Recharge and vulnerability assessment of groundwater resources in North west India: Insights from isotope-geospatial modelling approach
[Display omitted] •Considerable inter aquifer connectivity is observed based on isotope study.•Integrated isotope-geospatial vulnerability model shows accuracy up to 82%.•Permeability and groundwater dynamics mainly control contamination probability.•Vulnerability map with land use and population da...
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Veröffentlicht in: | Di xue qian yuan. 2024-01, Vol.15 (1), p.101721-268, Article 101721 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | [Display omitted]
•Considerable inter aquifer connectivity is observed based on isotope study.•Integrated isotope-geospatial vulnerability model shows accuracy up to 82%.•Permeability and groundwater dynamics mainly control contamination probability.•Vulnerability map with land use and population data delineated high risk zones.
Recent studies indicate dwindling groundwater quantity and quality of the largest regional aquifer system in North West India, raising concern over freshwater availability to about 182 million population residing in this region. Widespread agricultural activities have resulted severe groundwater pollution in this area, demanding a systematic vulnerability assessment for proactive measures. Conventional vulnerability assessment models encounter drawbacks due to subjectivity, complexity, data-prerequisites, and spatial–temporal constraints. This study incorporates isotopic information into a weighted-overlay framework to overcome the above-mentioned limitations and proposes a novel vulnerability assessment model. The isotope methodology provides crucial insights on groundwater recharge mechanisms (18O and 2H) and dynamics (3H) - often ignored in vulnerability assessment. Isotopic characterisation of precipitation helped in establishing Local Meteoric Water Line (LMWL) as well as inferring contrasting recharge mechanisms operating in different aquifers. Shallow aquifer (depth |
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ISSN: | 1674-9871 |
DOI: | 10.1016/j.gsf.2023.101721 |