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Record W7038798130

Investigation of Changes in Hydrological Processes using a Regional Climate Model

2013· dissertation· en· W7038798130 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2013
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Ecology and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStreamflowPrecipitationHydrometeorologySnowDrainage basinClimate modelClimate changeInfiltration (HVAC)Hydrological modelling
DOInot available

Abstract

fetched live from OpenAlex

This thesis evaluates regional hydrology using output from the Canadian Regional Climate Model (CRCM 4.1) and examines changes in the hydrological processes over the Churchill River Basin (CRB) by employing the Variable Infiltration Capacity (VIC) hydrology model. The CRCM evaluation has been performed by combining the atmospheric and the terrestrial water budget components of the hydrological cycle. The North American Regional Reanalysis (NARR) data are used where direct observations are not available. The outcome of the evaluation reveals the potential of the CRCM for use in long-term hydrological studies. The CRCM atmospheric moisture fluxes and storage tendencies show reasonable agreement with the NARR. The long-term moisture flux over the CRB was found to be generally divergent during summer. A systematic bias is observed in the CRCM precipitation and temperature. A quantile-based mapping of the cumulative distribution function is applied for precipitation adjustments. The temperature correction only involves shifting and scaling to adjust mean and variance. The results indicate that the techniques employed for correction are useful for hydrological studies. Bias-correction is also applied to the CRCM future climate. The CRCM bias-corrected data is then used for hydrological modeling of the CRB. The VIC-simulated streamflow exhibits acceptable agreement with observations. The VIC model's internal variables such as snow and soil moisture indicate that the model is capable of simulating internal process variables adequately. The VIC-simulated snow and soil moisture shows the potential of use as an alternative dataset for hydrological studies. Streamflow along with precipitation and temperature are analyzed for trends. No statistically significant trend is observed in the daily precipitation series. Results suggest that an increase in temperature may reduce accumulation of snow during fall and winter. The flow regime may be in transition from a snowmelt dominated regime to a rainfall dominated regime. Results from future climate simulations of the A2 emission scenario indicate a projected increase of streamflow, while the snow depth and duration exhibit a decrease. Soil moisture response to future climate warming shows an overall increase with a greater likelihood of occurrences of higher soil moisture.

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 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 score0.730
Threshold uncertainty score0.274

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 studies0.0000.000
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 head0.064
GPT teacher head0.202
Teacher spread0.138 · 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 teacher head, 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

Citations0
Published2013
Admission routes1
Has abstractyes

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