Climate change drives flooding risk increases in the Yellow River Basin
Bibliographic record
Abstract
The Yellow River Basin (YRB) has experienced severe floods and continuous riverbed elevation throughout history. Global climate change has been suggested to be driving a worldwide increase in flooding risk. However, owing to insufficient evidence, the quantitative correlation between flooding and climate change remains ill-defined. We present a long time series of maximum flood discharge dating back to 1843 compiled from historical documents and instrument measurements. Variations in yearly maximum flood discharge show distinct periods: a dramatic decreasing period from 1843 to 1950, and an oscillating gentle decreasing from 1950 to 2021, with the latter period also showing increasing more extreme floods. A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods: an oscillating gentle decreasing period from 1950 to 2000, and a clear recent increasing period from 2000 to 2021. We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an ∼44.4 billion US dollars loss of floods in the YRB in 2100.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".