Identification of groundwater recharge potential zones using AHP …
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3.1.4 Preparation of Drainage Density Map
Drainage density is the length of all the streams per unit area of a drainage basin. D d
= L/A, where D d = drainage density of the area, L = total length of the drainage
channel in the study area (m), and A = areal extent of the study area (m
2 ). It reflects
how properly or how poorly a watershed is drained by stream channels. The impact
of drainage density on infiltration can be considered from two different aspects. If
the river is of a lower order, it contributes mainly to drainage, leading to a lower
rate of infiltration. On the other hand, for higher-order rivers, more infiltration takes
place due to less slope of the terrain and more availability of water. Drainage density
for the area is calculated using GIS (Fig. 10).
3.1.5 Preparation of Lineament Density Map
In the rocky areas, the occurrence and movement of groundwater depend mainly on
the permeability resulting from the lineament of the area due to faulting, fracturing,
etc. Lineament is an essential parameter in calculating the groundwater recharge
potential as it indirectly gives knowledge about the storage and movement of groundwater. Straight stream valleys and aligned segments of a valley are typical geomorphological expressions of lineaments. In this study, after stream ordering, a surface
lineament map is prepared from the drainage map. The drainage lines having stream
order one, which is parallel to each other, are delineated as features of lineament.
In the present study area, the lineament density ranges from 0 to 3 m/m
2 . Particularly in the north, south, and southwest parts of the study area, the density range
from 0.5 to 2.5 m/m
2, and these sites are considered as potential zones for groundwater recharge as these sites are most suitable for infiltration of surface water into
the ground. Those areas, which have a lineament density of less than 0.5 m/m
2 , are
not suitable for groundwater recharge (Fig. 11).
3.2 Mapping with Remote Sensing and GIS Techniques
IRS-P6 LISS-III satellite image of Purulia district (dated March 8, 2011) is collected
(Fig. 5). Satellite images can be used to verify several artificially generated data. It
can also be used as an input to generate some further map layers.
3.2.1 Preparation of Land-Use Map
The extracted satellite image is classified according to land use. For this, we followed
a supervised classification technique. In supervised classification, some training polygons are created to train computer about the type of land cover. The maximum likelihood supervised classification technique is then applied using ArcGIS to get an
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