Implementation strategies and a cost/benefit comparison for compliance with an environmental flow regime in a Mediterranean river affected by hydropower
Bibliographic record
Abstract
Compliance with the Water Framework Directive (WFD) of the European Union requires water managers to establish environmental flow regimes (EFR) in rivers across the continent. Few water agencies have examined the economic and social welfare impacts of implementing environmental flow requirements. We present the approach used by the Catalan Water Agency to calculate an EFR and estimate the economic implications of its implementation in the Ter River (Catalonia, NE Spain), altered by weirs for hydro-electric production. We analyze various implementation strategies and their associated economic costs and benefits, concluding that the restoration of environmental flows in the Ter River has reasonable costs and is likely to be a socially desirable policy with economic benefits exceeding costs. This paper provides an example of how a water agency can generate policy-relevant information on the social welfare impacts of implementing environmental flow policies as mandated by the WFD.
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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 | 0.000 |
| 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".