Homeowners’ perceptions of property-level flood risk adaptation (PLFRA) measures: the case of the summer 2007 flood event in England
Notice bibliographique
Résumé
Flood events have far-reaching consequences, not only in economic or financial terms but also in social and health-related impacts. There is a growing body of research that suggests that property-level flood risk adaptation (PLFRA) measures have the potential to benefit homeowners by reducing the impact of flooding on households. Emphasis has, therefore, been placed on the implementation of PLFRA measures, and yet despite this, the take-up among the at-risk residents in England is low. One of the reasons identified in the literature is that homeowners do not clearly recognise the benefits of the measures. This research uses a survey of households affected by the summer 2007 flood event in England to investigate the perception of homeowners in connection with the benefits of PLFRA measures. The results highlight that there is a consensus among respondents that implementing adaptation measures has the potential to reduce health-related flood impacts such as worrying, stress and strain between families. However, there was a high level of uncertainty with regard to potential financial benefits from investing in adaptation measures, in the form of premium reduction by insurers. It was evident from the analysis that knowledge of the frequency of future flood events and expected flood damage rated highly among the factors perceived by homeowners to influence the uptake of PLFRA measures. Furthermore, the results show that there is a wide range of opinion among the respondents as to who is responsible for protecting homes against flood risk. For instance, the government flood protection scheme has the potential to provide a confusing message to floodplain residents as to whose responsibility it is to protect properties against flood risk. It is, therefore, recommended that at-risk population should be made aware of the limits of the responsibilities of other stakeholders in the domain of flood risk management at household levels. However, it is anticipated that the introduction of the new UK flood insurance scheme, Flood Re, may help to bring more clarity. There is a need to increase the motivation of homeowners to invest in PLFRA measures, which could be achieved through a range of actions, including the provision of subsidies and incentives, which would help in promoting more sustainable behaviour.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».