Virtual water flows between nations in relation to trade in livestock and livestock products
Notice bibliographique
Résumé
The virtual water content of a commodity is the volume of water used to produce this commodity. International\ntrade in food implies international flows of virtual water. For water-scarce countries it can be attractive to\nimport virtual water (through import of water-intensive products), thus relieving the pressure on the domestic\nwater resources.\nThis study aims to develop a methodology to assess the virtual water content of various types of livestock and\nlivestock products and to quantify the virtual water flows related to the international trade in livestock and its\nproducts. The results are then combined with the estimates of virtual water trade flows associated with\ninternational crop trade as reported in Hoekstra and Hung (2002, 2003), to get a comprehensive picture of the\ninternational virtual water flows. The study covers the period from 1995 to 1999.\nFirst, the virtual water content (m3/ton) of live animals is calculated, based on the virtual water content of their\nfeed and the volumes of drinking and service water consumed during their lifetime. Second, the virtual water\ncontent is calculated for each livestock product, taking into account the product fraction (ton of product\nobtained per ton of live animal) and the value fraction (ratio of value of one product from an animal to the sum\nof the market values of all products from the animal). Finally, virtual water flows between nations are derived\nfrom statistics on international product trade and virtual water content per product.\nThe global volume of international virtual water flows is estimated to be 1031 Gm3 per year (695 Gm3/yr from\nthe trade in crops and 336 Gm3/yr from trade in livestock and livestock products). This means that about 20% of\nthe global water use in agriculture is aimed at producing products for export. The countries with the largest net\nvirtual water export are: the United States, Australia, Canada, Argentina and Thailand. The countries with the\nlargest net virtual water import are: Japan, Sri Lanka, Italy, South Korea and the Netherlands.\nThe total water use within a country itself is not the correct measure of a nation’s actual appropriation of global\nwater resources. In the case of net import of virtual water into a country this virtual water volume should be\nadded to the total water use within the country, in order to get a picture of a nation’s real call on the global water\nresources. Similarly, in the case of net export of virtual water from a country this virtual water volume should be\nsubtracted from the volume of internal water use. The total of internal water use and net virtual water import can\nbe seen as the ‘water footprint’ of a country, the total volume of water needed to produce the goods and services\nconsumed by the inhabitants of the country. This concept is analogous to the ‘ecological footprint’ of a nation, a\nconcept that refers to the amount of land needed to produce the goods and services consumed by the inhabitants\nof a country. This study calculates the water footprint for each nation of the world. This study does not yet\ninclude green water use within the country. Future research on water footprints should include this part of water\nuse as well, to get a more realistic figure.
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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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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 | 0,000 |
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 ».