Design Criteria of Urban Drainage Infrastructures under Climate Change
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
Actual projections provided by climate models suggest that the probability of occurrence of intense rainfall will increase in a future climate due to increasing concentrations of greenhouse gases. Considering that the design of urban drainage systems is based on statistical analysis of past events, an increase in the intensity and frequency of extreme rainfall events will most probably result in more frequent flooding. The design criteria must therefore be revised to take into consideration possible changes induced by climate change. A procedure is proposed to revise the design criteria of urban drainage infrastructures. This procedure integrates information about (1) climate projections for extreme rainfall over the region under consideration; (2) expected level of performance (or acceptable level of risk); and (3) expected lifetime of the infrastructure/system. The resulting design criterion ensures that the service level remains above the selected “acceptable” level over a predefined portion of the infrastructure lifetime. It is argued that the definition of new design criteria should be part of a global adaptation strategy combining various measures to maintain an acceptable level of service in a long-term perspective. Defining this level of service is however a challenge in a context where uncertainties on projected changes in intense rainfall are still important.
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.
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 | 0.000 |
| 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