Water Recharges Suitability in Kabul Aquifer System within the Upper Indus Basin
Notice bibliographique
Résumé
Groundwater is the main source of water for drinking, household use, and irrigation in Kabul; however, the water table is dropping due to the excessive extraction over the past two decades. The groundwater restoration criteria selection mainly depends on the techniques used to recharge the aquifer. The design of infiltration basins, for example, requires different technical criteria than the installation of infiltration wells. The different set of parameters is relevant to water being infiltrated at the surface in comparison with water being injected into the aquifers. Restoration of the groundwater resources are complicated and expensive tasks. An inexpensive preliminary investigation of the potential recharge areas, especially in developing countries such as Afghanistan with its complex Upper Indus River Basin, can be reasonably explored. The present research aims to identify the potential recharge sites through employing GIS and Analytical Hierarchy Process (AHP) and combining remote sensing information with in situ and geospatial data obtained from related organizations in Afghanistan. These data sets were employed to document nine thematic layers which include slope, drainage density, rainfall, distance to fault, distance to river channel, lithology, and ground water table, land cover, and soil texture. All of the thematic layers were allocated and ranked, based on previous studies, and field surveys and extensive questionnaire surveys carried out with Afghan experts. Based on the collected and processed data output, the groundwater recharge values were determined. These recharge values were grouped into four classes assessing the suitability for recharge as very high (100%), high (63%), moderate (26%), and low (10%). The relative importance of the various geospatial layers was identified and shows that slope (19.2%) is the most important, and faults (3.8%) the least important. The selection of climatic characteristics and geological characteristics as the most important criteria in the artificial recharge of the aquifer are investigated in many regions with good access to data and opportunities for validation and verifications. However, in regions with limited data due to the complexities in collecting data in Afghanistan, proper researching with sufficient data is a challenge. The novelty of this research is the cross-disciplinary approach with incorporation of a compiled set of input data with the set of various criteria (nine criteria based on which layers are formed, including slope, drainage density, rainfall, distance to fault, distance to river channel, lithology, ground water table, land cover, and soil texture) and experts’ questionnaires. The AHP methodology expanded with the cross-disciplinary approach by adding the local experts´ questionnaires survey can be very handy in areas with limited access to data, to provide the preliminary investigations, and reduce expenses on the localized expensive and often dangerous field works.
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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) | 0,000 | 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 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,002 |
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 ».