38

Chapter-Four

HYDROGEOMORPHOLOGY, REMOTESENSING AND GIS

APPLICATIONS

4.1 INTRODUCTION

The term ‘Hydrogeomorphology’ designates the study of landforms as

caused by the action of water (Schidegger, 1973). Because water is one of the most

important agent in forming and shaping of land forms. Geomorphology the science of

land forms (Thornbury, 1986) is related to the genesis and the evaluation of the

distinctive part of the earth surfaces. The surface shape is defined by exogenic

processes like erosion and denudation transport and endogenic processes like internal

forces in the crust (Scheidegger, 1961). The exogenic force leads to the loosing of the

solid rock and disintegration of the rock masses for easy transport. Climate and nature

of rocks control the reduction, mobility, transportation and deposition in the region

(Penck, 1953). Geomorphic unit is explained as an individual and genetically

homogenous structure produced through definite constructional or destruction

geomorphic process (Fairbridge, 1968).

Geomorphological features are manifestations of underling parent materials

and the nature and duration of geomorphic processes that have produced the related

geomorphic units (Wright, 1993).the various definitions and properties of

geomorphological units and contributions from analysis of their processes are of

immense use in the field of pedology, hydrology and environmental engineering for

various purposes.

Demak (1972) has described the (1). Role of the geomorphology in the

investigation of surface forms from the quantitative and qualitative points of view, its

39

mode of occurrence and material composition. (2). Dynamic processes due to the

origin, nature and modeling of the forms. (3). Genesis in space and time and their

spatial relationship and (4). Areal coverage.

From ground water point of view, integration of geological, structural and

hydrogeological data with hydrogeomorphological data is vital for proper

understanding of its potential. Study of surface and sub-surface water is vital for

water resources assessment of any region. Integrating surface and sub-surface data

requires huge effort in terms of manpower and time. By employing a GIS platform

the same work can be affected faster and the result obtained will be more accurate.

In this context the advent of remote sensing and GIS technology has made it

relatively easy to integrate various databases and developing management plans. Its

application in hydrogeomorphological studies is of great importance. In recent years

extensive use of satellite remote sensing has made it easier to define the spatial

distribution of different ground water prospect classes on the basis of geomorphology

and other associated feature (Sinha et al 1990,). In many earlier studies (Bedi and

Bhan, 1978; Karanth and Seshu Babu.1978; Lattman and Parizid, 1964; Moore, 1978;

Raju et al., 1985; Satyanarayana, 1991; Palanivel et al, 1996), Sharna and Jugran,

1992; Chatterjee and Bhattacharya, 1995; Tiwari and Rai, 1996; Ravindran, 1997). It

is well known that ground water accumulation, infiltration and movement depend on

the drainage, geomorphology, slope of the terrain, vegetation, soil, and depth of

weathering.

The synthesis of data on these aspects constitutes morphometric analysis. To

ascertain the subsurface water conditions, the yield of the wells and water table

fluctuations the data on the existing bore wells has been collected. The data has been

40

interpreted and also graphically represented. The water level data was collected both

from dug well and bore well. Preparation of the hydrogeomorphology map also

involved different geomorphic units like hills, piedmont zones, dykes, plains and also

lineament. In the hydrology map delineation of command region, rainfed area, tank,

stream, bore well, irrigated area, tank command area, has been attempted. It reflects

the hydrological condition of the study area. Wetland maps depict the water bodies

like streams, tanks and also extension of hydric soils. It is observed that water level of

the bore well is higher in command compare to non command region of the study

area, because of the obvious water recharging from canal and command region. It is

further observed that the ground water level is declining in rain-fed region from 350

to 550 ft. due to overexploitation. To over come this, different types of artificial

recharge structures have been suggested for the study area.

The remote sensing methods have become highly efficient tools for geological,

structural, geomorphological analysis and their mapping because of its synoptic view,

multi-spectral, multi-temporal capabilities (Krishnamurthy and Srinivasa, 1996). The

geomorphology mapping of a terrain and analysis of their processes also would help in

soil resources mapping, groundwater potential zones demarcation, landscape ecological

planning, hazard mapping and their environmental applications (Reddy et.al. 2001) the

importance of geomorphology has pointed out on landuse planning and water resource

management. In the last five decades increasing use of satellite remote sensing has caused

various techniques in preparation of the spatial distribution of various groundwater

prospect types on the basis of geomorphology and their associated characteristics.

41

4.2. MORPHOMETRIC ANALYSIS:

Morphometeric is the measurement and mathematical analysis of the

configuration of the Earth’s surface, shape and dimensions of the landforms (Clarke,

1966). This analysis can be done through measurement of linear, aerial and relief aspects

of basin and slope delineation (Nag and Chakraborty, 2003). Earlier, morphometric

analysis using remote sensing techniques have been carried out by Srivastava and Mitra,

(1995), Srivastava, (1997), Agarwal, (1998) and they are of the opinion that remote

sensing techniques are powerful tools in morphometric analysis. In the present study, the

morphometric analysis for the parameters namely stream order, stream length, bifurcation

length, stream length ratio, basin length, drainage density, stream frequency, elongation

ratio, circulatory ratio, form factor and relief ratio have been carried out. They are

presented in Tables 4.1 and 4.2 and this study has been carried out with respect to sub

watersheds which have been recognized within the main study area. The six sub

watersheds are 1.Hullahalli, 2.Maduvinahalli, 3.Kasavinahalli, 4.Halepura,

5.Hanumanapura and 6.Tandavapura and the drainage network show dendritic to sub-

dendritic patterns.

4.2.1 Drainage

Drain is a natural depression of the land surface. It’s vertical, horizontal and

length of depression depends on bedrocks, topography, geological structure and the

nature of the soil etc. Many other factors like slope, rainfall and vegetation also

contribute for the development of a drain. (Map.4.1) The study area is represented by

dendritic to sub dendritic type of drainage pattern. The dendritic drainage pattern is the

most common drainage pattern characterized by branching or tree like drainage pattern.

Drainage net work in the present study area was prepared by toposheets and Pan+LISS

42

merged data, in which the spatial resolution of the data is 5.8 m For this interpretation

keys like tone, texture, pattern and association were used. After visual interpretation of

the drainage map of the study area, it was scanned and digitized using auto cad 2000 and

ERDAS IMAGINE and finalized after field validation for the doubtful drainages. Some

of the drainage paths were updated near North east of Suttur.

4.2.2 Stream order

Measurements of the numbers of streams, branching of streams etc, may be

used to numerically/ statistically quantity of the nature of the stream pattern and used

as a predictive tool to stream behavior primarily in discharge. The first step in the

analysis of any basin is the determination of the order of streams, the concept which

was introduced by Horton (1945) and later modified by Strahler (1957). (Fig.4.1)

Here Strahler’s (1964) method, which is simplest and most widely accepted method,

of numbering, is used in which the initial tributaries are allotted the rank of 1 and

called first order streams. The second order stream is formed below the junction of

two first order streams. The third order stream is formed below the junction of two

second order streams and so on. In the present study, demarcation of stream orders up

to fourth level stream is done. (Fig.4.2) the highest first order streams are in

Hanumanapura (188) and the lowest in Hullahalli (37). The highest second order

streams are in the village Hanumanapura (70) and the lowest in Hullahalli. The third

order stream concentration is highest is in Hanumanapura (70) and the lowest is

Tandavapura (1). In fourth category highest number is in Hanumanapura (7) and the

least in the remaining maduvinahalli, Halepura (1). The fifth order stream is nil in all

the sub basins. Table 4.2. Shows the distribution of stream orders in the study area

(Map.4.2)

43

4.2.3 Stream length

Mean length of a stream-channel segment of order u, is a dimensional property

revealing the characteristics size of components of a drainage network, and its

contributing basin surfaces. The first order stream-channel with its contributing first

order drainage-basin surface area should be regarded as the unit cell, or building

block, of any watershed (Strahler, Op.Cit).It has been computed for the different mini

sub basin Table 4.1. These characteristics indicate the flow of streams from high

altitude through variation with moderately steep slopes (Singh and Singh, 1997).

4.2.4 Mean stream length

The mean stream length is a characteristic property related to the drainage

network and its associated surfaces (Strahler 1964). The mean stream length is

defined as total stream length of order ‘u’ divided by the total stream segments of

order ‘u’ (Table 4.1).

4.2.5 Stream length ratio

Stream length ratio (RL) is defined as the total stream length of order ‘u’

divided by the total stream length of the next lower order ‘u-1’ (Table 4.1). Horton’s

(1945) stream length ratio states that mean stream length segments of each of the

successive orders of a basin tends to approximate a direct geometric series with

stream length increasing towards higher order of streams. The RL between streams of

different orders in the study area reveals that there is a variation in RL in each sub

basin (Table.4.2). This variation is indicated due to later youth stage geomorphic

development (Singh and Singh, 1997).

44

4.2.6 Bifurcation ratio

It is obvious that the number of any given order will be fewer than next lower

order but more numerous than for the next higher order. The stream order is a

measure of the position of a stream in the hierarchy of the tributaries. Gravelins

(1914), Horton (1945) and Schumn (1956), Strahler (1957,) Scheidegger (1970),

considered the bifurcation ratio as an index of relief and dissections (Table 4.1 and

4.2). The first order streams are those which have no tributaries. Similarly, the third

order streams receive first and second order streams as tributaries, and so on. The

lower bifurcation ratio values are characteristic of the watersheds which have suffered

less structural disturbances (Strahler, 1964) and the drainage pattern has not been

distorted because of the structural disturbances. The bifurcation ratio is indicative of

shape of the basin. An elongated basin is likely to have a high Rb; where as a circular

basin is likely to have a low Rb. The values of Rb indicate that the basin has suffered

less structural disturbances and the basin is elongated one in nature.

4.2.7 Drainage density

To characterize the degree of drainage development within a basin, purely

qualitative terms such as well drained and poorly drained are commonly used.

Drainage density is one simple measure of expression of the drainage development. It

is defined as the average length of the stream per unit area within the total area of the

basin. (Table 4.1).The factors controlling stream length are resistance to weathering

and permeability of rock formations apart from the climate and other factors like

vegetation. According to Nag (2003) the low drainage density is observed in region of

highly resistant or permeable soil material under vegetative cover and low relief.

High drainage density is observed in the regions of weak and impermeable subsurface

45

material and sparse vegetation and hilly regions. According to American hydrological

literature the drainage density is to indicate the closeness of spacing of channels

(Horton 1932). The significance of drainage factor determines the time of travel by

water through drains (Langbein 1947). He further suggests that drainage density

varies between 0.55 and 2.09 km/km2 in humid regions with an average density of

1.03 km/km2. It is related to climate, type of rocks, relief, infiltration capacity,

vegetation cover, surface roughness and run-off intensity factor.

4.2.8 Relief ratio

The relief of the basin is expressed as the ratio of the total relief of the basin

to the longest dimension parallel to the principal drainage line (Schmun 1956) (Table

4.1). It is a direct relationship between the relief and channel gradient and also the

correlation between hydrological characteristics of drainage. Usually the relief ratio

increases with decreasing drainage area and size of micro watershed of a given

drainage basin (Gottschalk, 1964).

4.2.9 Stream frequency

(Horton 1932) introduced Stream frequency or (channel frequency) as the

total number of stream segments per unit area (Table 4.1). According to Melton

(1958) low value of stream frequency (1 to 3.5) indicates the stream or channel being

controlled by fractures and high frequency above 10 indicates a more slope from

surface runoff. In the study area stream frequency ranges from 0.1 to 2.3 (Table 4.2)

which indicates that streams are being controlled mainly by fractures and the area is

characterized by narrow hilly region to plane land for the surface runoff.

46

4.2.10 Drainage texture

One of the important geomorphic concepts is the drainage texture, which is

the relative spacing of drainage lines (Horton,1945). According to him total numbers

of stream segments of all orders per perimeter of that area are taken into consideration

(Table 4.1). Drainage lines are numerous over impermeable areas than permeable

area. Horton (1945) found infiltration capacity as the important factor which

influences the drainage texture including drainage density and stream frequency.

Smith (1950) and Singh (1967) have classified five different textures based on

drainage density .If the drainage density is less than 2, it indicates very coarse;

between 2 and 4 is coarse and between 6 and 8 is fine drainage texture.

4.2.11 Elongation ratio

To determine the shape of the basin, Schumn (1956) used the elongation ratio

(Re) which is the ratio of the diameter (De) of a circle (whose area is same as the area

of the basin) to the maximum stream length of the basin. The elongation ratio varies

from 0 to 1, and if the value is 1 it indicates that the drainage basin is a circle

(Table.4.2). A circular basin is more efficient in the discharge of run-off than the

elongated basin (Singh and Singh, 1997).The value of Regenerally vary from 0.6 to 1.

This indicates the changes in climatic condition and geological aspects. Values close

to 1 is typical of regions of very low relief. Whereas the values with 0.6 to 0.8

indicate high relief and steep ground slope (Strahler, 1964). Re values of 0.9 to 0.8

represents the oval shape and less than 0.7.shows less elongation. Re of the study

area (Table 4.2) shows the range from 0.25 to 1.92 in the one watershed which

suggests the circular shape of the basin.

47

4.2.12 Form factor

(Horton, 1945) has defined the Form factor as the dimensionless ratio basin

area Au to the square of the basin length, Lb, thus, Rf=Au/Lb2. It is a quantitative

drainage basin representation and also it is dimensionless (Table.4.1). In the present

study Hanumanapura subwatershed shows highest value (2.39) and the Hullahalli

watershed minimum (0.13). The remaining subwatersheds like Maduvinahalli and

Maduvinahalli, Halepura and Tandavapura show values between 1.39, 0.59, 1.16 and

1.46.

4.2.13 Circularity ratio

Circularity ratio (Rc) is defined as the ratio of basin area Au to the area of a

circle Ac having the same perimeter as the basin (Miller, 1953) (Table 4.1). The

circularity ratio (Rc) is influenced by factors based on length and frequency of

streams, Landuse/land cover, geological structures, geomorphic formation, climate,

relief and slope of the basin. In the present study Rc values range from 0.5 to 17.77.

Maduvinahalli sub basin has 13.5 elongated, Kasuvinahalli subbasins 4.66 and more

or less circular. Halepura subbasin (5.42) is nearly circular and is characterized by

high to moderate relief, and drainage is structurally controlled. Mean-while the

Tandavapura subbasin shows 6.9 and is indicative of elongated basin (Table 4.2).

4.3 Development through watershed

Watershed management plan plays very important role in the development of

agrarian sectors. The natural resources, when developed can meet the requirements of

ever increasing population, and also ensure sustainability. Such resources should be

studied based on geology, geomorphology, groundwater, soils, forest, land use, and

48

agriculture pattern. In the present study 2/3 of the area is under rain fed crops pattern.

Due to non uniform distribution of the rainfall and the failure of the crops, the

agricultural sector has suffered its worst, and in this direction watershed management

assumes greater importance and provides solution for sustainable development. In this

regard the Dry land development board (DLDB) and watershed development board

(WDB) of Karnataka State have taken up joint ventures in parts of the state, by

making use of remote sensing and GIS techniques. From this point of view different

thematic maps of the study area have been prepared and water resource action plan

have been suggested.

4.4. Slope of the study area

Slope aspect and altitude map is a very important terrain parameter from land

utilization point of view. For evaluating various ground features of a basin and to

prepare different thematic maps slope analysis is important. In the present study slope

map has been prepared on 1:50000 maps based on the guidelines of All India Soil

(AIS) and Land use Survey (LUS, 1995) on slope categories (Table 4.3). The general

classification of slope following the above guidelines is shown below:

Using topo maps all the contours of the study area have been upgraded to

understand the altitude of the watershed and employing remote sensing and GIS

techniques slope map has been generated Map 4.3 and area of each category of the

slope is depicted.

49

Table 4.3.General slope category guideline

Sl. No. Slope category Slope (%)

1 Nearly level 0-1

2 Very gently sloping 1-3

3 Gently sloping 3-5

4 Moderately sloping 5-10

5 Strongly sloping 10-15

6 Moderately steep to steep sloping 15-35

7 Very steep sloping > 35

Table 4.4. Slope category of Contour spacing on 1: 50,000 (IMSD tech. guideline 1995)

Slope

category

Lower and upper limit

of slope percentage

Lower and upper Limit of contour

Spacing

1. 0-1 % More than 4 cm

2. More than 1% upto 3% More than 1.33 cm and upto 4cm

3. More than 3% upto 5% More than 0.8 cm and upto 1.33 cm

4. More than 5% upto 10% More than 0.4 cm and upto 0.8 cm

5. More than 10% upto 15 More than 0.26 cm and upto 0.4 cm

6. More than 15% upto 35% More than 0.11 cm and upto 0.26 cm

7. More than 35% 0.11cm and less

50

4.5. HYDROGEOMORPHOLOGICAL CHARACTERIZATION OF

THE STUDY AREA:

Hydrogeomorphology of the study area is represented in Map 4.7 and the data

in Table 4.5 Geomorphic unit-wise ground water prospect zones and their subsurface

phenomenon, their its identification and location are based on indirect analysis of

some directly observable terrain features like geological structures, geomorphic

features and their hydrologic characters. Remote sensing has also helped for better

observation and more systematic analysis of various geomorphic units. Individual

geomorphic unit are described in Table 4.5

4.5.1. Recharge geomorphic unit of the study area

Residual hill (RH), Pediment (PD) pediment Inselbergs (PI) and pediment

inselberg complex (PIC) are the regions of medium to high slope gradient (slope

category 4-7). In these regions infiltration is less and obviously run off is more.

Water gets recharged here, but moves towards pediplain shallow (PPS), pediplain

moderate (PPM), pediplain shallow command (PPSC) and pediplain moderate

command (PPMC) regions. All these land forms come under slope category 1 to 3.

51

4.5.2 Discharge geomorphic unit of the study area

Pediplain shallow (PPS), and pediplain shallow command area (PPSC) land

forms come under 1st to 3

rd order streams. Here the ground water is poor to moderate.

It will be moderate to good depending on the existence of fractures, fissures and

jointed zones. Pediplain moderate (PPM) and pediplain moderate command (PPMC)

land forms come under 1st to 5th order streams. Here the ground water is moderate to

good. It will be very good depending on the existence of fractures, fissures and jointed

zones. Such studies have been carried out for different river basins based on remote

sensing and GIS techniques (Krishnamurthy 1991 & 1996, Gupta and Ganeshraj,

1992, Gupta 2002, Travaglia et al 1987)

4.6 HYDROLOGY

The term Hydrology deals with the study of water for both surface and ground

water on the land surface. Studying hydrology is necessary for region to evaluate and

plan the water resource. River and Rain water is the main source of water in the study

area. From this it can be noticed that the Rainfed area region is having highest area of

the study area. Bore well irrigated area and Rain fed area is the lowest area.

Remaining areas like tank command area and bore well irrigated area and canal

command area.

4.6.1 Understanding the recharge and discharge potential of the aquifers

through test well data.

Six test wells (6 bore wells) have been developed by the Department of Mines

and Geology and the data has been obtained for these wells during the present study.

These wells are located in Nanjangud taluk. The data has been collected from the

Department of Mines and geology.

52

Table 4.6 Nanjangud town Borewell water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 2.00 2.50 3.40 3.25 4.95 3.55 1.85 2.45 4.75 3.45 3.85 2.85

Feb 2.60 2.95 3.80 3.40 5.30 3.65 1.95 2.55 3.85 3.70 3.60 5.05

Mar 3.45 3.05 4.05 4.25 3.75 3.35 2.10 2.35 3.50 3.75 3.55 5.90

Apr 3.55 3.45 4.05 5.55 3.55 2.15 2.35 2.30 3.50 3.25 3.05 4.55

May 3.50 3.55 4.40 5.05 3.80 1.85 2.95 2.20 2.95 3.05 3.00 4.85

Jun 3.30 3.65 4.80 4.70 3.80 1.75 2.85 2.25 3.50 3.30 3.45 4.60

Jul 3.25 3.25 5.30 4.50 3.70 1.70 2.70 3.05 3.05 3.15 3.25 5.00

Aug 3.20 3.10 3.80 3.50 2.95 1.65 2.65 2.75 2.60 2.95 3.15 4.20

Sep 3.05 3.00 3.25 3.20 2.75 1.60 2.50 3.45 2.55 3.20 2.85 0.00

Oct 2.90 2.90 3.05 2.95 2.55 1.50 2.25 3.30 2.50 2.83 2.75 0.00

Nov 1.85 2.30 2.75 2.80 2.20 1.45 2.20 3.20 2.50 2.65 2.95 0.00

Dec 2.45 3.25 3.20 4.15 2.50 1.75 2.35 3.30 3.25 3.05 2.89 0.00

Fig.4.3 Nanjangud Bore well water level (in meters)

Nanjangud

0

1

2

3

4

5

6

7

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

53

Table 4.7 Biligere Dug well water level data (in meters)

Fig.4.4 Biligere Dug well water level (in meters)

Biligere

0

2

4

6

8

10

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 2.05 2.30 1.85 5.25 6.10 4.50 3.40 2.95 5.50 5.60 5.80 1.60

Feb 2.30 3.35 2.15 5.30 6.55 4.55 3.60 2.85 5.70 6.20 6.20 2.50

Mar 3.10 3.40 2.50 0.00 6.65 4.50 3.85 2.95 5.95 6.45 2.10 2.80

Apr 3.25 3.95 6.80 0.00 6.60 2.90 3.95 2.90 0.00 5.10 2.00 3.90

May 2.95 4.15 7.05 0.00 6.50 3.25 4.05 2.95 0.00 4.85 2.10 5.55

Jun 2.80 4.25 0.00 0.00 6.35 3.10 4.00 2.85 0.00 5.25 3.90 6.20

Jul 2.70 4.45 0.00 0.00 6.10 3.00 3.90 2.75 0.00 5.00 4.20 8.90

Aug 2.75 4.10 6.50 0.00 3.80 3.50 3.75 2.45 0.00 3.95 1.65 6.20

Sep 2.65 3.95 5.80 0.00 1.70 3.40 3.10 2.35 5.45 2.80 1.45 0.00

Oct 2.40 3.70 5.40 0.00 1.55 3.30 2.90 2.30 5.50 2.40 1.60 0.00

Nov 2.10 1.20 5.25 0.00 1.40 3.10 2.60 2.35 5.50 2.00 1.00 0.00

Dec 2.05 1.45 5.20 0.00 1.65 3.30 2.55 2.50 5.30 3.10 3.10 0.00

54

Table.4.8 Sinduvallipura Bore well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 0.00 4.40 0.00 13.05 10.10 6.50 11.00 10.70 8.40 7.95 7.60 11.20

Feb 0.00 6.20 9.45 13.20 11.20 6.75 11.10 9.30 9.40 8.60 11.40 12.05

Mar 0.00 6.50 10.20 13.50 11.45 6.55 12.10 9.15 9.30 10.60 11.80 12.15

Apr 0.00 0.00 9.80 12.10 10.10 7.55 12.90 9.20 9.40 8.50 10.60 11.90

May 0.00 0.00 12.10 11.80 12.20 6.30 13.06 8.50 9.90 8.05 12.30 12.20

Jun 8.60 0.00 12.15 10.00 13.05 5.90 13.10 9.00 11.35 9.00 13.10 12.15

Jul 8.65 9.75 11.80 9.80 12.80 7.30 13.00 9.10 11.00 8.75 13.90 12.90

Aug 8.80 9.80 10.90 10.50 12.50 8.25 12.00 8.95 8.90 7.95 14.40 12.10

Sep 7.90 10.00 12.20 8.80 9.70 8.20 11.85 4.90 6.90 6.45 15.00 0.00

Oct 7.25 9.90 11.90 5.90 9.35 8.10 11.05 4.75 8.20 6.90 12.20 0.00

Nov 4.30 3.80 12.20 7.00 3.20 8.00 10.65 4.70 8.20 4.70 10.65 0.00

Dec 4.20 4.45 13.00 8.15 5.10 9.60 0.00 4.80 7.70 5.35 11.75 0.00

Fig.4.5 Sindhuvallipura Bore well water level (in meters)

Sindhuvallipura

0

2

4

6

8

10

12

14

16

2000 2002 2004 2006 2008 2010 2012 2014

years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

55

Table 4.9 Hanumanapura Dug well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 18.9 18.6 24.6 0 26.5 7.7 11.95 14.15 27.1 28.5 28.2 8.7

Feb 19.05 19.4 10.95 0 27.45 7.8 12.15 14.3 28.3 29.1 24.4 13.7

Mar 20.15 19.5 11.4 0 29.6 9.65 13.45 14.4 28.9 30.7 24 14.1

Apr 22.3 20 12.25 30.9 29.5 8.1 14.05 14.5 29.2 29.6 15.6 12.7

May 22.5 20.9 15.55 30.45 28.85 8 14.45 14.9 29.3 29.23 14.2 13.45

Jun 24.75 21.8 11.9 26.4 29.05 10 14.9 15.1 29.7 30.3 7.3 13.4

Jul 24.85 22.3 11.85 26 26.6 11.5 15 15 29 30.65 7.5 16.2

Aug 25.25 22.9 11.95 26.2 26.3 11.6 15.1 14.15 27.7 30.25 8.6 17.1

Sep 24.3 23 10.85 26 24.3 11.65 15 14.05 27.5 30.55 9.1 0.0

Oct 21.4 25.7 13 25.15 23.85 11.7 14.8 13.7 28 30.3 8.6 0.0

Nov 20.1 24.1 10.1 24.8 7.15 11.6 13.95 13.55 28 27.1 7.8 0.0

Dec 18.15 24.3 9.95 25.25 5.9 11.85 0.0 13.8 28 27.9 7.9 0.0

Fig.4.6 Hanumanapura Dug well water level (in meters)

Hanumanapura

0

5

10

15

20

25

30

35

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

56

Table 4.10 Debur Dug well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 4.50 3.46 3.57 4.80 4.90 5.10 4.55 3.90 4.90 5.75 4.50 4.90

Feb 4.15 4.10 4.20 5.50 5.50 4.80 4.80 4.75 5.40 5.17 5.10 5.00

Mar 4.30 4.80 5.60 5.75 5.30 4.60 5.80 4.65 5.50 5.70 5.75 4.80

Apr 4.10 3.90 5.90 6.00 5.70 4.15 6.10 4.60 5.95 5.56 4.10 5.10

May 5.10 4.30 6.75 5.80 4.20 4.10 5.45 4.25 5.50 5.25 4.30 5.40

Jun 3.56 5.10 6.60 5.40 5.50 4.30 5.40 4.25 5.50 5.68 4.60 5.10

Jul 4.15 6.10 6.60 5.81 4.20 4.10 5.30 4.80 5.30 5.45 4.50 5.90

Aug 3.90 4.70 6.20 4.65 4.30 4.90 5.10 5.20 5.03 4.63 4.30 5.70

Sep 4.40 4.20 4.60 3.87 3.50 4.70 4.05 4.60 4.25 4.15 4.80 0.00

Oct 5.15 3.62 3.90 3.67 4.10 4.50 3.90 4.55 3.95 4.40 3.90 0.00

Nov 3.30 3.10 4.20 3.81 3.40 4.10 3.35 4.45 3.95 4.20 3.70 0.00

Dec 2.50 3.30 3.70 4.50 4.20 4.70 3.35 4.60 4.20 4.10 4.30 0.00

Fig.4.7 Debur Dug well water level (in meters)

Debur

0

1

2

3

4

5

6

7

8

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

57

Table 4.11 Kalale Dug well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 4.10 5.50 6.10 7.45 6.25 5.10 3.40 5.55 5.40 5.40 5.20 4.20

Feb 4.35 5.60 7.55 7.60 8.40 6.00 3.80 5.85 6.20 6.70 6.30 6.00

Mar 5.70 5.75 7.85 10.30 8.60 5.05 4.90 5.70 6.20 6.95 7.00 6.20

Apr 8.30 6.15 9.50 10.25 7.70 4.05 5.80 5.75 6.50 6.00 5.50 6.01

May 7.00 6.45 9.90 10.00 8.20 3.55 5.90 5.60 6.70 5.70 5.75 0.00

Jun 7.80 6.75 10.65 9.90 8.10 3.45 5.85 5.75 6.80 7.20 5.90 0.00

Jul 7.75 6.20 10.70 9.80 7.95 4.85 5.75 5.40 6.80 6.90 4.75 0.00

Aug 7.60 6.00 10.00 9.70 7.40 4.80 5.60 4.95 6.50 6.40 7.60 0.00

Sep 7.40 5.80 9.45 8.60 6.30 4.70 5.20 5.25 5.40 4.75 6.10 0.00

Oct 7.10 5.70 6.95 5.05 5.20 4.60 5.05 5.10 5.10 4.65 4.60 0.00

Nov 5.80 5.70 7.40 4.85 2.95 4.40 4.65 5.00 5.10 3.15 3.60 0.00

Dec 5.35 6.00 6.50 5.10 3.20 3.25 0.00 4.90 5.10 3.70 7.10 0.00

Fig.4.8 Kalale Dug well water level (in meters)

Kalale

0

2

4

6

8

10

12

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

58

Table 4.12 Kothanahalli Dug well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 7.3 6.15 6.90 10.70 10.50 6.65 6.70 6.30 7.00 6.20 7.50 4.55

Feb 7.55 7.30 7.45 10.80 10.80 7.30 7.30 3.25 7.75 6.85 7.40 5.70

Mar 8.20 7.45 7.60 11.70 11.35 7.50 7.65 3.15 7.90 7.05 7.75 5.90

Apr 8.60 7.95 8.70 12.15 11.45 7.25 8.05 6.60 7.40 6.95 7.70 5.00

May 8.70 8.20 8.40 11.75 11.70 5.36 8.10 6.70 7.20 6.72 7.60 0.00

Jun 8.35 8.40 8.85 11.15 11.85 5.70 7.95 6.80 7.40 7.50 7.00 0.00

Jul 8.10 7.50 7.75 11.00 11.20 5.85 7.80 6.70 8.70 7.60 5.80 0.00

Aug 8.25 8.10 6.20 10.90 11.15 6.35 7.60 6.10 7.90 7.80 5.70 0.00

Sep 8.05 8.05 4.60 10.05 10.55 6.25 7.50 5.60 5.50 7.30 6.20 0.00

Oct 6.90 5.35 9.65 9.95 10.40 6.15 6.65 4.75 5.70 6.80 6.20 0.00

Nov 6.05 3.51 9.90 9.50 6.65 6.05 6.15 4.85 5.70 6.50 4.90 0.00

Dec 6.00 6.75 10.05 9.85 6.60 6.25 6.10 4.90 6.00 7.00 5.20 0.00

Fig.4.9 Kothanahalli Dug well water level (in meters)

Kothanahalli

0

2

4

6

8

10

12

14

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

59

Table 4.13 Hullahalli Dug well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 7.25 6.50 10.95 11.20 9.95 9.30 9.35 9.35 8.30 9.20 8.80 11.20

Feb 7.65 7.60 11.40 11.30 10.30 9.35 9.70 9.30 9.20 9.25 8.90 11.25

Mar 8.15 7.75 12.25 11.90 0.00 8.95 10.50 9.35 9.20 9.40 9.65 11.85

Apr 9.45 8.40 15.55 11.70 0.00 9.30 11.15 9.45 9.00 8.10 9.10 11.50

May 9.60 8.85 11.90 11.20 0.00 9.55 11.25 9.30 8.90 7.92 11.60 11.80

Jun 9.25 9.15 11.85 11.05 0.00 9.70 11.35 9.35 10.00 8.50 8.70 11.70

Jul 9.20 8.00 11.95 10.80 0.00 9.50 11.25 9.20 8.65 8.30 9.00 11.80

Aug 9.30 7.30 10.85 10.10 9.05 9.45 11.10 9.00 8.60 8.20 8.40 10.60

Sep 8.90 7.00 13.00 9.80 9.45 9.35 10.95 8.50 7.60 7.75 8.20 0.00

Oct 7.50 6.85 10.10 9.45 7.70 9.25 10.10 8.05 7.50 7.90 7.05 0.00

Nov 6.50 10.05 9.95 9.30 8.25 9.10 9.80 8.00 7.50 7.60 10.40 0.00

Dec 6.40 10.76 10.25 9.50 9.00 9.05 0.00 7.80 8.70 8.40 11.00 0.00

Fig.4.10 Hullahalli Dug well water level (in meters)

Hullahalli

0

2

4

6

8

10

12

14

16

18

2000 2002 2004 2006 2008 2010 2012 2014

years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

60

Table 4.14 Thagaduru Bore well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 12.70 0.00 21.70 21.22 15.98 9.80 16.85 20.25 14.50 11.35 8.10 10.60

Feb 13.10 0.00 22.00 22.60 17.90 11.60 17.05 20.40 15.70 11.40 6.90 10.80

Mar 13.60 0.00 23.00 23.53 21.00 11.95 17.95 20.50 17.70 12.70 6.80 11.30

Apr 17.10 0.00 20.20 24.25 21.30 13.50 18.20 20.65 18.90 12.54 7.90 9.95

May 17.60 0.00 23.46 18.40 21.40 13.80 19.70 19.36 18.30 10.86 6.40 10.60

Jun 13.95 0.00 23.20 19.15 21.50 14.20 20.05 19.50 17.60 10.96 8.00 10.50

Jul 15.08 18.65 24.05 19.70 18.85 15.65 20.15 19.60 15.55 10.85 7.70 10.60

Aug 16.25 18.60 24.75 20.81 18.80 15.75 20.25 19.20 15.51 10.26 8.30 10.50

Sep 0.00 18.57 24.95 20.22 15.10 15.80 19.95 19.79 9.85 11.60 9.20 0.00

Oct 0.00 19.40 18.50 15.15 14.90 15.70 19.70 19.55 8.80 11.20 8.00 0.00

Nov 0.00 18.95 15.35 14.09 7.50 15.55 18.95 19.65 8.80 7.35 8.50 0.00

Dec 10.95 20.16 17.95 16.05 8.45 15.70 18.85 19.70 10.00 7.95 8.80 0.00

Fig.4.11 Tagaduru Bore well water level (in meters)

Thagaduru

0

5

10

15

20

25

30

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

61

Table 4.15 Kowlande Bore well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 15.40 14.30 16.40 17.10 17.45 16.15 17.60 22.45 14.85 23.15 16.75 20.00

Feb 16.80 15.20 17.15 17.50 17.15 16.90 18.50 18.85 17.50 23.35 15.10 24.40

Mar 17.90 16.00 17.90 17.65 17.25 17.15 19.85 20.05 18.45 23.55 17.30 25.00

Apr 18.90 16.75 17.45 17.35 17.05 17.25 20.90 20.90 20.25 22.10 21.95 24.10

May 18.30 17.55 17.75 16.70 17.60 15.90 19.95 21.10 21.45 21.95 18.90 24.20

Jun 17.05 17.80 17.85 16.60 17.85 16.15 19.90 21.20 21.64 22.40 18.40 24.80

Jul 17.15 15.60 18.25 15.55 14.95 17.00 19.60 21.70 21.65 22.55 19.30 25.00

Aug 17.30 15.95 18.60 16.80 14.55 17.40 17.75 21.20 21.65 22.75 20.30 24.90

Sep 16.90 16.05 18.60 17.25 15.00 17.55 17.10 18.90 21.30 20.95 20.80 0.00

Oct 14.45 15.85 16.95 16.55 14.65 17.40 16.95 17.55 22.35 20.30 19.30 0.00

Nov 13.40 15.35 16.75 15.35 14.20 17.25 15.90 17.80 22.35 15.80 18.30 0.00

Dec 14.10 16.25 16.35 16.65 15.35 17.40 15.85 17.90 21.95 16.45 18.58 0.00

Fig.4.12 Kowlande Bore well water level (in meters)

Kowlande

0

5

10

15

20

25

30

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

62

Table 4.16 Debur (a) Bore well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 3.85 4.46 3.75 4.90 5.18 5.30 4.65 4.70 5.10 5.25 4.90 5.00

Feb 4.35 3.86 4.20 5.57 5.50 4.80 4.85 4.75 5.40 5.17 5.30 5.00

Mar 4.60 0 5.60 5.76 5.35 4.40 5.80 4.65 5.50 5.70 5.75 5.20

Apr 4.80 0 5.90 6.00 5.40 4.05 6.10 4.60 5.95 5.56 3.90 5.10

May 4.70 0 6.75 5.80 4.72 4.10 5.45 4.25 5.50 5.25 4.20 5.40

Jun 3.76 0 6.55 5.55 5.05 4.34 5.40 4.35 5.50 5.68 4.60 5.60

Jul 3.75 6.00 6.60 5.81 4.70 4.20 5.30 4.95 5.30 5.45 4.30 5.90

Aug 3.80 4.30 6.20 4.65 4.34 4.80 5.10 5.20 5.03 4.63 4.00 5.60

Sep 3.49 0 4.60 3.87 3.85 4.75 4.05 4.84 4.25 4.15 4.30 0.00

Oct 3.24 3.62 3.90 3.67 3.55 4.60 3.90 4.55 3.95 4.40 3.90 0.00

Nov 3.63 3.10 4.20 3.81 3.65 4.60 3.35 4.45 3.95 4.20 3.10 0.00

Dec 2.69 3.30 4.10 4.54 3.80 4.50 3.35 4.60 4.20 4.00 3.20 0.00

Fig.4.13 Debur(a) Bore well water level (in meters)

Debur

0

1

2

3

4

5

6

7

8

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.

L i

n m

ete

rs

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

63

Table 4.17 Kothanahalli (a) Bore well water level of Nanjangud taluk

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 5.15 6.48 5.70 9.10 8.10 8.10 5.20 4.55 7.00 5.20 7.90 5.20

Feb 5.60 5.88 5.70 9.52 8.35 8.35 5.30 4.65 6.55 5.65 7.40 5.60

Mar 8.20 0.00 5.58 10.11 9.00 9.00 6.05 4.70 6.67 5.40 7.60 5.60

Apr 8.60 0.00 6.40 9.00 9.15 9.15 6.80 4.80 7.10 5.43 6.20 5.85

May 8.65 0.00 6.75 8.60 9.45 9.45 6.90 5.25 6.95 5.41 6.00 5.40

Jun 5.48 0.00 7.00 7.45 10.48 10.48 6.85 5.35 7.14 5.70 5.60 6.00

Jul 6.53 5.78 6.95 7.27 9.84 9.84 6.75 5.25 6.75 5.85 5.50 5.80

Aug 6.22 5.60 7.50 7.03 9.32 9.32 6.65 5.05 4.42 6.10 7.60 6.00

Sep 6.96 6.43 7.70 8.00 7.78 7.78 6.50 4.90 4.60 6.03 7.95 5.90

Oct 0.00 5.35 7.65 6.94 7.55 7.55 6.10 5.45 4.70 4.40 5.80 0.00

Nov 0.00 3.51 8.05 7.19 5.40 5.40 6.00 5.40 5.70 4.05 5.00 0.00

Dec 6.36 4.87 4.90 7.86 6.00 6.00 5.90 5.50 5.00 4.55 5.20 0.00

Fig.4.14 Kothanahalli (a) Bore well water level (in meters)

Kothanahalli(a)

0

2

4

6

8

10

12

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

mete

rs

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

64

Table 4.18 kalale (a) Bore well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 6.00 5.60 7.10 7.90 8.10 6.55 6.30 7.95 0.00 0.00 6.00 8.20

Feb 6.20 6.48 8.80 8.00 8.45 7.20 7.25 8.15 0.00 0.00 6.80 9.00

Mar 7.10 6.50 9.10 12.40 8.60 7.05 8.30 7.95 0.00 0.00 7.30 9.20

Apr 8.30 7.10 10.45 12.30 7.85 6.65 8.60 7.90 0.00 0.00 6.90 9.10

May 8.10 7.40 10.85 11.95 8.45 6.45 8.75 7.10 0.00 0.00 7.30 8.90

Jun 8.20 7.50 11.15 11.90 8.40 5.90 8.65 7.15 0.00 0.00 7.80 9.70

Jul 8.10 7.65 11.20 11.70 8.25 7.60 8.50 7.00 0.00 0.00 6.90 10.00

Aug 8.00 7.40 10.30 9.30 8.05 6.90 8.40 6.25 0.00 0.00 7.20 9.60

Sep 7.70 7.25 8.40 8.30 7.20 6.75 8.10 6.10 0.00 0.00 8.30 0.00

Oct 6.50 7.20 7.30 5.30 6.15 6.60 7.20 5.85 0.00 0.00 7.10 0.00

Nov 5.90 6.75 6.30 5.75 4.70 6.45 7.00 5.55 0.00 0.00 6.90 0.00

Dec 5.35 7.00 7.80 6.05 4.90 6.15 6.80 5.50 0.00 0.00 7.10 0.00

Fig.4.15 Kalale (a) Bore well water level (in meters)

Kalale (a)

0

2

4

6

8

10

12

14

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

65

Table 4.19 Hura well water level data (in meters)

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Jan 6.50 6.30 7.35 11.55 14.05 8.90 4.45 7.10 6.70 5.30 6.80 9.30

Feb 6.95 7.20 9.30 11.70 14.85 9.30 4.95 5.95 9.30 6.10 8.20 10.50

Mar 7.05 7.35 9.65 12.80 15.05 9.20 6.05 6.05 9.55 6.35 8.65 11.00

Apr 8.10 7.90 9.80 12.75 15.20 9.70 7.05 6.15 9.70 5.10 7.90 10.70

May 8.30 8.10 10.25 12.35 15.45 9.10 7.20 6.25 9.50 5.05 8.30 10.70

Jun 8.05 8.30 10.70 12.25 13.40 6.60 7.35 6.40 7.30 5.85 8.55 10.60

Jul 8.00 11.20 11.40 11.85 12.80 6.50 7.25 6.30 6.20 5.70 8.30 10.75

Aug 8.15 11.30 10.80 12.10 12.05 4.95 7.10 6.05 5.90 5.55 8.90 10.00

Sep 7.75 11.40 11.05 11.50 11.00 4.85 7.00 5.90 5.20 5.10 9.20 0.00

Oct 6.55 11.10 10.40 11.50 10.70 4.80 6.85 5.70 5.10 6.30 9.00 0.00

Nov 5.90 6.80 10.30 12.55 8.10 4.70 0.00 5.60 5.10 5.90 9.10 0.00

Dec 6.20 7.15 10.65 12.95 8.50 4.35 6.50 5.70 5.00 6.40 9.30 0.00

Fig.4.16 Hura Bore well water level (in meters)

Hura

0

2

4

6

8

10

12

14

16

18

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

Jan

Feb

Mar

April

May

June

July

Aug

Sep

Oct

Nov

Dec

66

TABLE 4.20. 2001-12 YEAR WISE DETAILS OF WATER LEVEL DATA

NANJANGUD TALUK

Fig.4.17. 2001-12 year wise details of water level data of Nanjangud taluk

Nanjangud Taluk

0

50

100

150

200

250

300

350

400

2000 2002 2004 2006 2008 2010 2012 2014

Years

W.L

in

me

ters

NAN

BLG

SDP

HP

DB

KLTH

KAL

HUL

TGD

LWD

DB1

KAL1

KLTH1

HUR

YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

NAN 35.1 36.95 45.85 47.3 41.8 25.95 28.7 33.15 38.5 38.33 38.34 37

BLG 31.1 40.25 48.5 10.55 54.95 42.4 41.65 32.15 38.9 52.7 35.1 37.65

SDP 49.7 64.8 125.7 123.8 120.75 89 131.81 93.05 108.65 92.8 144.7 96.65

HP 261.7 262.5 24.6 241.2 285.05 121.15 154.8 171.6 340.7 354.18 163.2 109.35

DB 92.05 84.71 96.05 129.5 124.2 76.66 87.55 65.7 84.15 84.27 78.95 30.15

KLTH 92.05 84.71 96.05 129.5 124.2 76.66 87.55 65.7 84.15 84.27 78.95 21.15

KAL 78.25 71.6 102.6 98.6 80.25 53.8 55.9 64.8 71.8 67.5 69.4 22.41

HUL 99.15 98.21 140 127.3 63.7 111.85 116.5 106.65 103.15 100.52 110.8 91.7

TGD 130.33 114.3 259.1 235.2 202.68 169 227.65 238.152 171.206 129.03 94.6 84.85

LWD 197.65 192.7 210 201.1 193.05 203.5 219.85 239.6 245.39 255.3 225 192.4

DB1 46.656 28.64 62.35 59.93 55.09 54.44 57.3 55.89 59.627 59.438 51.45 42.8

KAL1 85.45 83.83 108.8 110.9 89.1 80.25 93.85 82.45 00.00 00.00 85.6 73.7

KLTH1 67.75 43.9 79.88 98.07 100.42 100.42 75 60.849 72.58 63.772 77.75 51.35

HUR 87.5 104.1 121.7 145.9 151.15 82.95 71.75 73.15 84.55 68.7 102.2 83.55

67

4.6.2 Ground water potential related to structures

The structures which are important from the point of ground water localization

are lineaments, as enumerated earlier. Fractures and jointed rocks also contribute

considerable for ground water movement and accumulation especially in hard rock

terrains. Ganeshraj (1987) has shown that prominent directions of lineament in

peninsular shield trend parallel to the west coast might have developed during west

coast faulting and pointed at their importance ground water exploration. Many

previous works also bring out the importance of lineaments in ground water

studies.(Map.4.6) Naganna (1979) observed that the E-W running lineaments in

Karnataka are transporting surplus ground water from western ghat region to the

eastern part of the state. Naganna and Lingaraju (1990) studied the palar basin, Kolar

district and found that yield of borewell located over lineaments are found to be high

compared to the bore well not located on lineaments. In the study area several major

and minor lineaments have been identified and mapped. And most of the lineaments

have been found to be favorable for ground water potential. This is tested by both

studying the existing wells and also by geophysical study. Such lineament related

ground water potential zones are located near Hullahalli, Rampura, Sarguru Hoskote

and Sutturu Dykes too have significance in ground water accumulation. The contact

zones in intrusive bodies like dolerite dykes also acted as productive zones. The dykes

function as sub-surface dams. Study of topography in relation to dyke would help to

locate wells for larger supplies of ground water (Radhakrishna, 1971). In present

study dykes have been found to be areas of ground water storage in their upstream

sides. These dykes trend NE-SW. Good prospect zones of dykes for ground water are

found near Thorvalli, huskur and volgere villages. (Map.4.11)

68

4.7. REMOTE SENSING

Remote sensing is the science and art of obtaining information about an object,

area, or phenomenon through the analysis of data acquired by a device that is not in

contact with the object, area of phenomenon under investigation. Remote sensing is

concerned with the measurement of force fields, electromagnetic radiation or acoustic

energy. The techniques employs devices such as the camera, lasers and radio frequency

receivers, radar systems, sonars, gravimeters, magnetometers and Scintillation

counters. Three important variations, which form the basis for deriving the information

about objects, are:

i) Spectral variations: The changes in the intensity of radiation with wave

length.

ii) Spatial variations: The changes in the intensity of radiation with

location.

iii) Temporal variations: The changes in radiation with time.

1. Data acquisition

2. Data analysis

Data acquisition is done through sensors mounted on platforms. The data may

be pictorial or numerical

The remotely sensed data are available in two forms.

i) Imageries and photographs

ii) Digitized data on tapes.

Data analysis involves examining the data using various viewing and

interpretation devices to analyses the data.

69

i) Study and analysis of transparencies or photographs are done with the aid

of visual interpretation technique. In this technique, the identification and

study of the objects are carried out considering concurrently all the photo

recognition elements such as tone, texture, colour, pattern, shape, size etc.

ii) The analysis of digital data is carried out with the aid of computer-

processed techniques.

With the aids of the referenced data the analyst extract information about type,

extent, location and condition of the resources over which data were collected. This

information is generally presented to the users who apply into their decision making

process.

4.7. 1 PRINCIPLES AND PRACTICE OF REMOTE SENSING

4.7.2 Basic Principles

The sun’s radiation energy (Electromagnetic) radiates the earth’s objects.

Depending upon the characteristics of these objects, various types of interactions are

expected like reflectance, transmittance, absorption and reradiation. Radiation effects

can be measured or photographed. Each object has a characteristic response with

reference to a wavelength or wave band, and is termed as its spectral signatures. The

characteristic of wavelength bands commonly used for remote sensing.

Electromagnetic (EM) energy can be detected in three ways:

1. Photographically using camera

2. Electro-optical using camera

3. Electronically using radar and other devices (Basion).

70

The electromagnetic spectrum is divided into several bands and ranges. Not all

regions are useful for remote sensing. The wavelength regions used in remote sensing

are:

1. Optical wave length region-Visible 0.4-0.7um, reflective 0.7-3.0um

2. Emissive wave length region 3-16um and

3. Radar wavelength region 0.833-133 cm.

The instruments capable of measuring the EM radiation even from a further

distance are called as sensors. These sensitive devices are of two types, as:

1. Passive sensors, which do not have their own source of radiation. They are

designed to capture the effects of natural radiation. This is mostly obtained

from reflected sunlight. Cameras and Photo detectors are suitable example.

2. 2. Active sensors have a built-in source of radiation. Radars have transmitted

and receive the waves sent for interaction.

The sensor system of the satellite can be classified into two categories:

1. Imaging sensors which are sub divided into (a) “framing system” (aerial

Photographic camera, Videocon) and (b) “scanning systems” (MSS, TIRS,

Radars).

2. Non-imaging sensors, data systems (Eg. Lidar spectro radiometer, thermal

radiometer, passive microwave radiometer, radar scaterometer).

An image is a two dimensional representation (replica) of the spatial

signature of an object with respect to its spectral features. (Fig.4.18)

71

4.7.3 Indian Remote Sensing Satellites

The Indian remote sensing programme had a modest beginning in the early

sixties when aerial platforms were used to acquire information about the earth

resources. The first Indian experimental satellite, sent by India for earth observations,

was Bhaskar-1. This was placed into the orbit by a Cosmos rocket from Russian

commodore on June 7th, 1979. Bhaskar had a payload consisting of two band TV

camera for land applications and a satellite Microwave Radiometer (SAMIR) for

oceanographic / atmospheric applications. However, experimental studies were

conducted primarily using LANDSAT data, towards the development of operational

methodologies for resource management applications (Table 4.1)

4.7.4 IRS-1A, IRS-1B, IRS-1C AND IRS-1D Satellites

The first indigenous operational remote sensing satellite IRS-1A was

launched in March 1988, which continued to provide excellent data even beyond its

mission life of three years. The second satellite. IRS-1B, (identical to IRS-1A) was

launched in August 1991 with the linear Imaging Self Scanner (LISS)-I and LISS-II

on board. These satellites have provided the images in four spectral bands in the

visible and near infrared (NIR) regions (0.45 to 0.86 microns) with spatial resolution

of 72 meters and 63 meters respectively. The second generation of IRS satellite

include IRS-1C and IRS-1D was successfully launched on September 29,1997. When

compared to IRS-1A/1B, sensors of these satellites have a better spectral and spatial

resolutions, more frequent revisits, provision for stereo-viewing and on-board

recording facility. These satellites have three sensors namely LISS-III, Panchromatic

(PAN) and Wide Field Sensors (WiFS). The LISS-III sensor has four spectral bands

in the 0.5-0.70 micron region, with a swath of 142 km and a spatial resolution of 23

72

meters (70 meters for short wave infrared band). The PAN camera with spectral band

of 0.50 – 0.75 microns and swath of 70km provide a spatial resolution of around 5.8

meters and has a steering capability up to _+ 2600 which will enable frequent revisits

and are suitable for stereo viewing. The WiFS sensors operate in 2 spectral bands viz.

red and near infrared; with a spatial resolution of 188 meters and swath of 774 km

enable monitoring of vegetation dynamics (Sebastin, 1996). The characteristics of

Indian remote sensing satellites and sensors are given in the Table 6.1. Satellite data

products are as follows:

1. False color composites (obtained by combining all multispectral bands of the

same scene.

2. TM. (Thematic maps)

3. Positive and negative films

4. Digital data in CD’s tapes and fluffy disks.

False color composite are produced from colour infrared film in which blue

coloured objects primarily in green, green objects results in the reflection of red

energy, and red objects reflecting primarily in the photographic infrared portion of the

spectrum (0.7 –0.9mn).

4.8. VISUAL IMAGE INTERPRETATION

Image interpretation needs systematic and frequent examination of object

present in the imageries. Maps and reports of field observation are other importing

supporting materials to be used during interpretations. Success in photo interpretation

varies with the training and experience of the interpreter, nature of the objects being

interpreted and the quality of photographs being utilized.

73

The satellite data interpretation can often be facilitated through the

application of a certain interpretation keys. This will help the interpreter to evaluate

the information presented on imagery in an organized and consistent manner. It

provides guidance about the correct identification of features or conditions on the

photographic images. The two types of commonly used image interpretation keys are:

1. Selective keys and

2. Elimination keys

TABLE.4.21 CHARACTERISTICS OF INDIAN SATELLITE FOR EARTH

OBSERVATION (AFTER KASTHURIRANGAN et al., 1996)

Parameters Bhaskar-I & II IRS-1A/1B IRS-1C/1D

Class Spin stabilized 3-axis stabilized 3-axis stabilized

Weight (kg) 444 975/898 1247

Power (W) 47 W from solar panels

and Ni-Cd batteries

709 W from solar array

(EOL) 2 Ni-Cd

batteries

813W from solar

array (EOL)

2 Ni-Cd batteries

Mission of life One year Three year Three year

Launch 1979,1981 1988/1991 1995/1998

Orbit Height (km) Apogee 557 Perigee

572

904 817

Inclination (deg) 50.7 99.028 98.12

Type Near circular Sun-synchronous Sun-Synchronous

Equator crossing time 10.25` 10.30

Repetivity (days) 22

74

TABLE: 4.22. CHARACTERISTICS OF REMOTE SENSORS ON

BOARD INDIAN SATELLITE FOR EARTH OBSERVATION

(AFTER KASTHURIRANGAN et al., 1996)

Bhaskara

I/II TV

Bhaskar

I/II

SAMIR

IRS-1A/1B

LISS- I/II

IRS-

1C/1D

LISS-II

IRS-

1C/1D

PAN

IRS/1C/1D

WiFS

Type TV

camera

Dick-type

Microwave

Radiometer

CCD

camera

CCD

camera

CCD

camera

CCD

camera

Spectral

Bands (m)

0.54-0.66 19,21,31

(GHz)

0.45-0.52

0.52-0.59

0.62-0.68

0.77-0.86

0.52-0.59

0.62-0.68

0.77-0.86

1.55-1.70

0.5-0.75 0.62-0.68

0.77-0.86

Ground

Res. (m) 1km 125km 73/36.5

-23

(VNIR) 5.8 5.8

Swath

(km) -341 - 148/2*74 -140 -70 810

Steering Nadir Nadir Nadir

Steerable

+ 260

Nadir

looking

A selective key contains numerous imagery examples with the supporting

texts. The interpreter selects the example that most nearly resembles the features

found on imagery. An elimination key is an orderly arrangement in which the

interpretation proceeds step by step from the general to the specific and leads to the

elimination of all other feature or conditions accept the one being identified.

Any image interpretation considers the following six basic elements.

Shape – refers to the general form or outline of individual objects, which is of same

significance to the photo interpreter.

75

Size - of object on photograph must be considered in the context of the photographic

scale.

Pattern – relates to the spatial arrangement of objects: The objects and their shadow

are important to an interpreter in two respects 1. The shape or outline of a shadow

affords a profile of objects (which aids interpretation) and 2. Objects within shadow

reflect little and are difficult to discern on photograph, (Which hinders the

interpretation).

Tone – refers to the colour or the relative brightness of objects on the photographs.

Without tonal differences the shapes, pattern and texture of objects could not be

discerned.

Texture: is the frequency of tonal change on a photographic image, which is an

important parameter for image interpretation.

Site or location: of an object in relation to the other features can be very helpful in

identification (Thomas Lillisand et al 1979). Before interpretation the interpreter

should have enough background information on meteorology, forest cover, cultural

features, topography, geology, pedology, and hydrology. These elements have

considerable influence over the colors of the imagery.

4.9. REMOTE SENSING APPLICATIONS

Remote sensing data are increasingly being employed to prepare the thematic

maps pertaining to the geology, structure and lineament, hydrogeomorphological

units, land use and land cover and environmental techniques also made a continuous

change in the mapping procedure. Presently remote sensing has become an integral

part of any mapping programme. The geocoded data available in the form of

76

photographic prints (imagery) acts as a better database for all the field geologists.

Pictorial data not only improves the accuracy of observation but also reduces the

number of field traverses to the barest minimum, thus reducing the time and cost of

the mapping programmes. Geological information like disposition of various

lithological units and structures play an important role an identifying the groundwater

potential zone. The aspects of morphography, morphogenesis, morphochronology and

morphometry are vital inputs in the preparation of geomorphological maps.

Information on existing land use / land cover and pattern of the spatial distribution

forms the basis for every development planning. The land use / land cover maps have

to be prepared by adopting visual interpretation techniques in conjunction with

collateral data such as topo maps and census records.

Satellite image interpretation studies, which provided only the qualitative

information earlier, are slowly becoming appropriate for obtaining the quantitative

data of objects. It can help in assessing the environmental system studies like rural

and urban dwelling densities, industrial pollution surface water pollution, oil leakage,

deforestation, soil erosion, forest fire, flooding, land slides, air pollution, dispersion

and circulation, movement of suspended sediments, solid waste dumping

(Deekshatulu 1985). Spectral band of 0.8-1.1 Mm gives much better information on

the water bodies. Lineament mapping is also a very important aspect in ground water

pollution assessment studies as these structures act as the master conduits for pollutant

migration (Ramaswamy and Balaji, 1993).

4.10. EARLIER STUDIES

The aerial photographs were used for geological exploration during early

twenties. Air photo interpretations started only after the fifties. Satellite imageries

77

have been extensively used for regional geological and structural mapping by

Srinivasa et al (1977), Katz (1978), Drury et al. (1980, 1984), Drury (1983a, 1990),

Ramachandran (1991), Ramaswamy et al (1996). Works on encephalon faults and

lineaments of west coast has been carried out using remote sensing techniques by

Ramaswamy (1995). Regional Remote Sensing Service Centre, Indian Space

Research Organization and Airborne Mineral Survey and Exploration Wing,

Geological Survey of India, Bangalore in a collaborative project, namely, project

Vasundhara (1994) have prepared various thematic maps of South India using the

satellite images. Other significant contributions on the application of remote sensing

techniques for geological, structural and lineament mapping were done in other of the

world by Lattman(1964, 1958), Parizek (1967), Badcock (1974), Huntington (1978),

Marianthi Stefouli and Somerton (1983), Moore (1983), Chavez (1983), Waters et al

(1990), Greenbaun (1987, 1992), Goetz et al (1981), Gold (1990), Thirupathy et al

(1996), Kameswara Rao et al (1996), Tamilarasan (1997), Srinivas et al (1977), Nair

(1997), Amit Kumar (1997), Chetty et al. (1997) Subramanian (1997) and Naik

(1998).

The application of remote sensing for ground water exploration has started

from the work of Ray (1960). Extensive hydrogeological studies have been and are

being carried out using remote sensing techniques by the Space Application Centre,

Indian Space Research Organization, National Remote Sensing Agency, National

Natural Resource Management System, Regional Remote Sensing Service Centre and

Karnataka Remote Sensing Technology Utilization Centre, Bangalore. Studies on

water resources and management using remotely sensed data have been carried out by

Balakrishna (1986, 1987), Reddy (1987), Reddy et al (1992), Sabins (1987), Goetz et

al (1975), Pease et al (1973), charon (1974), Fransworth (1984), Sahai et al (1982),

78

Salman (1983), Moore et al (1975), Meijerink (1996), anon (1990), Baweja et al

(1994), Hadanai (1993), Hansman et al (1993), Jayaram et al (1992), Kruck (1990),

Libatao et al (1990), Obeydkov (1990), Sommen (1990), Medeiros (1990),

Krishnamurthy and Srinivas (1995, 1996), Krishnamurthy (1997), Menenti (1993) and

kumar (1987). Studies on the role of remote sensing techniques in ground water

exploration in hard area have been also been done by Sathyanarayana Rao (1983).

Works on the applications of LANDSAT data for hydrogeologic modeling have been

carried out by Rango et al (1983), Davis (1978), Jackson et al (1977), Ragan et al

(1975; 1980) and Slack and Welch (1980). Per Sander et al (1997) attempted to use

the satellite data to analyse different methods of reducibility testing for groundwater

exploration. The use of stereo aerial photo interpretation was described by Goosen

(1978) for soil mapping. Verstappen (1977) used the data products for the study of

geomorphology and similarly, Way (1978) and Townshend (1981) used them for

terrain analysis and Physiography.

4.11. REMOTE SENSING FOR REGIONAL GEOLOGICAL

MAPPING

The IRS-1C and 1D data of WiFS, LISS-III and PAN sensors are found to be

highly useful for geological mapping. The WiFS camera provides the synoptic

coverage of large areas useful for regional scale mapping and understanding. The

multispectral LISS-III data with a spatial resolution of 23.5m is useful for semi

detailed mapping upto 1:50,000 scale. The panchromatic data are found to be useful

for a detailed mapping upto the scale of 1:12,500. Finer geological features like the

traces of bedding and minor joints can be easily identified and mapped. (Map.4.5)

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4.12. IMAGE INTERPRETATION FOR LINEAMENT AND

STRUCTURES

There are basically two stages in an image interpretation and study of lineaments.

1. The correct identification of lineaments that represents crustal fracturing or linear

Zones of thick unconsolidated, coarse material that may overlie buried structures.

2. The correct interpretation and assessment of these features with regard to their like

Control on the groundwater flow. (Waters, 1990).

Some of the main factors that control the analysis of geological lineaments are

as follows:

Stage 1:

1. The Scale of the imagery used.

2. The density of non-geological features present.

3. The orientation of important geological feature.

4. The surface expression of important geological features.

Stage 2:

1. The subsurface morphology of the lineaments.

2. The hydrogeological function of lineaments.

3. The amount of ancillary information available.

The initial image analysis for lineaments should be performed with no prior

knowledge of the detailed geology, geomorphology or hydrology of the area. This is

in order to avoid introducing any operation basin in to an interpretation.

80

The procedure (Pauline Waters, 1990) involves tracing all the lineaments

observed over an aerial photographs or satellite image on to an overlay of temperature

stable transparent film. During this process the image is viewed vertically and

obliquely, in either transmitted or reflected light. This is repeated for each photograph

on at least four separate occasions. On each occasion, the photographs is rotated and

viewed from different directions. For example, on the first occasion, the photographs

is viewed along the south-north direction and then rotated slightly. Elongated lines

orienting in different direction are traced simultaneously. Only those lines that feature

out from two or more of the above said analyzed are included in the final lineament

map. Before the map is finally constructed, it is useful to mount the photographs on

the wall at eye level. This enables the image to be viewed from a distance and from all

directions. In this way many more lineaments can be detected. (Map.4.6)

The map is then screened to remove all man-made lineaments. These include

roads, railways, canals or straight drainage channels and field boundaries. The method

used for this is to make a comparison of all these features with the 1:50,000

topographic maps. The lineament map and the cultural map are reproduced at the

same scale and registered with certain reference points common to both.

Relationship between certain image characteristics (Marianthi Stefouli, 1990) and

the geologic nature of the linear features are indicated as:

1. Faults are expressed as pattern variation on either sides of the fault.

2. Presence of faults and fractures show a change in texture.

3. These structures are also expected to show many variations in relief

depending upon the displacements.

81

4. Longitudinal contacts are expressed as typical boundaries with two or more

textures and tones.

For proper interpretation of an image, a thorough knowledge of the type of

geologic structure and the lithology of the area is also needed (Marianthi Stefouli,

1990). IRS-1B satellite image mosaic plate and in conjunction with toposheet and

field check the major and minor lineaments of the taluk are delineated. And also used

for preparing the Hydrogeomorphological map (Map.4.7) showing pediplain and

pediments, and land use and land cover map demarcating vegetation, forest, land with

scrub and barren and lakes/ water body,(IRS-1B, 26th

January 1994, topographic

sheets 57D/8,57D/12,57D/16, 58A/8,58A/9 and 58A/13 scale 1:50,000.

4.13. IMAGE INTERPRETATION FOR HYDRO GEOMOPHOLOGY

The summer season satellite image and survey of India toposheets are the

main input for the preparation of Hydrogeomorphological map. The geomorphic units

are to be delineated based on the image characteristics. A base map prepared on a

transparent tracing film is placed over a geocoded image and with the help of a light

table, the geomorphic units and form, the structural information like folds, faults,

fractures, lineaments and structural trend lines and the lithology are identified and

incorporated. The regional geological maps, available literature and other field

observations are used in enriching the geomorphological map. The notable

hydrogeomorphic units of structural, fluvial and denudation origin and their lithology

and ground water conditions as analyzed by several workers.

The IRS-1B images captured in January 1994 and the Survey of India

toposheet of 1:50,000 scales have been used for the preparation of

82

hydrogeomorphological map of the present study area. The available geological map

followed by an intensive field check has helped in the identification of various units.

4.14. REMOTE SENSING AS A TOOL IN GROUNDWATER

EXPLORATION

Satellite data have been proved to be highly useful for groundwater studies and

mapping. Remote sensing is an excellent tool for the hydrogeologist and geologists to

better understand and the perplexing problems of groundwater exploration

(Lamoreaux; 1984). But groundwater by its very nature is not available for direct

observation (Farnswooth et al 1994). This remotely sensed data cannot be used

directly but require substantial and to some extend subjective information about an

area to be collected by the interpreter. Shapes, patterns, tones and textures identified

through image analysis provided direct or indirect evidence of features of

hydrogeological interest. These include structures (faults, joints, ductile shears, folds),

intrusions (dukes, veins), distribution of solid and unconsolidated lithologies,

morphology (landforms, erosion surfaces, basin of deeper weathering, present of

ancient drainage systems and pattern, presence of hygrophile and hydrophilic

vegetation and areas of preserved soil moisture during dry-season conditions.

There are basically two approaches in the use of remote sensing as a ground

water exploration technique. The first approach relates the pattern surface and

groundwater flow considering the structures, drainages and physiographic conditions.

The second approach relates to the well yields, along the structurally deformed zones.

Well yields often show a positive correlation with linear features or with interaction

between two features. IRS-1B satellite imagery has been analyzed for the

identification of lineaments and surface water bodies.

83

4.15. GEOGRAPHIC INFORMATION SYSTEM (GIS)

A Geographical Information System (GIS) as defined by the National Science

Foundation is a computerized data base management system used to capture, storage,

retrieval, analysis and display of spatial (e.g. locationally defined) data. The

technology can be used to overlay and combine into a single computerized map that

can summarized geographic, cultural and scientific land attribute. With the release of

software MAP/INFO, a popular GIS software, there is a tremendous user base with a

myriad of application ranging from high level cartography to land use planning,

natural resource arrangement, agriculture, forestry etc. The GIS was used to perform

analysis that was previously too costly or not feasible.

To illustrate this, consider the information needs of a hydrogeologist who

wishes to study the erosion and sedimentation in a watershed. In such an application,

it is critical to be able to identify the likely sources of sediment. At a minimum, this

identification process would involve the study of topographic slope, soil erodability,

and surface runoff characteristics on area if, topographic maps, detailed a soil survey

maps, and land cover maps exist for the area, the analyst would have the raw data

needed for the study. However more often than not, the maps will be at compatible

scales. Besides the scale problem the analyst in this case needs the information

derived from the existing map sources, instead or original mapped data. That is slope

information must be derived from land cover. Hence the following tasks have to be

performed to develop an information base for the analysis

i. For each data source, the map sheets covering the watershed should be carefully

joined together to form one large sheet for each type of data (contours, Soils, land

84

cover). The boundary of the area would then be delineated on each data map and

the map should be converted to common scale.

ii. Next necessary information would be derived from the source map. Slope

information would be determined from the contours shown on the topographic

map. The soil erodability would be derived from the soil map and runoff

potential would be derived from the land cover.

iii. The analyst would then have to merge the three sets of derived information. This

involves interrelating the information sets through the area to locate the areas

where combinations of site characteristics indicate high soil erosion potential.

The information merging procedure was historically performed by a map

overlay method. First each derived data set was prepared on a transparent map sheet.

These maps were coded in grey tones according to the degree of the conditions being

depicted. The darkest areas on the composite map would indicate a combination of

factors representing high potential sediment source areas.

The principal advantages of the map overlay methods are that it requires little

specialized equipment. However, certain difficulties are inherent in this approach. The

task of bringing this data to a common scale format and deriving applicable

characteristics are time consuming and expensive, because they are tailored to a

specific analysis, the overlay sheets may not be applicable to the other studies. It is

difficult to quantify the results of the overlay analysis, since annual computation of

areas on the composite map can be extremely time consuming.

The difficulties of manual overlay techniques are greatly reduced by a

computer coding the land information. Land related data recorded according to

85

location are called Georereferenced data or Geocoded data. A spatially ordered

collection of such data is called a Geobased file.

Computer analyzation of Georeferenced data in the study of soil erosion

potential. In this illustration, the data maps (a) are computer coded with respect to a

grid (b). The data maps are encoded by recording the information category most

dominant in each cell. That is, each cell is assigned a single soil type in the soil data

file, a single land cover type in the land cover file and an average elevation in

topographic file. The task of geocoding the data can be tedious and costly. Yet once

this task is accomplished, the analysis of geocoded data can be performed quickly and

accurately. The job of interpreting characteristics (such as slope, erodability, runoff)

from the original data is simple one for the computer can calculate areas by simple

counting grid cells and multiplying the area of each cell. If the database also

contained information on land ownership, the land owners is the greatest problem

areas can be identified. Derived Proposed changes in vegetation cover and topography

can be analysed in this manner evaluate the visual impact of the changes.

4.15.1. METHODOLOGY

Satellite images (Map.4.8) are interpreted using image/photo interpretation

keys such as color/tone, texture, pattern shape, size association, drainage, topography

etc., to derive hydrogeomorphological maps. This map shows various land forms

present in an area such as pediplain, pediment, and fractures/ Lineament etc., the

texture will vary depending upon terrain (hard rock terrain, alluvial terrain, etc). for

each of the landform groundwater prospects is assigned based on type of landform,

lithology, structure, soils, land use/ land cover, drainage, topography, etc.,

86

Information on various features like lineament, lithology, landforms, land use/

land cover, slopes, drainage, soils etc., are derived using satellite data IRS-1B LISS-

III data (1994) in conjuction with collateral data such as SOI Toposheets, 57D/8,

57D/12, 57D/16,58A/5,A/9 and A/13 in the scale of 1:50,000 and field observations.

This information is integrated to assess the suitability of sites of locate the

groundwater potential zones. Interpretations of various parameters, which control the

occurrence, and movement of groundwater such as Lithology, structures, landforms

etc., are carried out. GIS environment has helped in identifying prospective zones and

integration of various thematic maps. All of these help in further necessitating the

target areas of potential ground water zones.

ANALYSIS

4.15.2. TOPOGRPAHY AND SLOPE ANALYSIS

The taluk is located on an uneven terrain with maximum and minimum

elevations varying between 400-1000 Mts respectively. The higher elevations are

observed in the SW and North of the taluk and the lower elevation in the stream

courses.

Slope is one of the most important terrain characteristics and plays a

vital role in geomorphological and run off processes, soil erosion and Land use

planning. So it is very important to have an understanding of the spatial

distribution of slopes for the development and measurement of both land and water

resources.

The general slope of the taluk is towards N-W & N-E. Very gently sloping

categories (more than 1% and upto 3%) corresponding to weathered portion of the

granite gneisses and schist are observed in the N-S part of the taluk. moderate slopes

87

(Gently slopes) more than 3% up to 5% are observed in the SW part and nearly Level

0-1% are observed in the eastern side of the taluk (Map 4.3).

4.15.3. DRAINAGE AND SURFACE WATER BODIES

In the area drainage represents a fan shaped pattern. The drainage in the taluk

is dendritic (Map.4.1) as is common in granite, schist and gneissic terrain, the stream

in the taluk are first, second, third and fourth order with a ephemeral stream

originating in south and Northern part of the taluk and trending towards the outlet

located in the eastern side of the taluk.

4.15.4. GEOLGOY AND SOILS

Geographically the taluk is covered by the rocks of Archaen age, i.e., granite,

gneisses and schistose rocks (Map.4.9).They comprise essentially gray to pink

granites which also exhibit gneissosity at places the strike of foliation in gneisses is

NW – SE with dip towards NE and the schistose rocks are seen on the North /south

direction. The rocks are coarse to medium grained and after found porphyritic with

phenoicrusts of potash feldspar and schistose rocks shows shistosity.

4.15.5. HYDROGEOMORPHOLOGY

Delineating of various geomorphic units and knowledge about their

groundwater play an important role in the optimum utilization of land resources.

Besides, the information on landforms and geological information like lithology and

structures also help in identifying the groundwater potential zones. The

hydrogeomorphological map has been prepared (Map 4.7) on 1:50,000 scale by

demarcating various geomorphic units / land forms, lineaments using satellite imagery

and in conjunction with geological map and the survey of India topo sheets & field

observation.

88

4.15.6. DESCRIPTION OF GEOMORPHIC UNITS

Pediplain of Granite, Gneiss & schist with Moderate Weathering.

It is a flat surface of pediplain of granite gneiss & schist with 20-60 m. thick

weathered material and covered with soils. It occupies generally the topographically

low areas near stream courses and associated with fractured lineaments. The ground

water prospects in these zones are moderate to good. Very good yields are expected in

this zones when associated with fractures / lineaments. Ground water in these units

mostly occurs in weathered and fractured zones.

Pediplain of Granite, gneiss, and schist with shallow weathering.

This is a flat surface of pediplain of granite, gneiss & schist with weathering

extending up to maximum depth of 20, and covered with the soils. These units

generally occupy relatively elevated regions and occasionally associate with fractures

/ Lineament. Poor to moderate yields of ground water are expected in these units will

help to sink a dug wells. In general, the yields of the wells located in these units are

found to be 100-200 m3/d.

Pediments of granites, gneiss and schist

It is a flat surface of erosional bedrock of granite, gneiss & schist with veneer

of detritus. These units mostly act as run off zones or recharge areas. Groundwater

prospects in these units are less than 100m3/d or sometimes dry.

Fractures / Lineaments

The various geomorphic units in the study area are traversed by lineaments

vertical to sub-vertical and horizontal to sub-horizontal deep-seated fractures. The

89

fractures in the study area are generally associated with topographical depressions and

controlling drainage network. These are trending in N-S, NE-SW, E-W, NW-SE,

NNW-SSE, NNE-SSW directions. The depth of weathering is more in the areas

traversed by lineaments and fractures. Hence, these fractures play a vital role in the

development of ground water in the study area.

4.15.7. LAND USE / LAND COVER

Visual interpretation of Irs-1D LISS III FCC of band 2, 3, 4 on 1:50,000

scale was carried out and various land use/land cover categories were delineated.

To estimate the spatial distribution pattern of land use/land cover in rabi and kharif

season, the satellite data of two seasons was acquired during December 2009– rabi

and October 2010- kharif data were used in the study. The land use/ land cover

classes like dense and hill vegetation land, rock out crops land settlement and

barren land, water bodies land (rivers, streams, lakes etc.) and agricultural land

was delineated based on the image characteristics like tone, texture, shape,

association, background, etc. Forest area occupies the hilly terrain of Southeastern

part, while agriculture land occupies the northeastern part of low lying areas. Land

use describes as the land is used for the different purpose such as agriculture,

settlements or industry, whereas land cover refers to the material such as

vegetation, rocks and water bodies that are present on the surface (Anderson et. al.,

1976; Sankar et.al. 2001) among these terms, land use is more common. The land

use map of the area is prepared by using satellite imagery and are classified as

water body, agriculture, forest, and wasteland and built up land (Map 4.10).