Risk Assessment and Decision Making on Mitigation Measures
Bibliographic record
Abstract
Abstract The proliferation of hydropower development to meet obligations under the Renewable Energy Directive has also seen the emergence of conflict between the hydropower developers and the fisheries and conservation sectors. To address this trade-off between hydroelectricity supply and its environmental costs, this chapter introduces a series of tools and guidance to assess environmental hazards of hydropower in particular on fishes, to enhance assessing cumulative effects from several hydropower schemes and to enable informed decisions on planning, development and mitigation of new and refurbished hydropower schemes. The newly developed European Fish Hazard Index is introduced as objective, comparable, and standardized screening tool for assessing the impacts on fishes at existing and planned hydropower schemes, while explicitly considering the ecological status and consecration value of the ambient fish assemblage. In addition, guidance is provided on assessing the environmental impacts of consecutive hydropower schemes in a river system. This guidance separates between cumulative impacts on habitats and species and thus, considers cumulative length of all impoundments in a river system, total fragmentation by barriers (barrier density), but also different migratory life history traits of species and their encounter probability with hydropower schemes and sensitivity to mortality. Finally, a decision support scheme is provided to balance the environmental risk with appropriate, site-specific mitigation planning and implementation at new and existing hydropower schemes.
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.007 |
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".