Updating Rainfall IDF Relationships to Maintain Urban Drainage Design Standards
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The hydrologic design standards for urban drainage systems are commonly based on the frequency of occurrence of heavy rainfall events. Observations of recent climate history indicate that the frequency of occurrence of heavy rainfall events is increasing. This increasing trend will likely continue in the future due to global warming. In this study, extending from previous analysis results for Chicago, the rainfall intensity–duration–frequency (IDF) relationships were determined to represent the climate conditions of the first and second halves of the last century. Using these IDF relationships, the impact of the observed increase in heavy rainfall events on the design and performance of urban drainage systems were quantified. This quantification demonstrated the need for updating rainfall IDF relationships to reflect changing climate conditions. In the design of new and retrofitting or replacement of old urban drainage systems, up to date IDF relationships need to be used to maintain design standards.
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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 | 0.002 | 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 | 0.000 |
| 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 it