Climate Change Impact on Rainfall-Induced Landslides in Ottawa Sensitive Marine Clays
Bibliographic record
Abstract
The City of Ottawa is situated in an area known as the Champlain Sea, 17,000 years before present (BP) the entire area was covered with sea water. This area deposited marine clays which are known to be highly sensitive. The City of Ottawa needs to expand land use to allow for the expansion of infrastructure and housing to support its growth. This study is intended to assist the City of Ottawa’s geotechnical engineers in their decision-making by identifying future sensitive areas prone to landslides due to rainfall based on future climate model data. The project incorporates rainfall intensities from downscaled climate model data in the Transient Rainfall Infiltration and Grid-based Regional Slope-Stability (TRIGRS) model to investigate areas sensitive to landslides, then within a GIS platform, the future landslide susceptibility maps were created based on Factor of Safety (FS) values showing the areas prone to landslides. The data input for the model includes climate model data, topography, hydrogeology, geology and geophysical data obtained from a previous study. These data were prepared using ArcGIS software and converted into ascii format for TRIGRS model. The model was calibrated using historical rainfall intensities and validated by comparing to historical landslide areas. Sensitivity analysis were performed to ranges of geotechnical properties found within sensitive marine clays in the area to find the values best to create the ideal scenario, normal scenario and worst-case model scenario for the prediction. Rainfall intensities from projected climate data Intensities Duration Frequency (IDF) of 10 years and 50 years returning period and rainfall intensities of 12 hr, 24 hr, and 48 hr were selected for the model. Results from simulations find the projected climate rainfall intensity do not have impact or has minimal impact to slope stability in sensitive marine clay areas in Ottawa directly. However, higher rainfall runoff is expected from projected rainfall RCP8.5 than the RCP4.5. The infiltration rate remains constant throughout each simulation, which is the same value as the hydraulic conductivity. The time when the slope becomes unstable varies depending on initial water levels. Results from the ideal and normal scenario show no areas prone to slope failure after 48 hours of rainfall duration. However, the factor of safety decreases as the rainfall duration increases and is expected to decrease with longer rainfall durations. The worst-case scenario shows some areas prone to slope failure (FS < 1) with 2% probability of slope failure at 48 hours of rainfall duration. The distribution of these unstable areas are located along the Ottawa River, Rideau River, Carp River, Mississippi River and valleys along their tributaries, the majority of the area prone to slope instability from rainfall are in the east part of the City of Ottawa. While there are many uncertainties and limitations which contribute to the model results, this study is useful to engineers and planners in initial implementation of mitigation strategies to mitigate the damages and cost from landslides events. The susceptibility maps can also assist in decision making for planners in developing into these areas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".