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Record W7042969662

Scenarios and implications of land use and climate change on water quality in mesoscale agricultural watersheds

2015· dissertation· en· W7042969662 on OpenAlexfundaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2015
Typedissertation
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsClimate changeLand useWater qualityLand use, land-use change and forestryAgricultural landHydrology (agriculture)AgricultureSurface runoffSurface water
DOInot available

Abstract

fetched live from OpenAlex

A comparative study in two mesoscale, agricultural watersheds located in mid-latitude, developed regions (Altmühl River, Germany and in Pike River, Canada) investigated potential future land use change and climate change impacts on surface water quality. The two watersheds provided a unique opportunity to compare potential impacts of change in similar physical and climatological regions, yet under different political settings related to agricultural policies as well as water quality management and protection. The objectives of the research were to develop agricultural land use scenarios to apply to a hydrological model simultaneously with climate change simulations. This modelling framework allowed quantifying these combined impacts on streamflow, sediment loads, nitrate-nitrogen loads and concentrations, as well as total phosphorus loads and concentrations to the 2050 time horizon. The impacts of climate change were evaluated alone and then with land use change. Overall, the quality of surface water simulated in both watersheds will be deteriorated according to environmental standards set by the ministries by 2050 due to higher mean annual nutrient loads transported into the rivers. Climate change impacts were greater than land use change impacts; however land use change can have an important influence on water quality, depending on the magnitude of crop changes taking place. Field-level adaptation strategies in the Pike River were simulated to determine the extent of reducing the combined impacts of land use and climate change. The strategies were able to mitigate the combined impacts, and also to improve the quality of surface water compared to the in-stream nutrient concentrations in the reference simulation.In both watersheds, it was determined that the combined interaction between climate change and land use change in the hydrological model are non-linear. Examining the combined impacts are necessary to determine potential alterations in water quality in a basin since the direction and the magnitude are not predictable from the individual changes alone.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.919
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.031
GPT teacher head0.258
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2015
Admission routes2
Has abstractyes

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