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01.02.2020 | Original Article | Ausgabe 1/2020

Sustainable Water Resources Management 1/2020

Assessment of groundwater potential zones using multi-criteria decision-making technique: a micro-level case study from red and lateritic zone (RLZ) of West Bengal, India

Zeitschrift:
Sustainable Water Resources Management > Ausgabe 1/2020
Autoren:
Sabita Roy, Sugata Hazra, Abhra Chanda, Sourav Das
Wichtige Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s40899-020-00373-z) contains supplementary material, which is available to authorized users.

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Abstract

Locating potential zones of ground water reservoir is a challenging task particularly in dry areas, mountaneous region or lateritic zones. In the present century, Satellite Remote sensing could offer a fresh promise to identify surface and sub-surface water resources with less time and cost. The present study was carried out in the drought-prone red and lateritic zones (RLZs) of West Bengal, India, to identify groundwater potential zones. Multi-criteria approach based on remote sensing and geographic information system utilizing six parameters, namely hydrogeomorphology, slope, drainage density, lineaments density, land use/land cover and fractional impervious surface were used in this analysis. Weightages were assigned to the parameters using Analytical Hierarchical Process (AHP) while different classes within each parameter were ranked according to their relative importance for groundwater potentiality. The study characterized different zones of groundwater prospects, viz. excellent (0.77%), good (35.20%), fair (61.80%), and poor (2.13%). During validation, 81% among the surveyed 180 dug wells of the area in the “good” potential zones were found to be perennial; while, ten among the ten dug wells surveyed in the ‘poor’ potential zone were found to be non-perennial in nature. The findings, thus, could establish that present methodology using AHP with enhanced parameterization has a better potential to identify and map the groundwater potential zones more realistically, and can be applied for drought risk reduction in wider RLZ zones.

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