Comment on egusphere-2022-1103
Bibliographic record
Abstract
Abstract. Wetlands and reservoirs are important water flow and storage regulators in a river basin; therefore, they can play a crucial role in mitigating flood and hydrological drought risks. Despite the advancement of river basin theory and modeling, our knowledge is still limited about the extent that these two regulators could have in performing such a role, especially under future climate extremes. To improve our understanding, we first developed a framework coupling wetlands and reservoir operations with a semi-spatially explicit hydrological model and then applied it in a case study involving a large river basin in Northeast China. The projection of future floods and hydrological droughts was performed using this framework during different periods (near-future: 2026–2050, mid-century: 2051–2075, and end-century: 2076–2100) under five future climate change scenarios. We found that the risk of future floods and hydrological droughts can vary across different periods, in particular, will experience relatively large increases and slight decreases. This large river basin will experience longer duration, larger peak flows and volume, and enhanced flashiness flood events than the historical period. Simultaneously, the hydrological droughts will be much more frequent with longer duration and more serious deficit. Therefore, the risk of floods and droughts will overall increase further under future climate change even under the combined influence of reservoirs and wetlands. These findings highlight the hydrological regulation function of wetlands and reservoirs and attest that the combining of wetlands with reservoir operation cannot fully eliminate the increasing future flood and drought risks. To improve a river basin’s resilience to the risks under future climate change, we argue that implementation of wetland restoration and development of accurate forecasting systems for effective reservoir operation are of great importance. Furthermore, this study demonstrated a wetland-reservoir integrated modeling and assessment framework that is conducive to risk assessment of floods and hydrological droughts, which can be used for other river basins in the world.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.024 | 0.013 |
| Insufficient payload (model declined to judge) | 0.177 | 0.108 |
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".