The Presentation gives the overview of the process necessary for accomplishing the task for the preparation of Ground water movements and identification carried out by Rajiv gandhi national drinking water mission project.
identification of ground water potential zones using gis and remote sensingtp jayamohan
the identification of ground water potential zones using gis and remote sensing.The study is conducted in the Muvattupuzha block.The various parameters used are geology,geomorphology,rainfall,soil type,etc.
Iirs overview -Remote sensing and GIS application in Water Resources ManagementTushar Dholakia
Remote sensing and GIS application in Water Resources Management- By S.P. Aggarval spa@iirs.gov.in Indian Institute of Remote sensing ISRO, Department of space, Dehradun
The Presentation gives the overview of the process necessary for accomplishing the task for the preparation of Ground water movements and identification carried out by Rajiv gandhi national drinking water mission project.
identification of ground water potential zones using gis and remote sensingtp jayamohan
the identification of ground water potential zones using gis and remote sensing.The study is conducted in the Muvattupuzha block.The various parameters used are geology,geomorphology,rainfall,soil type,etc.
Iirs overview -Remote sensing and GIS application in Water Resources ManagementTushar Dholakia
Remote sensing and GIS application in Water Resources Management- By S.P. Aggarval spa@iirs.gov.in Indian Institute of Remote sensing ISRO, Department of space, Dehradun
Introduction
Water resources of India at a glance
Hydrogeological cycle
Exploration of groundwater
Groundwater potential zone
Indicators
Sensors
Rules for selection of imagery
Conclusion
Reference
The subsurface occurrence of groundwater may be divided into zones of aeration and saturation. The vertical distribution of groundwater is explained in this module.
drought monitoring and management using remote sensingveerendra manduri
Monitoring drought and its management became easier with the help of remote sensing..several drought monitoring indices can be used to monitor drought condition. this ppt consists of information regarding droughts in relation to agriculture and their monitoring with the help of remotely sense based indices.
Workshop on Operationalizing the Regional Collaborative Platform to Address ‘Water Consumption, Water Productivity and Drought Management’ in Agriculture, 27 - 29 October 2015, Cairo, Egypt
Remote Sensing & GIS based drainage morphometryAkshay Wakode
Remote sensing and Geographical Information Systems (GIS) techniques are increasingly being used for morphometric analysis of drainage basins throughout the world. GIS facilitates the manipulation and analysis of spatial information obtained using remote sensing. Integrating GIS and RS provides an efficient mechanism not only to upgrade and monitor morphometric parameters but also to permit spatial analysis of other associated thematic database. As compared to the conventional morphometric studies, remote sensing provides extant ground reality inputs for assessing changes in drainage patterns, density soil characteristics and land-use/land form changes in real life. Morphometry by and large, affects the hydrological processes rather indirectly through their dependency on several other factors such as soil, geology, vegetation cover and climate (Schmidt et al. 2000). The interrelationship between morphometric parameters varies from basin to basin under diverse topography and climatic condition. Understanding these relationship would enable the identification of the dominant parameters acting on a particular basin. An extensive and detailed analysis accounting for the various morphometric parameters under linear, areal and relief aspects of measurements was performed. The test site is located along the foothills of the Western Ghats, near the city of Pune and comprises of three large scale basins. The three rivers viz. Ghod, Bhima and Mula-Mutha, which are amongst the largest in the state, broadly consist of 23 sub-basins of Ghod, 22 of Bhima and 11 of Mula-Mutha.
DEFINITION :
GIS is a powerful set of tools for collecting, storing , retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes
APPLICATION AREAS OF GIS
Agriculture
Business
Electric/Gas utilities
Environment
Forestry
Geology
Hydrology
Land-use planning
Local government
Mapping
11. Military
12. Risk management
13. Site planning
14. Transportation
15. Water / Waste water industry
COMPONENTS OF GIS
DATA INPUT
SPATIAL DATA MODEL
Data Model:
It describes in an abstract way how the data is represented in an information system or in DBMS
Spatial Data Model :
The models or abstractions of reality that are intended to have some similarity with selected aspects of the real world
Creation of analogue and digital spatial data sets involves seven levels of model development and abstraction
SPATIAL DATA MODEL
Conceptual model : A view of reality
Analog model : Human conceptualization leads to analogue abstraction
Spatial data models : Formalization of analogue abstractions without any conventions
Database model : How the data are recorded in the computer
Physical computational model : Particular representation of the data structures in computer memory
Data manipulation model : Accepted axioms and rules for handling the data
SPATIAL DATA MODEL
SPATIAL DATA MODEL
Objects on the earth surface are shown as continuous and discrete objects in spatial data models
Types of data models
Raster data model
vector data models
RASTER DATA MODEL
Basic Elements :
Extent
Rows
Columns
Origin
Orientation
Resolution: pixel = grain = grid cell
Ex: Bit Map Image (BMP),Joint Photographic Expert Group (JPEG), Portable Network Graphics(PNG) etc
RASTER DATA MODEL
VECTOR DATA MODEL
Basic Elements:
Location (x,y) or (x,y,z)
Explicit, i.e. pegged to a coordinate system
Different coordinate system (and precision) require different values
o e.g. UTM as integer (but large)
o Lat, long as two floating point numbers +/-
Points are used to build more complex features
Ex: Auto CAD Drawing File(DWG), Data Interchange(exchange) File(DXF), Vector Product Format (VPF) etc
VECTOR DATA MODEL
RASTER vs VECTORRaster is faster but Vector is corrector
TESSELLATIONS OF CONTINUOUS FIELDS
Triangular Irregular Network: (TIN)
TIN is a vector data structure for representing geographical information that is continuous
Digital elevation model
TIN is generally used to create Digital Elevation Model (DEM)
DIGITAL ELEVATION MODEL
DATA STRUCTURES
Data structure tells about how the data is stored
Data organization in raster data structures
Each cell is referenced directly
Each overlay Is referenced directly
Each mapping unit is referenced directly
Each overlay is separate file with general header
This document help you to prepare Triangulation Network (TIN), Hillshade Map, Slope map, interpolation and Digital Elevation Model (DEM) in a area and how to interpret them.
Introduction
Water resources of India at a glance
Hydrogeological cycle
Exploration of groundwater
Groundwater potential zone
Indicators
Sensors
Rules for selection of imagery
Conclusion
Reference
The subsurface occurrence of groundwater may be divided into zones of aeration and saturation. The vertical distribution of groundwater is explained in this module.
drought monitoring and management using remote sensingveerendra manduri
Monitoring drought and its management became easier with the help of remote sensing..several drought monitoring indices can be used to monitor drought condition. this ppt consists of information regarding droughts in relation to agriculture and their monitoring with the help of remotely sense based indices.
Workshop on Operationalizing the Regional Collaborative Platform to Address ‘Water Consumption, Water Productivity and Drought Management’ in Agriculture, 27 - 29 October 2015, Cairo, Egypt
Remote Sensing & GIS based drainage morphometryAkshay Wakode
Remote sensing and Geographical Information Systems (GIS) techniques are increasingly being used for morphometric analysis of drainage basins throughout the world. GIS facilitates the manipulation and analysis of spatial information obtained using remote sensing. Integrating GIS and RS provides an efficient mechanism not only to upgrade and monitor morphometric parameters but also to permit spatial analysis of other associated thematic database. As compared to the conventional morphometric studies, remote sensing provides extant ground reality inputs for assessing changes in drainage patterns, density soil characteristics and land-use/land form changes in real life. Morphometry by and large, affects the hydrological processes rather indirectly through their dependency on several other factors such as soil, geology, vegetation cover and climate (Schmidt et al. 2000). The interrelationship between morphometric parameters varies from basin to basin under diverse topography and climatic condition. Understanding these relationship would enable the identification of the dominant parameters acting on a particular basin. An extensive and detailed analysis accounting for the various morphometric parameters under linear, areal and relief aspects of measurements was performed. The test site is located along the foothills of the Western Ghats, near the city of Pune and comprises of three large scale basins. The three rivers viz. Ghod, Bhima and Mula-Mutha, which are amongst the largest in the state, broadly consist of 23 sub-basins of Ghod, 22 of Bhima and 11 of Mula-Mutha.
DEFINITION :
GIS is a powerful set of tools for collecting, storing , retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes
APPLICATION AREAS OF GIS
Agriculture
Business
Electric/Gas utilities
Environment
Forestry
Geology
Hydrology
Land-use planning
Local government
Mapping
11. Military
12. Risk management
13. Site planning
14. Transportation
15. Water / Waste water industry
COMPONENTS OF GIS
DATA INPUT
SPATIAL DATA MODEL
Data Model:
It describes in an abstract way how the data is represented in an information system or in DBMS
Spatial Data Model :
The models or abstractions of reality that are intended to have some similarity with selected aspects of the real world
Creation of analogue and digital spatial data sets involves seven levels of model development and abstraction
SPATIAL DATA MODEL
Conceptual model : A view of reality
Analog model : Human conceptualization leads to analogue abstraction
Spatial data models : Formalization of analogue abstractions without any conventions
Database model : How the data are recorded in the computer
Physical computational model : Particular representation of the data structures in computer memory
Data manipulation model : Accepted axioms and rules for handling the data
SPATIAL DATA MODEL
SPATIAL DATA MODEL
Objects on the earth surface are shown as continuous and discrete objects in spatial data models
Types of data models
Raster data model
vector data models
RASTER DATA MODEL
Basic Elements :
Extent
Rows
Columns
Origin
Orientation
Resolution: pixel = grain = grid cell
Ex: Bit Map Image (BMP),Joint Photographic Expert Group (JPEG), Portable Network Graphics(PNG) etc
RASTER DATA MODEL
VECTOR DATA MODEL
Basic Elements:
Location (x,y) or (x,y,z)
Explicit, i.e. pegged to a coordinate system
Different coordinate system (and precision) require different values
o e.g. UTM as integer (but large)
o Lat, long as two floating point numbers +/-
Points are used to build more complex features
Ex: Auto CAD Drawing File(DWG), Data Interchange(exchange) File(DXF), Vector Product Format (VPF) etc
VECTOR DATA MODEL
RASTER vs VECTORRaster is faster but Vector is corrector
TESSELLATIONS OF CONTINUOUS FIELDS
Triangular Irregular Network: (TIN)
TIN is a vector data structure for representing geographical information that is continuous
Digital elevation model
TIN is generally used to create Digital Elevation Model (DEM)
DIGITAL ELEVATION MODEL
DATA STRUCTURES
Data structure tells about how the data is stored
Data organization in raster data structures
Each cell is referenced directly
Each overlay Is referenced directly
Each mapping unit is referenced directly
Each overlay is separate file with general header
This document help you to prepare Triangulation Network (TIN), Hillshade Map, Slope map, interpolation and Digital Elevation Model (DEM) in a area and how to interpret them.
Ground Penetrating Radar And 2-D Geoelectricity Application For Detecting Lan...IJERA Editor
The potential of landslide in some area in Abang district, Karangasem Regency, Bali, has been identified by
using ground penetrating radar and geoelectricity with dipole – dipole configuration. The Research has been
conducted in 6 sites. The interpretations of GPR and Geoelectricity revealed the presence of clay (8.52 cm/ns
and 11.8 – 18.6
m), saturated sand (12.11 cm/ns and 216
m) and water penetration (3.23 – 4.27 cm/ns
and 7.5 – 60
m) at 2 – 5 meter below the subsurface. The slip surface is detected at 5 – 8 m depth. The result
of sample laboratory test show high plasticity limit (27.13 – 24.51) and liquid limit (34.50 - 30.00) which leads
to landslide phenomenon.
Assesment of groundwater_potential_zones_for_bruhat_bangalore_mahanagara_pali...Mohammed Badiuddin Parvez
Groundwater is an important natural resource in present day, but of limited use due to frequent failures in monsoon, undependable surface water, and rapid urbanization and industrialization have created a major threat to this valuable resource. The present work is an attempt to integrate RS and GIS based analysis and methodology in groundwater potential zone identification in the BBMP study area with an aerial extent of 715.95 km2. By Mohammed Badiuddin Parvez
well logging project report_ongc project studentknigh7
It briefs well logging basics for students of geophysics on well logging or partly on reservoir characterization. It can be good note book for summer ,winter training in well logging data analysis and open hole log interpretation
Effects of shale volume distribution on the elastic properties of reserviors ...DR. RICHMOND IDEOZU
Shale volume (Vsh) estimation has been carried out on three selected reservoirs (Nan.1, Nan.2, and Nan.4) distributed across four wells (01, 03, 06, and 12) in Nantin Field, using petrophysical analysis and reservoir modeling techniques with a view to understanding the reservoir elastic properties. Materials utilized for this research work include: Well Log data (Gamma Ray Log, Resistivity Log, Sonic Log, Density Log, Neutron porosity log), and a 3-D Seismic volume were used for the study. Sand and shale were the prevalent lithologies in Nantin Field. Nan. 1 reservoir was thickest in Nantin well 12 (29.7ft), Nantin 2 reservoir was thickest in Nantin Well 12 (30.9ft) while Nantin 4 reservoir was thickest in Well 3 (72ft). Correlation well panel across the Field showed that Nantin 4 reservoir, was thicker than Nan 1 and Nan 2 Reservoir respectively. Normal and synthetic Faults were also mapped, the trapping system in the field includes anticlines in association with fault closures. The thicknesses and lateral extents of these reservoirs were delineated into three zones (1, 2, and 3) which were modeled appropriately. Petrophysical and some elasticity parameters such as Poisson ratio (PR), Acoustic Impedance (AI), and Reflectivity Coefficient (RC) were evaluated for the wells. The results from elasticity evaluation showed a high Poisson Ratio of 0.40 in Nantin 2 reservoir of Well 12 based on high shale volume distribution of 0.70 indicating high stress level and possible boundary to hydraulic fracture. The lowest Poisson Ratio was evaluated in Nantin reservoir of Well 1 with lowest shale volume of 0.18 which indicates weak zones and may not constrain a fracturing job. Results from Acoustic impedance showed a high AI value of 7994.3 in Nan 2 Reservoir compared to Nan.1 which has the least AI value of 7447.3 because of low shale volume. A higher Reflectivity Coefficient of 0.01 was recorded in Nan.2 reservoir indicating bright spot while a lower RC of -0.00023 was recorded in Nan.4 Reservoir indicating dim spot. Hydrocarbon volume estimate of the three reservoirs showed 163mmstb in Nan.1 reservoir, 169mmstb, in Nantin 2 reservoir and 115mmstb in Nan. 4 Reservoir. The reservoirs encountered were faulted and laterally extensive. Nantin 2 reservoir was more prolific with a STOIIP of 169 mmstb compared to Nan. 1 with a STOIP of 163 mmstb and Nantin.4 with a STOIP of 115 mmstb, because of its good petrophysical values, facies quality and low shale volume distributions.
Reservoir characterization technique based on geostatistical inversion methodiosrjce
IOSR Journal of Applied Geology and Geophysics (IOSR-JAGG) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of Applied Geology and Geophysics. The journal welcomes publications of high quality papers on theoretical developments and practical applications in Applied Geology and Geophysics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
SEMINAR on
"Capacity Building for effective use
of Consultants" CONSULTANCY DEVELOPMENT CENTRE
An Autonomous Institution of DSIR, Ministry of Science &
Technology, Govt. of India
LARGE SCALE INSTALLATION OF SUBSURFACE DRAINAGE SYSTEM Tushar Dholakia
LARGE SCALE INSTALLATION OF SUBSURFACE DRAINAGE SYSTEM in Chambal Command, Rajasthan - Er. C.M. Tejawat, F.I.E., P. Eng., B.E. (Ag.), M.Sc. (Land Drainage Engineering) Deputy Director (Monitoring), CAD Chambal, Kota (Raj.)
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Home assignment II on Spectroscopy 2024 Answers.pdf
Iirs Role of Remote sensing and GIS in Ground water studies
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
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
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
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
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)
iirs/nrsc/nrsc/isro
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.
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