Modeling the risk of groundwater contamination using modified DRASTIC and GIS in Amman-Zerqa Basin, Jordan
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Notice bibliographique
Résumé
Abstract Amman-Zerqa Basin (AZB) is the second largest groundwater basin in Jordan with the highest abstraction rate, where more than 28% of total abstractions in Jordan come from this basin. In view of the extensive reliance on this basin, contamination of AZB groundwater became an alarming issue. This paper develops a Modified DRASTIC model by combining the generic DRASTIC model with land use activities and lineament density for the study area with a new model map that evaluates pollution potential of groundwater resources in AZB to various types of pollution. It involves the comparison of modified DRASTIC model that integrates nitrate loading along with other DRASTIC parameters. In addition, parameters to account for differences in land use and lineaments density were added to the DRASTIC model to reflect their influences on groundwater pollution potential. The DRASTIC model showed only 0.08% (3 km2) of the AZB is situated in the high vulnerability area and about 30% of the basin is located in the moderately vulnerable zone (mainly in central basin). After modifying the DRASTIC to account for lineament density, about 87% of the area was classified as having low pollution potential and no vulnerability class accounts for about 5.01% of the AZB area. The moderately susceptible zone covers 7.83% of the basin’s total area and the high vulnerability area constitutes 0.13%. The vulnerability map based on land use revealed that about 71% of the study area has low pollution potential and no vulnerability area accounts for about 0.55%, whereas moderate pollution potential zone covers an area of 28.35% and the high vulnerability class constitutes 0.11% of AZB. The final DRASTIC model which combined all DRASTIC models shows that slightly more than 89% of the study area falls under low pollution risk and about 6% is considered areas with no vulnerability. The moderate pollution risk potential covers an area of about 4% of AZB and the high vulnerability class constitutes 0.21% of the basin. The results also showed that an area of about 1761 km2 of bare soils is of low vulnerability, whereas about 28 km2 is moderately vulnerable. For agriculture and the urban sector, approximately 1472 km2 are located within the low vulnerability zone and about 144 km2 are moderately vulnerable, which together account for about 8% of the total agriculture and urban area. These areas are contaminated with human activities, particularly from the agriculture. Management of land use must be considered when changing human or agricultural activity patterns in the study area, to reduce groundwater vulnerability in the basin. The results also showed that the wells with the highest nitrate levels (81–107 mg/l) were located in high vulnerable areas and are attributed to leakage from old sewage water.
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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 | 0,001 | 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 découle