Dynamic Modeling for Municipal Climate Change Adaptive Measures and Integrated Watershed Management
Bibliographic record
Abstract
Extreme rainstorms with higher intensity and frequency are expected to increase in future climate. Climate change expected potentially to impact the capacity of infrastructure, service level, and the natural environment. Traditional stormwater management plans, procedures and actions are no longer sufficient to deal efficiently with the uncertainty of climate change. Urban stormwater infrastructure has been sized based on assumptions of rainfall intensities. Given that these intensities are shifting upwards as a result of climate change, storm sewer systems and overland flow routes will likely be more often inundated beyond the design capacity. Knowing the relationship between the piped storm sewer network and the above-ground major system has become more critical. Formerly these two systems were calculated independently, but 1D/2D computer modelling allows them to become a single integrated system. An integrated 1D/2D sewer and overland flow model is sophisticated tool that has become feasible for use by practitioners. The use of this type of computer models can provide local authorities with new insights into how infrastructure responds to rainfall events and how best to make the changes that will add resiliency under more extreme climatic conditions. The paper outlines an approach of using an integrated 1D/2D sewer and overland flow dynamic computer models in Hamilton areas. Hydrologic and hydraulic modeling components will be presented with specific case study examples. Through this approach, potential risks of flooding and system responses were evaluated and alternative solutions of flood remediation were developed by considering constraints and opportunities.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".