Flood hazard and risk in Lillooet River valley, British Columbia, Canada
Bibliographic record
Abstract
This thesis examines flood hazard in Lillooet River valley in the southern Coast Mountains of British Columbia, Canada. My research is multi-disciplinary: I used earth science methods to estimate pre-historical flood frequency and sediment yield, as well social science theory to study the process of knowledge transfer between the scientific community and local stakeholders. The results from this thesis contribute to and complement previous earth science and natural hazard studies in Lillooet River valley, while furthermore providing knowledge for river and floodplain management. The results also shed a light on the communication of scientific knowledge to local emergency managers and the use of such information at the local level.My thesis comprises three studies. First, I compiled a varve chronology spanning 825 years (AD 1179-2004) from annually layered sediments (varves) recovered from Lillooet Lake. I compared twentieth-century discharge records of Lillooet River to the contemporary part of the varve chronology to determine the relation between river discharge and varve thickness. Based on this relation, I examined the entire 825-year varve chronology for the floods it might record. Second, I made annual sediment yield estimates for the period AD 1629-1997 and compared them to estimates derived from Lillooet Lake cores by previous researchers. I compared times of anomalously high sediment yield to ages of large landslides and floods in the watershed, and to times of marked glacier advance and retreat in order to understand controls on sediment delivery. I assessed the persistence of high sediment input episodes using statistical methods. Third, I assessed the history and current flood management policy landscape at the federal, provincial, and local levels. In the context of the transfer of flood management responsibility from the British Columbia Government to municipalities in 2003, I interviewed local floodplain and emergency managers on their use of scientific knowledge in preparing for flooding in Lillooet River valley.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".