Comprehensive portfolio of adaptation measures to safeguard against evolving flood risks in a changing climate
Bibliographic record
Abstract
Flooding exacerbated by climate change presents growing risks to communities worldwide. Despite extensive research on flood risk, there is a lack of critical analysis of flood adaptation measures spanning traditional and emerging methods. Here, we compile a comprehensive portfolio of 39 adaptation measures classified into four groups: infrastructural/technological, institutional, behavioral/cultural, and nature-based measures. Each measure is evaluated for its advantages, disadvantages, co-benefits, and tradeoffs. Our analysis identifies four broad eras in the evolution of flood adaptation measures. While early efforts primarily focused on structural modifications, more recent projects shifted toward soft adaptation measures, with a growing interest in employing community-centered and nature-based solutions. We lay out key decision-making attributes to identify successful adaptation strategies that are socially just, practically feasible, and technically sound. Finally, we highlight gaps and provide recommendations for future research, with an emphasis on a transdisciplinary approach toward developing and implementing climate-resilient and equitable flood adaptation strategies. The focus of flood adaptation measures has shifted over recent decades from structural modifications towards community-centred and nature-based solutions, according to a global synthesis and classification of adaptation measures.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".