Global Water Monitor 2023, Summary Report
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Record temperatures across most of the world in 2023 also affected water resources and water-related hazards. Heatwaves contributed to deepening and new droughts in South America and Canada. There were many extreme rainfall events, including several cyclones. The global water cycle in 2023 was influenced by a change in circulation and ocean water temperatures in the Pacific Ocean from La Niña to El Niño conditions but against a backdrop of overall increasing sea surface temperatures due to global warming. The higher temperatures increase the strength and rainfall intensity associated with storm systems such as tropical cyclones. There were a relatively large number of such events in 2023, and the human and economic toll was large. The year started with continuing heavy rain and flooding in the Philippines and the western USA. In February, cyclonic storm systems hit Madagascar, Malawi and Mozambique in southeast Africa, while heavy rain caused floods and landslides in southeastern Brazil. In April, southeast Asia was hit by a large-scale heatwave, followed by cyclone Mocha in Myanmar. The first half of the year also saw extremely dry conditions in northern Argentina and nearby regions and in southwestern Europe. In May, record dry conditions in northern Italy were abruptly ended by heavy rainfall and flooding. An extremely wet season in South Korea, India and Pakistan brought landslides and flooding between June and August, while in Canada, very dry and hot conditions caused a record wildfire activity. From July onwards, very dry and recurrent hot conditions across South America led to a rapidly developing drought in the Amazon basin that intensified during the second half of the year. In September, a Mediterranean cyclone or ‘medicane’ brought heavy rainfall to Greece and caused reservoir dams to fail in Libya, killing thousands. In November, several years of deepening drought in Somalia were interrupted by heavy rainfall and flooding, while nearby South Sudan largely remains in drought. The final weeks of 2023 brought severe storm systems with heavy rains and flooding to the northeast coast of Australia. At the start of 2024, the greatest risk of developing or intensifying drought appears to be in Central and South America (except southern Brazil and Uruguay), southern Africa and western Australia. Regions unlikely to develop drought for at least several months include the Sahel region and the Horn of Africa, northern Europe, India, China and southeast Asia, and southern Brazil and Uruguay.
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.
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 | 0,007 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,001 |
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 découle