Geospatial technique for delineation of groundwater potential zones in mine and dense forest area using weighted index overlay technique

2018 ◽  
Vol 7 ◽  
pp. 387-399 ◽  
Author(s):  
Surajit Murasingh ◽  
Ramakar Jha ◽  
Sirisha Adamala
Author(s):  
Raghib Raza ◽  
Gajendra Kumar Chawla ◽  
Chandra Shekhar Dwivedi

In the present study, delineation of ground water potential in Jodhpur district, Rajasthan is framed by using geospatial technique (i.e., remote sensing and GIS) and with multi-criteria leadership (MCDM) procedure. The analytical network process (ANP) is one of the suitable strategies that makes the research workable for delineation methodically, and corporate the analytic hierarchy process (AHP) as an uncommon case. For proper value to recognize the ground water potential zone in Jodhpur, Rajasthan, the AHP and ANP methods are utilized to decide the values of different parameters and their classes. The AHP values are then connected in a direct mix into raster calculator to get five distinctive groundwater potential zones in the investigation region, to be specific as ‘very poor' (2052.0 km2), ‘poor' (4225.9 km2), ‘moderate' (6355.1 km2), ‘good' (6451.2 km2), and ‘very good' (3301.7 km2). It has been presumed that about 9752.9 km2 area of Jodhpur district has very good to good groundwater potential, which is about 43.56% of the complete study area.


Author(s):  
Veeraswamy Golla ◽  
Pradeep Kumar Badapalli ◽  
balaji etikal ◽  
Vidya Lakshmi sivakumar ◽  
Sai Krishna Telkar

2021 ◽  
Vol 10 (6) ◽  
pp. 396
Author(s):  
Ümit Yıldırım

In this study, geographic information system (GIS)-based, analytic hierarchy process (AHP) techniques were used to identify groundwater potential zones to provide insight to decisionmakers and local authorities for present and future planning. Ten different geo-environmental factors, such as slope, topographic wetness index, geomorphology, drainage density, lithology, lineament density, rainfall, soil type, soil thickness, and land-use classes were selected as the decision criteria, and related GIS tools were used for creating, analysing and standardising the layers. The final groundwater potential zones map was delineated, using the weighted linear combination (WLC) aggregation method. The map was spatially classified into very high potential, high potential, moderate potential, low potential, and very low potential. The results showed that 21.5% of the basin area is characterised by high to very high groundwater potential. In comparison, the very low to low groundwater potential occupies 57.15%, and the moderate groundwater potential covers 21.4% of the basin area. Finally, the GWPZs map was investigated to validate the model, using discharges and depth to groundwater data related to 22 wells scattered over the basin. The validation results showed that GWPZs classes strongly overlap with the well discharges and groundwater depth located in the given area.


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