Flood risk mapping in Europe, experiences and best practices
Bibliographic record
Abstract
Abstract Within the context of the European Flood Risk Management Directive, adopted in 2007, the European countries are required to prepare flood hazard and flood risk maps before 2014. The Exchange Circle on Flood Mapping (EXCIMAP) has made an inventory of flood mapping practices in Europe. This inventory has resulted in a ‘Handbook on Good Practices for flood mapping in Europe’ and an ‘Atlas of Flood maps containing examples from 19 European countries, Japan and USA’. This paper highlights the main conclusions of the EXCIMAP Handbook and Atlas, regarding the most appropriate ways to present flood‐related information. Distinction is made between different types of use and users, such as land‐use planning, emergency planning, flood risk management, reinsurance and the general public. Many countries disseminate flood maps (mainly flood extent maps) and flood hazard maps (depth or depth–velocity combinations) already via Internet. Many European rivers are part of transboundary water systems. Therefore, uniform approaches in flood (risk) assessments, map legend and presentation are urgently needed.
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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 | 0.031 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".