Groundwater Quality Assessment Using CCME WQI and GIS Technique for Ujjain City, India
Notice bibliographique
Résumé
<p>Groundwater is a significant source of freshwater for people all around the world. About 97.2 % of the water on Earth is saline, with only 2.8 % available for usage as fresh water, of which approximately 20 % is groundwater. In India, a large portion of the populace relies on groundwater for drinking. The determination of water quality in residential, commercial, and industrialised areas is of great importance, and for this, the water quality index (WQI) is an effective tool which determines the suitability for drinking water of groundwater. The WQI is described as an index that reflects the combined impact of several water quality parameters that are analysed and accounted for while calculating the water quality index. In the present study, 54 groundwater samples were collected from the 54 wards of Ujjain city, Madhya Pradesh, India, during the summer period of 2019. The Bureau of Indian Standards (BIS, 2012) was used to assess the appropriateness of groundwater for drinking and calculate WQI. The water quality index was calculated using eight water quality parameters, including pH, turbidity, electrical conductivity (EC), total dissolved solids (TDS), alkalinity, chlorides (Cl–), hardness, and fluorides (F–). The objective of the study is to determine the class of all 54 samples using the Canadian Council of Ministers of Environment Water Quality Index (CCMEWQI) into five classes: excellent, good, fair, marginal, and poor. Also, the Geographic Information System (GIS) mapping technique was used to outline the spatial distribution trend of physiochemical properties and predominant ion concentration in groundwater. The obtained results suggest that wards 34 and 39 had the lowest CCMEWQI values of 32.873 and 32.120, respectively, which is unsatisfactory when compared to other wards. As a result, the general water quality of both wards (34 and 39) is poor and completely unfit for direct drinking. The CCMEWQI was found to be marginal in Wards 2, 3, 4, 6, 8, 9, 10, 12, 15, 19, 24, 25, 26, 35, 38, 40, 41, 42, 45, 46, 48, 49, and 53. Wards 5, 8, 11, 13, 14, 21, 22, 23, 28, 29, 30, 31,32, 33, 36, 50, 51, and 54 had fair water quality. CCMEWQI > 79 indicates that the water quality is good, as in Wards 20, 44, and 47. It is concluded from CCMEWQI that 6% of samples were found in the good category. 33% of the ground water samples were found to be in the range of fair quality. Similarly, 41% of samples were marginal, while 20% of samples were found to be poor. In the study area, groundwater is the main source of drinking water, so it must be managed effectively before its quality degrades.</p>
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,001 | 0,004 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».