Role of Remote sensing and GIS in Ground water studies –Potentials. Constaints and case studies – By Dr S K Srivastav. Isro Dehradun

1. Role of Remote Sensing & GIS in
Ground Water Studies
Potentials, Constraints and Case Studies
Dr. S.K. Srivastav
Indian Institute of Remote Sensing
(National Remote Sensing Centre)
ISRO, Dept. of Space, Govt. of India
Dehra Dun
e-mail: sksrivastav@iirs.gov.in

2. Background
RS data provide only the surface or near-surface information; therefore, a link must
be established between the surface observation and the subsurface (groundwater)
phenomena (Jackson, 2002).
Of all the hydrological applications of remote sensing, the hydrogeological analysis is
one of the most difficult tasks (Farnsworth et al., 1984).
However, the spatially complete and temporal nature of the RS data provide excellent
opportunities to hydrogeologists for improving the understanding of the hydro-
geological system, especially in remote and unexplored areas (Hoffmann and Sander,
2007).
Since RS data have limitations with regard to depth penetration, the best approach is
to integrate the airborne, space-borne and ground-based remote sensing techniques
with field measurements (Meijerink et al., 2007).
The RS data are most useful when they are combined with GIS and numerical
modelling (Becker, 2006).
iirs/nrsc/nrsc/isro

3. Potentials and constraints
VIS-NIR-SWIR Region
Mapping of surface features of hydrogeological relevance (or g.w. indicators)
for understanding the controls of ground water occurrence and movement .
These include – lithologies, structures, geomorphology, drainage patterns,
land use / land cover and soil moisture.
The amount of information which can be extracted from RS data depends on many
factors – type of data including spatial and spectral resolutions, scale of image,
date of acquisition of the image, type and knowledge of terrain, experience/ skill
of the interpreter, etc.
Mapping and monitoring the spatial distribution of ground water exfiltration (effluent
streams) and infiltration (influent streams) zones.
However, quantifying the magnitude of flux from space is still a major challenge
Moist soils, swampy/waterlogged zones and vegetation (in dry climate) indicate
ground water occurrence at shallow depth.
However, quantification of soil moisture not possible. Further, in humid areas,
the relation between g.w. and vegetation is complex and does not readily indicate
g.w. occurrence.
iirs/nrsc/nrsc/isro

4. DEMs generated using stereo images can be used to map the topographic attributes
of the terrain.
Spatial distribution and quantification of the magnitude of actual evapotranspiration rates
(i.e. g.w. discharge by natural process and net draft for irrigation in g.w. irrigated areas)
along with TIR and meteorological data.
Absolute values estimated using SEBAL technique are often overestimated,
however, the strength of RS data lies in providing the spatial patterns of g.w. use.
Salt crusts provide an indication of high water table and also throw light on
g.w. quality.
iirs/nrsc/nrsc/isro

5. Thermal Region
Mapping moist soils and shallow water table areas.
However, quantitative and temporal measurements of soil moisture are difficult.
Mapping discharge of ground water into rivers, lakes and sea.
Possibility of detection of such ground water discharges depends on temperature
contrast and quantum of g.w. discharge. Quantification of g.w. discharge also
not possible.
Quantifying the spatial distribution of actual evapotranspiration rates in
conjunction with VIS-NIR-SWIR and meteorological data.
High resolution thermal images useful for mapping geothermal vents,
hot springs, finding relation between distribution of hot springs and
lineaments.
iirs/nrsc/nrsc/isro

6. Microwave Region
Most suitable for mapping spatial distribution and temporal dynamics of soil moisture.
Present configuration of microwave sensors provides soil moisture information
restricted to 0–2 cm, and to areas free of dense vegetation cover. Coarse spatial
resolution of the order of few kilometers is another major constraint.
Detection of buried channels and palaeo-drainage up to certain depth (~ 2 m).
Limited to only in hyper-arid conditions and in absence of surface cover.
Generation of high-resolution digital elevation models (DEMs) using SAR
data with a technique called radar or SAR interferometry (InSAR).
Provides digital surface model (DSM) rather than digital terrain model (DTM).
Height accuracy is of the order of few meters, therefore, elevations can not be
directly used in quantitative g.w. flow modelling studies.
iirs/nrsc/nrsc/isro

7. Subtle changes in land surface elevation due to ground water withdrawal
or recharge from/to the aquifers in unconsolidated sediments can be
detected using a technique called differential radar interferometry (D-InSAR).
The limitations include – (1) low availability of suitable InSAR images;
and (2) Temporal decorrelation of radar signal due to change in
land cover and atmospheric conditions.
Measuring surface water elevation using Radar altimetry at sub-meter
accuracy.
However, the coarse spatial resolution limits its applicability only to large lakes
and wetland systems.
iirs/nrsc/nrsc/isro

8. GRACE – A special satellite mission for quantifying seasonal and
inter-annual variations in terrestrial water storage
GRACE – Gravity Recovery and Climate Experiment (launched by NASA & DLR
in 2002)
Principle - Spatio-temporal changes in mass distribution causes perturbations in the
orbits of twin satellites, separated by about 220 km, inducing change in the relative
distance between two satellites, which is used to map the gravity field.
Accuracy estimates for interannual and seasonal water storage variations are of the
order of 9 mm (at 1300 km resolution) and 10–15 mm (for area >2 million km2)
water equivalent, respectively (Guntner et al., 2007).
For estimating ground water recharge, storage changes due to other components
of terrestrial water storage such as snow, surface water (rivers, lakes and wetlands),
soil moisture, and biomass are separated using auxiliary observations and
numerical models .
Coarse resolution limits its applicability to study ground water dynamics at basin/
continental/ global scale (>900,000 km2 )
iirs/nrsc/nrsc/isro

9. RS & GIS applications in ground water
Mapping of prospective ground water zones,
Ground water quality zonation including finding zones vulnerable to
pollution,
Site selection for artificial ground water recharge structures,
Inputs in ground water budgeting,
Upscaling of aquifer related parameters/ recharge rate,
Ground water information management, etc.
iirs/nrsc/nrsc/isro

10. Infiltration Vs. Exfiltration Zones
(Examples: Doon Valley & Indo-Gangetic Plain
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11. A few conspicuous landforms
(Example: part of Spiti Valley)
Ground photo
IRS LISS-3 Image
Ground photo
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12. G.W. carriers and barriers
(Examples: S. India)
iirs/nrsc/nrsc/isro

13. Surface manifestation of faults on satellite imagery
vis- a-vis hydrogeological section
(Example: Doon Valley)
R.
na
45 0
mu
±
47 5
Ya
F
500
42 5
55
77 5
0
500
60 0
550
57 5
60 0
Legend
5
57
Nagsidh 55
F Piezometric Head (m amsl)
Hill
475 50
0
0
500
(contour interval = 25 m)
Surface/Ground Water Divide
475
450
450
Direction of Ground Water 400
.
Movement
aR
Hills 0
ng
0 5 10 20 35
Ga
River / Stream
Kilometers
1
F 2
50 m Dehradun Southern
F 3
4
Fan Piedmont
5 7
6
1
2
Dehradun Southern
3
Fan Piedmont
4
5 7
6
25 m
Tube Well 2 km
100 m
Topographic Surface
2 km
Piezometric Surface High-permeability facies
Low-permeability facies
Intermediate-permeability facies Tube Well Aquifer Tapped Piezometric Surface/SWL
(Source: Srivastav, 2008) iirs/nrsc/nrsc/isro

14. Case Studies

15. Ground Water Potential Zoning
Segmentation or Hydrogeomorphic Approach
using Satellite Imagery
(Example – RGNDWM Project)
GIS-based Integration of relevant data layers
(Example – Doon Valley)
iirs/nrsc/nrsc/isro

16. RGNDWM Project
Methodology
IRS- LISS-III Data
WGS 84 - UTM
SOI toposheets
SOI toposheets On screen Existing
Existing
WGS 84 -- UTM
WGS 84 UTM interpretation maps
maps
Base map Lithological Structural Geomorphic Hydrological
overlay map overlay Map overlay Map overlay Map overlay
Integration
Hydrogeomorphic units
Evaluation of Identification of Observation
Observation
ground water locations for Well data
Well data
prospects recharge structures
Map composition using GIS
Ground water prospects map on 1: 50,000 Scale
Geodatabase of ground water
National Remote Sensing Agency
iirs/nrsc/nrsc/isro

17. iirs/nrsc/nrsc/isro

18. RGNDWM Project
Details of Map Legend:
Lithological, Geomorphological, structural, Hydrological &
base information along with ..
1. DEPTH TO WATER TABLE
2. RECHARGE CONDITIONS
3. NATURE OF AQUIFER MATERIAL
4. TYPE OF WELLS SUITABLE
5. DEPTH RANGE OF WELLS
6. YIELD RANGE OF WELLS
7. SUCCESS RATE OF WELLS
8. QUALITY OF WATER
9. STATUS OF GROUND WATER EXPLOITATION
10. TYPE OF RECHARGE STRUCTURES SUITABLE
11. PRIORITIZATION OF AREAS FOR RECHARGE
STRUCTURES
12. REMARKS / PROBLEMS / LIMITATIONS
iirs/nrsc/nrsc/isro

19. RGNDWM Project
States covered
Phase-I
Andhra Pradesh (part) 247
Karnataka 267
Kerala 67
Madhya Pradesh 458
Chhattisgarh 202
Rajasthan 413
Phase-II
Jharkhand 129
Himachal Pradesh 91
Gujarat 210
Orissa 220
Total Sheets Covered = 2304
iirs/nrsc/nrsc/isro

20. RGNDWM Project
Work in progress (Phase-III)
Phase Coverage No. of Schedule /
Maps Status
I 6 States 1654 Completed
II 4 States 650 Completed
III A 6 States 1290 In progress
(Sept 07- Sept 09)
B 4 States 339 Recently Launched
(June 08 – June 10)
Phase-III A Phase-III B
Sl. No. State No. of Maps Sl. No. State No. of Maps
1 AP (part) 204
1 Arunachal Pradesh 120
2 Assam 103
3 Jammu & Kashmir 360 2 Haryana 73
4 Maharashtra 455 3 Uttar Pradesh (part) 88
5 Punjab 82 4 West Bengal (part) 58
6 Uttarakhand 86
Total 339
Total 1290
iirs/nrsc/nrsc/isro

21. RGNDWM Project
A sample map (53J/4) of Uttarakhand (Phase-III)
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22. RGNDWM Project
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23. RGNDWM Project
Feedback on the use of Ground Water Prospects Maps by State Govts.
upto October 2008
State No. of Success No. of Recharge
wells rate Structures
Drilled Planned Constructed
Andhra- Pradesh 43827 93% 478 478
Chhattisgarh 33413 92.5% 1155 327
Karnataka 47951 95% 2641 2589
Kerala 7730 92% 65 8
Madhya Pradesh 22006 90% 5190 3361
Rajasthan 98994 85 – 95% 320 320
Gujarat 12014 94.3 % 470 29
Orissa 292 92% Nil Nil
Total 266227 10319 7112
iirs/nrsc/nrsc/isro

24. GIS-based Integration
(Example: Doon Valley, Uttarakhand)
R. 4 Intermontane Valley Part
na
±
Ya
mu
Vikasnagar
As 2a
Mussoorie ±
an
R. Sahaspur
y
lle
Va
2b
on
Do
Dehra
Dun Legend
1
Sw GW
MB Prospects
T
MBT 0.10 - 0.39 Poor
Litho/Geom boundary 0.39 - 0.58 Poor to Moderate
ey
Water Divide
Doiwala
all
0.58 - 0.68 Moderate to Good
V
Road
on
Rail 0.68 - 0.81 Good to V. Good
Do
District boundary
So Rishikesh 0.81 - 1.0 V. Good to Excellent
River/stream ng
R.
Settlement R. Hill/Scarp zone
0 5 10
a
ng
3 Lineament (Thrust/Fault/Fracture) Kilometers
Ga
(d) (b)
Ya
mu
na
R.
± Hilly/Mountainous Part
±
Dehra Dun Legend
GW
Sw Pros-
pects
0.1 - 0.2 V. Low
0.2 - 0.32 Low (Source: Srivastav, 2008)
0.32 - 0.45 Low to Moderate
0.45 - 0.61 Moderate to Good
0.61 - 0.95 Good to V. Good
R.
0 10 20
0 5 10
a
ng
Ga
Kilometers Kilometers
iirs/nrsc/nrsc/isro

25. Data Layers (hill / mountainous part)
(a) lithology; (b) lineament density; (c) dip-direction and slope-aspect relation; (d) relief; (e) curvature; (f) plan curvature;
(g) profile curvature; (h) slope; (i) log of specific catchment area; (j) topographic wetness index.
(Source: Srivastav, 2008) iirs/nrsc/nrsc/isro

26. Data Layers (valley part)
(a) geomorphology; (b) lithology; (c) depth to potentiometric surface; (d) distance to aquifer boundary; (e) distance to
perennial stream; (f) distance to valley axis; (g) slope; (h) drainage density; and (i) recharge source.
(Source: Srivastav, 2008) iirs/nrsc/nrsc/isro

27. D-InSAR technique for detecting land subsidence due to
ground water withdrawal
(Example: Kolkata city)
GW2 GW2
3 0.0 3
1.0 0.0
2.5
L1 5.0
3.0 GW2 L1 GW2
4.0 4 4
L3 L3
L2
L2
Average subsidence Average subsidence
rate = ~5mm/year rate = ~6.5mm/year
(Max.) (Max.)
L1 : Machhua Bazar .
. GW23 and GW24: Piezometric pressure observation
L2 : Calcutta University 1.0
points
L3 : Rajabazar Science College Subsidence contour with figures in mm/year
Estimated rate of subsidence during 1992–98 = 5 – 6.5 mm/y
IHS colour composition of the interferograms showing subsidence fringes in Kolkata City during the
1990s due to ground water withdrawal
(Source: Chatterjee et al., 2007) iirs/nrsc/nrsc/isro

28. 1. Rat-hole type coal mines and AMD
Study under M.Sc. Geohazards Research
(Blahwar, 2010)
• Coal is extracted by an
artisanal method of mining
called as “rat-hole”
mining.
• Carried out by individuals
and highly unorganized.
• From literature: Water
bodies polluted with acid
mine drainage (AMD).

29. “To identify and map the rat-hole type coal mines (Visual Interpret.)”
CARTOSAT-1 PAN and RESOURCESAT-1 LISS-4 merged FCC depicting rat-hole
type coal mines and other landscape features.

30. “To determine the presence & hydro-chemical
characteristics of AMD”
Sampling locations
Monsoon
14 – water samples; 4 additional – pH, EC, T; 8 – stream sediments
Non-monsoon
30 – water samples; 12 additional – pH, EC, T; 22 – stream sediments

31. Mines as source of AMD?
X-axis stream provenance
S = Sedimentary rock
M = Metamorphic rock
S+M = Mixed sedimentary
and metamorphic

32. Geospatial analysis of fluoride incidence in ground water
(Example: part of Raigarh Dist., Chhattisgarh)
N
Konpara W E
#% %
Kathrapalli Salehapara
%
%
# Raikera
#%
S
Nundaraha
%
# #
#
Auraimura kerakhol
%
%
#
Charbhanta
# % #
Banai Chirmura Bajarmura
# % % %
Gharghoda Dholnara
% Bhalumuda# #% ##
##%
Karuwahi
%
Kolam #
Jhankhadarha Barkaspalli #%# # % Rodopalli
## #
#
# % % Muragaon
Bhendra Jhariapalli Patrapalli# Chitwahi % #% # Saraitola
#
#%
Baihamura ## %
#
#
% #% ## #
#
% # #Dolesara
# %#
# # # % Pata
#
Mahuapalli # # #%
Gare
% #
# %
#
Ukrapalli ##
Devgarh Pata Bandhap# # LEGEND
# % % #
# % Kunjhemura
Regaon #
Jerekela %
# % Village location
Bhalumara #% %
# Murhinar % Manjhapara #
#
% # Pre-monsoon sampling wells
Amlidih Chhaiadoria Kachkoba
%
% # % Paved road
# #
#
Basanpalli
#% Unpaved road
##
Tamnar
%
Parkipahri
# Jhindolpara Amaghat
%
#% Gorhi
# ##
% # %
(Source: Beg, 2009)
iirs/nrsc/nrsc/isro

33. Health Risk and Population at Risk
Pre-monsoon
Post-monsoon
Pre- and post-monsoon combined
(Source: Beg, 2009)
iirs/nrsc/nrsc/isro

34. Ground water quality zonation using GIS
(Example: part of Nalgonda Dist., A.P.)
(Source: Kumar and Anjaneyulu, 2003) iirs/nrsc/nrsc/isro

35. (Source: Kumar and Anjaneyulu, 2003) iirs/nrsc/nrsc/isro

36. Ground water pollution potential zoning
(Example: Solani watershed, Uttarakhand & U.P.)
Method: DRASTIC Model (Aller et al., 1987)
DI = DwDr + RwRr + AwAr + SwSr + TwTr + IwIr + CwCr (1)
where DI is the Drastic Index, and w and r represent
weights and ratings, respectively.
D - Depth to ground water
R - Recharge rate
A - Aquifer media
S - Soil Media
T - Topography
I - Impact of Vadose Zone
C - Hydraulic conductivity of aquifer
Higher the DRASTIC index, greater the relative pollution potential.
iirs/nrsc/nrsc/isro

37. 77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E 77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E
DEPTH TO WATER TABLE MAP Rainfall Recharge Map
± ±
30°15'0"N
30°15'0"N
30°15'0"N
30°15'0"N
30°10'0"N
30°10'0"N
30°10'0"N
30°10'0"N
(
! (
!
30°5'0"N
30°5'0"N
((
!! ((
!!
30°5'0"N
30°5'0"N
((
!!!
(
((
!!
(
! (
!
(
! (
! !!
((
(
!
(
! (
!
30°0'0"N
(
!
30°0'0"N
30°0'0"N
30°0'0"N
(
!
(
!
(
!
!
(
LEGEND (
! (
!
(
!
29°55'0"N
(
! (
!
29°55'0"N
(
! Dug well
29°55'0"N
(
!
29°55'0"N
(
!
(
! (
!
(
! Tube Well (
! !
(
LEGEND
(
!
Depth to water table (
! <107 mm/yr
<5 m (
! 107 - 161mm/yr
((
!!
(
!
5-10 m 161 - 202 mm/yr
29°50'0"N
29°50'0"N
(
!
29°50'0"N
10-15 m !
( 202 - 239 mm/yr
29°50'0"N
(
!
15-20 m 239 - 361 mm/yr
Hilly Area Kilometers
>20 m Kilometers 0 2 4 8 12 16
Hilly Area 0 2 4 8 12 16
77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E
77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E
(Source: Than Zaw, 2008) iirs/nrsc/nrsc/isro

38. 77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E
77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E 77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E
Aquifer Media Map Soil Media Map Slope Map
± ±
30°15'0"N
±
30°15'0"N
30°15'0"N
30°15'0"N
30°15'0"N
30°15'0"N
30°10'0"N
30°10'0"N
30°10'0"N
30°10'0"N
30°10'0"N
30°10'0"N
30°5'0"N
30°5'0"N
30°5'0"N
30°5'0"N
30°5'0"N
30°5'0"N
30°0'0"N
30°0'0"N
30°0'0"N
30°0'0"N
30°0'0"N
30°0'0"N
29°55'0"N
29°55'0"N
29°55'0"N
29°55'0"N
29°55'0"N
29°55'0"N
percent slope
0-2
2-6
Legend (rating value)
6-12
29°50'0"N
29°50'0"N
29°50'0"N
4
Legend
29°50'0"N
29°50'0"N
29°50'0"N
12-18
6
sand and gravel >18
9
Hilly Area Kilometers Kilometers
Kilometers Hilly area
0 2 4 8 12 16 Hilly Area 0 2 4 8 12 16 0 2 4 8 12 16
77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E 77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E 77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E
(Source: Than Zaw, 2008) iirs/nrsc/nrsc/isro

39. 77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E 77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E
Vadose Zone Media Map Hydraulic Conductivity Map
± ±
30°15'0"N
30°15'0"N
30°15'0"N
30°15'0"N
30°10'0"N
30°10'0"N
30°10'0"N
30°10'0"N
30°5'0"N
30°5'0"N
30°5'0"N
30°5'0"N
30°0'0"N
30°0'0"N
30°0'0"N
30°0'0"N
29°55'0"N
29°55'0"N
29°55'0"N
29°55'0"N
Legend
Legend in rating value
29°50'0"N
29°50'0"N
sand and gravel with 2
29°50'0"N
29°50'0"N
significant amount of silts and clay
4
sand and gravel 6
Kilometers Kilometers
Hilly Area 0 2 4 8 12 16 Hilly Area
0 2 4 8 12 16
77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E 77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E
(Source: Than Zaw, 2008) iirs/nrsc/nrsc/isro

40. 77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E
DRASTIC INDEX MAP
±
30°15'0"N
30°15'0"N
30°10'0"N
30°10'0"N
30°5'0"N
30°5'0"N
30°0'0"N
30°0'0"N
29°55'0"N
29°55'0"N
DRASTIC INDEX
115 - 132
132 - 142
142. - 152
29°50'0"N
29°50'0"N
152 - 163
163 - 181
Kilometers
Hilly Area 0 2 4 8 12 16
77°45'0"E 77°50'0"E 77°55'0"E 78°0'0"E 78°5'0"E
(Source: Than Zaw, 2008) iirs/nrsc/nrsc/isro