This document summarizes a study that mapped groundwater potential zones in the Muvattupuzha block of Kerala, India using GIS and remote sensing. Key factors like geology, geomorphology, lineaments, drainage density, rainfall, land use, slope and soils were analyzed as layers in GIS. Weighted overlay analysis was used to delineate excellent, moderate and poor groundwater potential zones. Validation with field data found good correlation. The study aims to aid groundwater development and management to address water scarcity in the region.

2. 2

3.  Groundwater is the water located beneath the earth’s
surface in soil pore spaces & fractures of rock formation
 Ground water prospect zonation means identifying and
mapping the prospective ground water zones in an area by
qualitative assessment of controlling factors.
INTRODUCTION
3

4. Mapping of
Ground
Water
Potential
zones
Identification
of GPZ aid in
development &
utilization of
groundwater &
surface water
resources
Eliminates
water scarcity
& improve
the irrigation
practices
Increase
agricultural
income &
standard of
living
4

5.  GIS is a very powerful tool for processing, analyzing &
integrating spatial data sets.
 Remote sensing serves as the preliminary inventory
method to understand the groundwater
prospects/conditions.
GIS & Remote
Sensing
5

6. GIS gives
valuable data on
geology,
geomorphology,
lineaments &
slope
Help in
systematic
integration of
data for
exploration &
delineation of
potential zones
With the
advent of RS &
GIS
technologies,
the mappings
of potential
zones is easier
6

7. OBJECTIVE
7

8. STUDY AREA
 Study area selected in this study is Muvattupuzha block
which is situated near Muvattupuzha river basin.
 It is having an area of 225.36 sq.km.
 Muvattupuzha river is one of the major perennial rivers in
central Kerala.
8

9. 9

10. Why Muvattupuzha?
 Muvattupuzha has got varied topography.
 Muvattupuzha receives ample rainfall, still it faces water scarcity,
at times.
 So far, according to our concern, it is one the best blocks with
varied topography and also,the one which is located nearer to our
residing points. Hence it is convinient for us in every ways.
10

11. LITERATURE REVIEW
11

12. Authors Year Review
Surajith Murasingh,
Ramakar jha
2013 Various groundwater
potential zones in Tensa
valley, India have been
delineated using RS sensing
and GIS techniques.The
layers such as base, DEM,
drainage density, contour,
land use, lineament density
etc were used and finally the
GIS weighted overlay
analysis was done.
Y. Yaswanth Kumar, D.V.
Satyanarayana Moorthy, G.
Shanmuka Srinivas
2017 The Digital Elevation Model
(DEM) has been generated
from the 20 m contour
interval contour lines
derived from SOI
toposheets. The layers used
were the same as above.
12

13. Baswadraj D.B. et.al 2016 Conducted a case study to
find out the groundwater
potential zones in
Dodahalla Watershed,
Belagavi
andKarnataka.The layers
used were the same and
the final GIS weighted
overlay analysis was done.
Preeja K. R et al 2011 The same layers were
gathered from Landsat ETM
+ data and Survey of India
(SOI)toposheets of scale
1:50,000 .
N.S. Magesh et al 2011 Various ground water
potential zones has been
delineated in the Theni
district of Tamil Nadu .The
layers used were the same
and the final GIS weighted
overlay analysis was done.13

14. SOFTWARE USED
 ArcGIS 10.3 of Esri was used as the spatial platform for
integrating various maps.
 ArcGIS deals with information on location patterns of
features and their attributes.
14

15. 15

16. Collateral Data
GIS Weighted Overlay Analysis
Ground Water Potential Map
Validation
Geology
Geology
Lineament
density
Drainage
Drainage
Density
Slope
Rainfall
Soil
Satellite
16
DEM
Geomorphology
LULC
Water Depth
Field
Data
GWD
Data
Interpolation

17. 17
Details of data Collected:
• Digital Elevation Model (DEM) was obtained from ASTER
and updated using Toposheet of 1:25000 scale.
• Map of Muvattupuzha block was obtained from Kerala State
land use board.
• Drainage, drainage density and slope maps were obtained
from DEM map.
• Geology, Geomorphology, land use land cover(LULC) and
lineament density maps were obtained from Kerala State
Land use board.
• Annual rainfall data for the period 2016-17 was got from
metrological Department , Thiruvananthapuram.
• Soil map was got from the Dept. Of soil survey & soil
conservation.
• Ground water level data was collected from Groundwater
Department, Kakkanad.

18. IDENTIFICATION OF CAUSATIVE
FACTORS
1. Drainage density
2. Slope
3. Geology
4. Geomorphology
5. Soil
6. Lineament density
7. Rainfall
8. Land use land cover
18

19. Digital Elevation Model (DEM)
• A digital elevation model is a digital model or 3-D representation
of a terrain's surface created from terrain elevation data
• In this study, DEM was downloaded from ASTER.
• It was used to analyse drainage, drainage density and slope of the
study area.
• Using extract tools the DEM of study area was extracted.
19

20.  Input study area map into GIS
20

21.  Input actual well locations
21

22. In catalog select new shape file.In feature
type select polygon
In editor toolbox select start editing and click on
the required template
Begin digitizing the Feature you want to create
and click on stop editing and save edits.
select Spatial analyst toolset. Click on extract by
mask
Input raster data (DEM) & shape file of the
boundary to get DEM map
22
PREPARATION OF DEM

23.  Digitizing:It is the process of converting any feature of a paper
map into digital format.
23

24.  Extraction Of DEM
24

25. 25

26. 1.Drainage
and
drainage
density map
This map
consists of water
bodies, rivers,
tributaries,
streams,
ponds.The
Hydrology tools
are used to
extract
hydrologic
information
from a DEM.
Drainage
density is
defined as the
closeness of
spacing of
stream channels
It is an inverse
function of
permeability.
26

27. In spatial analyst extension of hydrology
toolset, select fill tool
Click on flow direction .Select flow
accumulation
To get the streams, click on map algebra.
Select raster calculator. Give accumulation
>1000
click on stream order & input the map to
obtain drainage map
In conversion tools, select raster to
polyline.From spatial analyst extension,
select line density. 27

28.  Fill tool:Fills sinks in a surface raster to remove small
imperfections in the data.
28

29.  Flow direction:indicates the direction of steepest descent
from that cell.
29

30.  Flow accumulation:It tabulates for each cell the no. of cells
that will flow to it.
30

31. Raster calculator
31

32.  Stream order
32

33. 33

34.  Converting raster to vector
34

35.  Line density tool
35

36. 36

37. 2. Slope
map
Slope is the rate
of change of
elevation. It
determines the
gravity effect on
the water
movement.
Slope map is
obtained from
DEM using surface
toolset of spatial
analyst.
37

38. 38

39. 39

40. 3.Geology
Map
The water-
bearing
properties vary
from one rock
type to another
rock type.It
depends on
compactness of
the
rocks(porosity&
permeability)
The study area
consists of basic
rocks,Charnokite,K
hondalite,and
Migmatite
complex.
40

41. 41

42. 4.Geomorphology
Map
Geomorphologi
cal maps portray
important
geomorphic
units, landforms
and underlying
geology .
A systematic study
of these maps are
helpful for
selecting ground
water potential
zones and artificial
recharge sites. This
information
provides a reliable
base for effective
planning,
development and
management of
groundwater
resources of an
area. 42

43. 43

44. 5.Soil
Map
The rate of
infiltration
depends on
grain size of
soil.
Different types
of soils in the
study area are :
Alluvium
Hill soil
Laterite
44

45. 45

46. 6.Lineament
density Map
Lineaments
represent zones
of faulting and
fracturing
resulting in
increased
permeability.
They act as path
ways for ground
water
movement.
Area with high
lineament density
are good for ground
water potential
zones.
46

47. 47

48. 7.Land Use
And Land
Cover map
Land use refers
to man’s
activities in
land, various
uses which are
carried out on
land.Land cover
denotes the
natural
vegetation,
water bodies,
rocks.
LULC affects
evapotranspiration
volume, timing and
recharge of ground
water system.
48

49. 49

50. 8.Rainfall
map
It determines
the amount of
water that
would be
available to
percolate into
the groundwater
system.
The data obtained
from IMD was
spatially
interpolated using
Inverse Distance
Weighted (IDW)
method to obtain
the rainfall
distribution map.
50

51. 51

52. Assessment of ground water
potential zones
WEIGHTED OVERLAY ANALYSIS
 All the thematic maps are overlaid in terms of
weighted overlay Analysis (WOA) using the spatial
analysis tool in ArcGIS 10.3.
 The advantage of WOA is that human judgement can
be integrated with analysis.
52

53. 53

54.  A weight or percentage influence represents relative
importance of parameter and the objective.
 The ranks have been given for each individual parameter of
each thematic map depending on its potentiality.
The ranks
 1 denotes very poor
 2 denotes poor
 3 denotes moderate
 4 denotes high
 5 denotes very high
The weights and rank have been chosen based on judgement
of researchers who had carried out similar work on ground
water potentiality mapping.
54

55. 55
Sl No. Parameter Classes Rank Weight
1. Geomorphology Valley 5 16
Lower plateau 4
Denudational hills 2
Flood plain 5
Structural hills 2
Residual hills 4
2. Slope Nearly level (0-5.026317) 5 19
Very gently sloping (5.02631-9.494) 4
Gently Sloping (9.4941-14.799712) 3
Moderately Sloping (14.799-22.897) 2
Strong Sloping (22.8976-71.206161) 1
3. Drainage
density(km/km2)
Very low (0-53.90919525) 5 11
Low (53.90919525-138.28880) 4
Medium (138.28880-234.38780) 3
High (234.38780-351.5817081) 2
Very high (351.58170-597.6889) 1
4. Lineament
density(Km/Km2)
Very low (0-0.259872993) 1 9
Low (0.2598729-0.7337590) 2
Medium (0.733759-1.13885) 3

56. 56
Sl.no. Parameter class ran
k
weight
5. Land use/land cover Built up land 4 13
Paddy area 4
Rocky area 1
Mixed crop 4
Forest 2
Cultivable waste land 2
Water body 5
6. Rainfall(mm) Moderate (2709.62-2958.413) 3 22
High (2958.413-3134.41) 4
Very High (3134.41-3436.25) 5
7. Geology Basic rocks 3 4
Charnockite 3
Khondalite 4
Migmatite complex 3
8. Soil Hilly soil 2 6
Laterite 4
Alluvium 5

57. GROUND WATER POTENTIAL ZONE
 The generated output shall consist of various classes of
ground water potential zones namely Excellent,
Moderate and Poor Zones from ground water potential
point of view
57
Table 3 Area statistics of different Groundwater Prospect Zones
Category of
ground water
potential
zone
Area in Km2 Area in %
Excellent 27.672 12.28
Moderate 148.31 65.81
Low 48.30 21.43

58. 58

59. Validation
 In order to validate the classification of ground water
potential zones obtained by remote sensing and GIS
based ground water potential map,data on existing
well were collected by field investigations and enqiury.
 This data was cross-checked by using data obtained
from ground water department for the year 2016-17.
59

60. 60
Sl.No. Place name Latitude Longitude Depth to water level in
meters
Average
depth in
metres
Minimum Maximum
1 Perumattom 9.9934844 76.5960512 1.78 4.87 3.325
2 Thrikkalathoor 10.0294243 76.5491221 0.65 5.16 2.905
3 Pezhakkapily 10.0145626 76.5669526 1.98 6.14 4.06
4 Arakuzha 9.9293692 76.5957139 2.03 5.35 3.69
5 Arakuzha 9.96229 76.58473 1.08 7.45 4.265
6 Kadalikad 9.9237669 76.6742785 0.67 6.72 3.695
7 Kumaramangalam 9.9350273 76.708533 0.9 2.89 1.895
8 Paingottor 9.9914808 76.7067144 0.62 3.72 2.17

61. 9 Pulinthanam 10.0051014 76.6684829 2.13 7.17 4.65
10 Kalloorkadu 9.9687875 76.6609538 2.2 3.85 3.025
11 Kalloorkadu 9.970022 76.660516 1.13 4.28 2.705
12 Vazhakulam 9.9455851 76.6370999 2.35 4.29 3.32
13 Kadathi 9.981 76.551 1.02 5.15 3.085
14 Vettikavu 9.9819 76.5208 0.88 3.56 2.22
15 Koikkadu 9.9588 76.550063 1.21 6.61 3.91
16 Marady 9.95505 76.558178 1.28 4.06 2.67
61

62. 62

63. Conclusions
Remote sensing and GIS techniques has helped in:
 efficient use of cost, time, and labour.
 integration of eight thematic maps such as drainage
density, rainfall, LULC, slope, geology, geomorphology,
lineament density and soil which gives information to
local authorities and planners about the areas suitable for
groundwater exploration.
 Generation of ground water potential map of the area.
 To extract useful information from satellite images.
63

64. Conclusions
 The excellent zones are distributed along the
lineaments
 The area around the alluvial plain, low slope, flat
topography near river plain is good in groundwater
prospects.
 Areas with high slope, high-drainage density, low
lineament density are poor to very poor in
groundwater prospects.
64

65. Conclusions
 Geological characteristics,lineament, drainage and
slope shows direct influence on ground water
conditions in the study area.
 Drainage density is an inverse function of
permeability. The less permeable a rock is, the less
infiltration of rainfall.
 Subsequent validation with boreholes/well yield data
revealed a good correlation with respect to the
observed groundwater potential zonation.
65

66. FUTURE SCOPE
 Aid in proper development and utilization of groundwater
resources for eliminating water scarcity and thereby
improving the irrigation practices and agricultural income
for standard living conditions of the society
 The study can be further extended to identify the sites and
suitable artificial recharge methods for augmentation of
groundwater resources in moderate and poor potential
zones.
 Gives information to local authorities and planners about
the areas suitable for groundwater exploration in order to
ensure sustainability of well yields and counter the
problem of water table depletion.
66

67. FUTURE SCOPE
 Provide sufficient support in groundwater studies
where the region lacks previous hydrogeological
investigations and data.
 Useful for various purposes such as sustainable
development of groundwater as well as
implementation of water conservation projects and
programmes in the area.
67

68. REFERENCES
 Y Yashwanthkumar, D V Sathyanaryana
Moorthy,GShanmukhaSrinivas,“identification of ground water potential zones
using GIS ”The international journal of civil engineering and technology ,march
2017,pp. 01-10.
 Basavaraj DB ,CG Hiremth, J Davithuraj, B K Purandara “Identification of
ground water potential zones using ARC GIS 10.1” International Journal of
Advances in mechanical and civil engineering, September 2016.
 Preeja KR, SabhuJoseph,Jobin T homas , Vijith H “identification of groundwater
potential zones of a tropical river basin(Kerala, India) using GIS and remote
sensing techniques” Journal of the Indian society of Remote sensing, February
2011.
 ML Waikar and Adithya P Nilawar, “identification of ground water potential
zones using GIS techniques” International Journal of Innovative Research in
Science ,Engineering and Technology, May 2014.
 KamalKUBarik,DalaiPC,GoudoS.P,PandaSR,Nandi D, “Delineation of
Groundwater Potential Zone in Baliguda Block of Kandhamal District, Odisha
using Geospatial Technology Approach” ,International Journal of Advanced
Remote Sensing and GIS,pp. 2068-2079.
68

69.  GirishGopinath,“IntegratedHydro geological survey of the
muvattupuzha river basin ,Kerala ,India.”, August 2003.
 M. Nagarajan and Sujith Singh “Assessment of Ground water potential
zones using GIS”, Journal of the Indian society of Remote sensing, March
2009.
 PankajKumar,SrikanthaHerath,RamAvtar,Kazuhiko Takeuchi, “
Mapping of groundwater potential zones in Killinochi area, Sri Lanka,
using GIS and remote sensing techniques” Sustainable Water Resource
Management, September 2016.
 N.S. Magesh, N. Chandrasekar, John Prince Soundranayagam,
“Delineation of groundwater potential zones in Theni district, Tamil
Nadu, using remote sensing, GIS and MIF techniques.” ,February 2012.
 Surajith Murasingh,Ramkar Jha“Identification of Groundwater
Potential Zones Using Remote Sensing and GIS in a mine area of
odhisha”,July 2015.
69

70.  S.Anirudhan,M.Sundararajan,R.G.Rejith,”Nature of Groundwater
Occurrence in hardrock terrain:Kerala,India.”,March 2017.
 Abdul Azeiz Hussain,Vanum Govindu,Amare Gebre Medhin
Nigguse,”Ground water Potential Using Geospatial
Techniques”December 2015.
 Jesiya N.P,Girish Gopinath,”Delineation of Groundwater Potential
Zones in Selected Urban and Peri-Urban Clusters of Kozhikode
District,Kerala,India”,April 2015.
 RamuMahalingam B,Vinay M,”Identification of Groundwater
Potential Zones Using GIS and RS : A case study of Mysore
Taluk:Karnataka”,March 2014.
70

71. THANK YOU
71

72. LITERATURE REVIEW
1.Surajit Murasingh, Ramakar Jha (2013)
 Various groundwater potential zones in Tensa valley,
India have been delineated using remote sensing and
GIS techniques.
 Various maps (i.e., base, DEM, drainage density, contour,
land use, lineament density and groundwater prospect
zones) were prepared using the remote sensing data
along with the existing maps.
 Base map and DEM were transformed to raster data
using feature to raster converter tool in ArcGIS 9.3
version. 72

73. 2.Y. Yaswanth Kumar, D.V. Satyanarayana Moorthy, G.
Shanmuka Srinivas(2017)
 The various thematic maps are Boundary, Drainage,
DEM,Drainage Density, Slope, Soil, Lineaments, Land Use/ Land
Cover, Rainfall maps.
 The Digital Elevation Model (DEM) has been generated from the
20 m contour interval contour lines derived from SOI toposheets.
 The Slope map has been prepared from DEM. These maps have
been overlaid in terms of weighed overlay method using Spatial
Analysis tool in Arc GIS 9.3.
 During weighed overlay analysis, the ranking has been given for
each individual parameter of each thematic map and weights were
assigned according to their influence.
73

74. 3.BASAVARAJ D.B et al.(2016)
 conducted a case study to find out the groundwater potential
zones in Dodahalla Watershed, Belagavi andKarnataka, India with
an aerial of 320.20 km2.
 The thematic maps such as geomorphology, land use / land cover,
slope, soil,lithology and drainage map were generated for the
study area.
 The groundwater potential zones are generated by overlaying all
the thematic maps in terms of weighted overlay method using the
spatial analysis tool in ArcGIS 10.1.
74

75. 4.Preeja K. R et al.(2011)
 The information on geology, geomorphology,lineaments,
slope and land use/land cover was gathered from
Landsat ETM + data and Survey of India
(SOI)toposheets of scale 1:50,000 in addition,
 GIS platform was used for the integration of various
themes.
75

76. 5.N.S. Magesh et al(2011)
 Various Groundwater potential zones for the assessment of
groundwater availability in Theni district have been
delineated using remote sensing and GIS techniques.
 Survey of India toposheets and IRS-1C satellite imageries are
used to prepare various thematic layers viz. lithology, slope,
land-use, lineament,drainage, soil, and rainfall were
transformed to raster data using feature to raster converter
tool in ArcGIS.
76

77. 6.Thilagavathi N et al(2011)
 RS & GIS techniques have been used to map the groundwater
potential zones in Salem Chalk Hills, Tamil Nadu, India.
 Satellite imageries were also used to extract lineaments,
hydrogeomorphic landforms, drainage patterns, and land
use, which are the major controlling factors for the
occurrence of groundwater.
 Various thematic layers pertaining to groundwater existence
such as geology, geomorphology, land use/land cover,
lineament, lineament density, drainage, drainage density,
slope, and soil were generated using GIS tools.
 By integrating all the above thematic layers based on the
ranks and weightages, eventually groundwater potential
zones were demarcated.
77

78. 7.Ramu et al(2014)
 Conducted a study to analyse the ground water potential
zones in Mysore Taluk.
 Totally nine parameters have been consider for the study
such as drainage density, elevation, geology, geomorphology,
land use and land cover, lineaments, rainfall pattern, slope
gradient and soil texture.
 The selected parameters have been prepared and classified
in GIS environment, then weightage for each parameters and
its classes have been assigned using Analytical Hierarchical
Process, then weighted overlay analysis inArcGIS used to find
out the result.
78

79. 8.M.L.Waikar and Aditya P. Nilawar (2014)
 The accurate information to obtain the parameters that can
be considered for identifying the groundwater potential zone
such as geology, slope, drainage density, geomorphic units
and lineament density are generated using the satellite data
and survey of India (SOI) toposheets of scale 1:50000.
 It is then integrated with weighted overlay in ArcGIS.
 Suitable ranks are assigned for each category of these
parameters.
79

80. 9.Kamal Ku. Barik et al (2017)
 GPZ are demarcated with the help of geospatial techniques.
 The parameters, considered for identifying the GPZ such as
geology, geomorphology, slope, drainage density, lineament
density, rainfall, soil and landuse and land cover (LULC) are
generated using satellite data and toposheet.
 Later, they are integrated with each other applying weighted
overlay in ArcGIS. Suitable ranks are assigned for each
category of these parameters.
80

81. 10.Girish Gopinath(2003)
 Demarcated the groundwater potential zones in the
Muvattupuzha river basin different thematic maps were
prepared in 1 :50,000 scale from conventional data and
remotely sensed data.
 The thematic maps on resistivity , lithology ,drainage map
and contour map were prepared using the data obtained
through field investigation, from secondary sources and
Survey of India topographical sheets in 1 :50,000 scale
 hydrogeomorphology , lineament map and , landuse were
prepared using Indian Remote Sensing Satellite
81

82. 11.M.Nagarajan(2009)
 The thematic maps such as geology,geomorphology,soil
hydrological group,land use,land cover and drainage map
were prepared for study area.
 The ground water potential zones were obtained by
overlaying all the thematic maps in terms of weighted overlay
method using the spatial analylis tool in ArcGIS 9.2.
82

83. 12.Pankaj Kumar et al(2016)
 GPZ maps are generated using remote sensing and
geographic information system (GIS) for Killinochi area,
Northern Sri Lanka.
 Five different themes of information such as
geomorphology, geology,soil type (extracted from
existing topo sheet)
 slope [generated from shuttle radar topography mission
(SRTM) digital elevation model (DEM)]
 land use/land cover (extracted from digital processing of
AVNIR satellite data) were integrated with weighted overlay
in GIS to generate groundwater potential zonation map of
the area.
83

84. 13.JESIYA N P AND GIRISH GOPINATH(2015)
 An integrated approach has been made in the study to
identify groundwater potential zones in the urban
and Peri-Urban Clusters of Kozhikode district, Kerala.
 Interpretation of remotely sensed data is carried in
conjunction with the existing information and groundwater
level data from the fieldwork to map the controlling and
indicative parameters, and integrated these parameter layers
in the GIS environment using Weighted Index Overlay
Analysis (WIOA) method.
84

85. 14.Vanum Govindu et al
 eight major biophysical and environmental factors like
geomorphology, lithology, slope, rainfall, landuse land cover
(LULC), soil, lineament density and drainage density were
considered
 weighted valuedetermination for each factor and its field
value was computed using IDRSI software. At last, all the
factors were integrated together and computed the model
using theweighted overlay so that potential groundwater
areas weremapped.
85

86. 86