Future trends in freshwater planetary boundary transgressions
Notice bibliographique
Résumé
Changes in the global freshwater cycle have become increasingly common around the world since mankind’s industrialization. The concept of planetary boundaries (PBs) is a framework defining safe limits for human activity in terms of changes in Earth subsystems, freshwater being one of the boundaries. Here the goal was to use the recently proposed new method for the freshwater change PB to determine the status of and changes in it during this century under two climate change scenarios (RCP2.6 and RCP6.0). Additionally, local changes were determined to identify areas where freshwater changes are likely to cause potential risks, especially to the agricultural sector. The impact of climate change was assessed by comparing the two chosen scenarios. \n \nData from ISIMIP2b was used to determine global and local changes in discharge and root-zone soil moisture. Changes were calculated as the frequency of monthly discharge or root-zone soil moisture values exiting variability based on pre-industrial conditions on each 0.5-degree grid cell. Each grid cell has its local variability bounds calculated from preindustrial data (1691-1860), with values below 5th percentile being considered a dry exit, and values above 95th percentile being wet exits. Additionally, dry exit frequency values were used in conjunction with crop yield and land-use data to determine risk to the agricultural sector by calculating a risk index. \n \nThe freshwater change planetary boundary has already been transgressed, and the trend continues upward in the future, especially in the higher-emissions RCP6.0 climate scenario where the share of global land area where discharge or root-zone soil moisture exits preindustrial variability bounds keeps rising through-out the century. In RCP2.6 this trend stabilizes around the 2050s. Discharge changes have fewer differences between climate scenarios than root-zone soil moisture. Notable regions with a high dry exit frequency include the Mediterranean, China, and India, while Canada, Russia, Northern Europe, and India have a high wet exit frequency. The agricultural sectors of some of the largest global crop producers are at risk in the future due to drying conditions, including the North American Corn Belt, Western Europe, Northern China, and India. \n \nMitigating climate change to reduce water cycle changes, as well as sustainable irrigation practices to cope with decreasing water resources, are key to ensuring continued food and water supply for humanity. The results of the thesis are valuable, as they help in identifying the potential areas where adaptation to change is most critical.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,011 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 0,013 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».