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Record W1596891619

HYDROLOGIC IMPACT OF CLIMATE CHANGE IN SEMI-URBAN WATERSHEDS

2012· dissertation· en· W1596891619 on OpenAlexaboutno aff
Shamarokh Arjumand

Bibliographic record

VenueMacSphere (McMaster University) · 2012
Typedissertation
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeEnvironmental scienceHydrology (agriculture)Water resource managementGeographyEnvironmental planningGeologyGeotechnical engineeringOceanography
DOInot available

Abstract

fetched live from OpenAlex

The thesis aims to investigate the impact of climate change on the hydrology of four semi-urban watersheds in southern Ontario. The study is mainly concerned with future changes in climate variables and flow regimes. The study also assesses future changes in the frequency and magnitude of peak and low flows. The hydrologic effects of climate change were assessed using a couple of climate and hydrological models. Three regional climate models (RCMs), namely, Canadian Regional Climate Model (CRCM), United States Regional Climate Model 3 (RCM3), United Kingdom Hadley Regional Model 3 (HRM3) were used to extract raw climate variables. The raw RCM data were corrected using a bias correction method. The method performance statistics and the nonparametric test results revealed that the bias corrected climate variables followed the patterns of the observed climate variables for all weather stations. Future climate scenario was then simulated and analyses show increases in annual precipitation about 5-8% and increases in mean annual daily mean temperature about 2.6-3.2 oC. Three hydrological models (namely HBV, MAC-HBV, and SAC-SMA) were used for flow simulation. The models' validation results show a good agreement with the observed flow with a Nash Sutcliffe efficiency around 0.49-0.75 and a correlation coefficient of around 0.7-0.8 for all sub-basins. The three hydrologic models coupled with the bias corrected RCMs data were used to simulate current and future flow. For future period (2050s), the models predicted increasing winter flow and decreasing spring, summer and autumn flows. Mean annual flow shows slight to moderate changes. Significant increases in peak and low flow magnitude are predicted for higher return periods (20-100 years). Overall, the effects of projected future changes in precipitation and temperature clearly govern the significant changes in seasonal and annual flows, peak and low flow magnitudes and frequencies. Using three hydrologic and three climate models projections, a comprehensive picture of probable hydrologic impact of climate change was assessed in the study area. The wide range of predicted changes will have significant implications for future water resources development in the selected semi-urban watersheds.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.397
Threshold uncertainty score1.000

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)0.0950.000

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 head0.014
GPT teacher head0.220
Teacher spread0.207 · 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.

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

Citations1
Published2012
Admission routes1
Has abstractyes

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