reasonably the separation between macropore and matrix components of subsurface flow, upon comparison with results from a chemicalbased hydrograph separation of the subwatershed's streamflow.As in the proof of concept, the predicted amount of macropore flow into tile drains was greater under finer-textured soils than coarser-textured soils.By describing the portion of percolation that flows through macropores and potentially controls subsurface P transport, the macropore flow algorithm provides a framework for future iii developments of SWAT that describe macropore transport of P to tile drains.To improve the partitioning between macropore and matrix flows, future developments of SWAT-QC2 should account for dynamic macropore connectivity and the effects of soil moisture on macropore flow, but more research is needed to determine experimentally the spatiotemporal variation of macropore flow in agricultural soils.de recherche et de dveloppement en agroenvironnement (IRDA -Research and Development Institute for the Agri-Environment), for his 'ground-truthing' of concepts about soil water and macropore flow from his years of field research.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.309
Teacher spread0.282 · 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