Flood risk mapping in Europe, experiences and best practices
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
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.
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 | 0.002 | 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 | 0.001 |
| 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