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Enregistrement W4381986065 · doi:10.1111/jfr3.12914

The growing strength of the ‘Journal of Flood Risk Management’ community

2023· article· en· W4381986065 sur OpenAlexaboutno aff
Chrissy Mitchell

Notice bibliographique

RevueJournal of Flood Risk Management · 2023
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueFlood Risk Assessment and Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFlood mythChinaVulnerability (computing)Flood risk managementGeographyDiversity (politics)Risk managementPolitical scienceEnvironmental planningEnvironmental resource managementBusinessEnvironmental scienceLawComputer science

Résumé

récupéré en direct d'OpenAlex

The Journal of Flood Risk Management provides an international platform for knowledge sharing in all areas related to flood risk. Not even halfway through 2023, the Journal has already received papers from over 36 different countries, outlining the diversity of coverage. United Kingdom, China, United States and Iran have submitted the majority. Closely followed by Germany, Italy, Egypt, Netherlands, Canada, the Republic of Korea and India. Perhaps more important to authors is the readership, which shows a healthy global spread, and in 2022, 350,000 full-text article views were undertaken. Those countries mentioned above lead the way in accessing the articles, alongside the Philippines, Australia and Malaysia. The top 10 most viewed articles all having well over 2000 views each. They show no clear trend in the topic area, covering the many different aspects of flood risk management. In this issue, it is excellent to see the diversity in topics. A number of articles consider the decision-making aspects of flood management. Chyon et al., provide an integrated assessment of flood risk, where both the physical hazard and the socio-economic exposure alongside vulnerability are considered, providing an approach that can successfully improve adaptive capacity and can be applied elsewhere (Chyon et al., 2022). Davids et al. (2023), investigates how homeowners “rationalities” respond to expert advice, using Cultural Theory to invite behavioural skills beyond engineering into consideration. Interestingly, Tyler et al. (2023) review funding scenarios for a number of coastal counties in south-eastern United States, where results show counties that are socially vulnerable are less likely to receive funding. A number of articles focus on urban aspects. Chang et al. (2022) consider the lack of operational or quantitative stormwater management resilience indicators that can support a reduction in inundation for short-duration flooding. Alongside the same theme of looking at further evidence for measures, Azhar et al. (2023) consider the safety criteria for flooding in relation to stationary vehicles. Highlighting the shift in stability being highly dependent on the road conditions. Hosseinzadeh et al. (2023) consider potential detention pond placement and support for decision makers when planning design requirements. When considering the improvements of predictions, Moon et al. (2023) use nomographs to consider future flooding of an urban river. Sahraei et al., 2022 use a GIS-based multi-criteria decision-making approach for large ungauged watersheds, focusing on susceptibility when having little access to data: an interesting hybrid method that seemingly outperforms some previous methods when compared with known historic maps. Mahmoodi et al. (2023) compare different weighting methods for watershed multi-criteria models and highlight the importance of prioritizing a number of factors that go into the decision-making. While Hu et al. (2023) look to improve the estimation of flood frequency statistics, they suggest it is an approach that can be further used in other ungauged catchments. Finally, in this issue, Collins et al. (2023) consider natural flood management and strongly conclude that these sorts of natural interventions in large permeable catchments should be considered further. Sharpe et al. (2023) focus on the impact of riparian forests on hydraulic roughness, looking at the reliability of roughness coefficients. Ceccato and Simonini (2023) consider levee failure mechanisms, in particular focusing on small cavities, in relation to the Panaro levee breach in 2020. In the past 15 years (2009–2022), the average number of papers submitted to the Journal of Flood Risk Management has been 165 per year. It is recognised that this is often the accumulation of considerable time, study and financial commitment by the authors, which makes it disappointing when not all of these papers make it through to final publication. Guidance is provided to authors prior to submission (Wiley, 2023a). Some of the more common reasons for not being published include no clear novelty or advance in scientific knowledge presented, written to a lower standard, too much of an overlap with a similar authored paper published elsewhere, no response by an author following feedback, and a request for minor or major changes. Perhaps most frustrating is a paper that has really good scientific advances, but where the language used is challenging to follow. For this, a service is offered to authors (Wiley, 2023a) or we suggest a native reader undertakes a thorough check before submission. When an author submits an article, the peer review process includes a thorough review and response from an associate editor and two reviewers, before consideration by the editor in chief. If changes are recommended then the revised article can often require a second or even third iteration of review, repeating this same process. This journal, as do many others, relies on the peer review of experts in the field to undertake these reviews and is very grateful for those who volunteer their time and expertise to do so. The time it takes to respond to an author and ultimately publish is directly dependent on the time it takes to find reviewers willing to undertake a review, as well as the time it takes reviewers to respond. Although this robust process has previously occurred in less than 1 month, it can take significantly longer. The journal openly welcomes new potential reviewers (Wiley, 2023b) and kindly requests that if an invitation to review is sent to you, that a decision (either way) and a suggestion of who might be appropriate to ask and available further to yourself, is gratefully received.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,008
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,547
Score d'incertitude au seuil0,856

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0080,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0030,002
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,008
Tête enseignante GPT0,231
Écart entre enseignants0,223 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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