SENSITIVITY OF HYDROPOWER PERFORMANCE TO 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
( † sadly deceased- please see dedication) Abstract: One solution to reduce the extent of climate change is to replace fossil-fuelled electricity generation with renewable sources including hydropower. However, simultaneous changes in climate may alter the available hydropower resource, threatening the financial viability of schemes. To illustrate the potential problem, a sensitivity analysis is presented that considers the impact of altered precipitation and temperature on river flows, energy production and financial performance measures of a planned hydro scheme in Sub-Saharan Africa. The behaviour of the river basin was found to amplify changes in precipitation and, while the design and planned operational strategy of the station tended to moderate the impact, the overall financial impact remained significant. Comparison with (non-climate) project parameters indicated that financial performance, not surprisingly, depends strongly on discount rate and electricity sales price and that, importantly, it showed a similar sensitivity to precipitation change and rising temperature. Critical changes in climate were identified in order to indicate the severity of climate change that could be tolerated before the project becomes financially non-viable.
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