Curbing the Summer Surge: Permanent Outdoor Water Use Restrictions in Humid and Semiarid Cities
Bibliographic record
Abstract
Abstract As urban droughts make headlines across the globe, it is increasingly relevant to critically evaluate the long‐term sustainability of both water supply and demand in the world's cities. This is the case even in water‐rich regions, where upward swings in water demands during periods of hot, dry weather can aggravate already strained water supplies and increase cities' vulnerability to water shortage. Summer spikes in water demand have motivated several cities to impose permanent restrictions on outdoor water uses; however, little is yet known about their effectiveness. This paper examines daily water production data from 15 Canadian cities to (1) quantify how overall and seasonal demands are evolving over time across humid and semiarid settings and (2) determine whether permanent water use restrictions have been effective in curbing summer water demands both seasonally and during specific hot and dry periods. Results show that while per‐capita water demand is declining in all cities studied, the seasonal distribution of that demand has remained largely stable in all but a few cases. While average demands in the summer months remain largely unaffected by the imposition of permanent restrictions, cities that enforce stringent limits on outdoor water use have seen a reduction in the variability of daily demands and a decline in peak demands following their implementation. During short‐term periods of exceptionally hot and dry weather when vulnerability to water shortage is most acute, cities with strict restrictions also see smaller surges in demand than those with weaker or no restrictions in place.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".