Assessment of Groundwater Quality of Rural Areas of Allahabad District, India
Notice bibliographique
Résumé
Ground water resources are faced with an unprecedented risk of contamination, either due to leaching of metal from underground minerals or release of large quantities of industrial effluents throughout the world. Currently, about 20% of the world’s population lacks safe drinking water according to United Nations Environmental Program (UNEP, 1999). Groundwater is the most important natural resource required for drinking for many people around the world, especially in rural areas. The resource cannot be optimally used and sustained unless the quality of groundwater is assessed. A study on assessment of water quality of Allahabad District was conducted for 400 nos. of samples which were collected from 40 habitations of twenty blocks (two habitations from each blocks). The 16 water quality parameters (physical, chemical, and bacteriological), including iron, fluoride, hardness, total alkalinity, and arsenic, were analysed after bringing samples under controlled conditions from various, remotely placed habitations in the environmental engineering laboratory of the civil engineering department. The results were compared with the desirable limits of particular parameters as recommended by BIS: 10500 (91). The results showed that most of the sources were found to be contaminated by pathogenic organisms as per MPN test. The fluoride concentrations were found in excess of permissible limits in Shankargarh and Kondhiyara blocks. Iron concentrations were found too high in Shankargarh, Jasra, Soraon, and Mauaima blocks. The hardness of water samples tested was also high in Shankargarh, Jasra, and Mauaima blocks. The total alkalinity of Manda, Pratappur, Phulpur, Mauaima, and Holagarh blocks were found to be too high with reference to the desirable limit. The samples of Shankargarh and Bahadurpur blocks have shown higher arsenic concentration per new WHO guidelines. Based on assessment and testing of the quality of the groundwater of the Allahabad District, the quality is doubtful and requires preventive measures be taken before supplying water to the rural people. Therefore, sufficient precautions must be taken by concerned authorities to search for alternative sources, or treatments, of present sources to make it potable.
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 ».