Post-wildfire assessment and fire resilience strategies: a case study from Turkiye, with a critical evaluation of NRC-2021
Bibliographic record
Abstract
Purpose The purpose of this study is to assess structural damage mechanisms and evaluate fire resilience strategies following the 2021 Manavgat wildfire in Turkiye. Through detailed on-site inspections of 210 damaged structures, the research critically compares observed damage with recommendations from the National Guide for Wildland–Urban Interface Fires (NRC-2021), highlighting practical challenges, regional adaptability, economic feasibility and policy integration. The study provides targeted recommendations to enhance building resilience, improve wildfire mitigation strategies and inform future building codes, aiming ultimately to safeguard communities from similar wildfire incidents. Design/methodology/approach The study employed a detailed on-site investigation of 210 wildfire-affected buildings in Manavgat, Turkiye, including masonry, reinforced concrete (RC), steel and mixed structures. Structural damage and failure mechanisms were systematically identified, documented and categorized based on severity and construction materials. Observations from site inspections were then critically compared with the Canadian National Guide for Wildland–Urban Interface Fires (NRC-2021), assessing compliance levels, highlighting gaps and evaluating the effectiveness, practicality and adaptability of recommended resilience strategies to regional conditions. Findings The study identified that structural failures following the wildfire were primarily due to inadequate fire resilience measures, with timber components highly vulnerable to ignition, RC experiencing significant spalling and steel structures prone to rapid strength loss and buckling. Comparative analysis showed low compliance rates with NRC-2021 guidelines, especially concerning external walls, roofs, doors and windows. Results highlighted practical implementation challenges, economic limitations and gaps in regional adaptability, underscoring the critical need for comprehensive integration of fire-resistant construction strategies, effective vegetation management, regular maintenance and improved community-level preparedness planning. Originality/value This study offers original insights by providing a comprehensive field-based assessment of structural damage and resilience strategies from a major wildfire incident in Turkiye, critically benchmarking observed outcomes against the NRC-2021 guidelines. Its uniqueness lies in systematically evaluating implementation challenges, economic constraints, regional adaptability and policy integration gaps. The research contributes valuable, evidence-based recommendations to enhance fire-resilient construction, improve existing standards and inform future wildfire management policies, benefiting parties involved in disaster risk reduction, emergency planning and sustainable urban development.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".