Interbasin water transfers in the United States and Canada
Bibliographic record
Abstract
Interbasin water transfers (IBTs) can have a significant impact on the environment, water availability, and economies within the basins importing and exporting water, as well as basins downstream of these water transfers. The lack of comprehensive data identifying and describing IBTs inhibits understanding of the role IBTs play in supplying water for society, as well as their collective hydrologic impact. We develop three connected datasets inventorying IBTs in the United States and Canada, including their features, geospatial details, and water transfer volumes. We surveyed the academic and gray literature, as well as local, state, and federal water agencies, to collect, process, and verify IBTs in Canada and the United States. Our comprehensive IBT datasets represent all known transfers of untreated water that cross subregion (US) or subdrainage area (CA) boundaries, characterizing a total of 641 IBT projects. The infrastructure-level data made available by these data products can be used to close water budgets, connect water supplies to water use, and better represent human impacts within hydrologic and ecosystem models.
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.
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 | 0.000 |
| 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 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".