geospatial services

SBL GSS Division

Remote Sensing and GIS Application in Hydro geological Mapping and

Water Quality Modeling

ByVenugopalan Nair

Outline

1. Introduction2. Remote Sensing System3. Electro Magnetic Spectrum4. Digital Image Processing5. Radiometric corrections6. Geometric corrections7. Thematic mapping8. Hydro geological Mapping9. Water Quality Modeling- A Case Study

Self Introduction

Name: Venugopalan NairEducation: M.Sc. (Applied Geology), Barkatullah University, Bhopal, IndiaM.Tech (Remote Sensing), Bharathidasan University, Trichy, IndiaM.Tech (Hydrology), IIT, Roorkee, IndiaExperience: 15 Years + in GISNational Geophysical Research InstituteGB Pant Institute ofHimalayan Environment and DevelopmentDefense Terrain Research LabCentral Ground Water BoardRMSISBL

Self Introduction

• Venugopalan Nair, Senior Manager, SBL has delivered a lecture on “Remote sensing and GIS in hydrogeological mapping and water quality modeling” for a training course on sustainable development and management of ground water resources, conducted by Central Ground Water Board, Rajiv Gandhi National Ground Water Training and Research Institute, River Development and Ganga Rejuvenation, Ministry of water Resources, Government of India

• In the lecture, Mr.Nair has explained the basics of remote sensing technology to participants from agricultural, soil conservation, Cochin University of Science and Technology, and many other departments constantly works for sustainable development. The presentation explained how this useful technology and implement in agriculture, land resource utilization, water conservation and ground water quality modeling. The enthusiastic participants made many queries in their respective domain and updated themselves about this technology.

Remote Sensing System

Electro Magnetic Spectrum

Energy Interactions

Resolutions in Remote Sensing

1. Spatial Resolution

2. Spectral Resolution

3. Radiometric Resolution

4. Temporal Resolution

Resolutions in RResolutions in Remote Sensihjhjkhkngdfwefrefrte3trer3434ererwemote Sensing

Spatial Resolutions

CARTOSAT I MAGESpat ial Resolu t ion: 2 .5m

LISS IV ImageSpatial Resolution 5.8m

Land sat Image Spatial Resolution 30m

Spectral Resolution

Characteristics of commonly used bands

Radiometric Resolutions

Temporal Resolution

Sample Satellite Image

Satellite Image Procurement

1. Sun Angle

2. Nadir angle

3. STD/Ortho ready

Digital Image Processing

1. Radiometric Corrections

2. Geometric Corrections

3. Image classification

Digital Image Processing

PIXEL

Image Enhancement

GIS Services – Geo Referencing

Using Feature matching

Using DGPS points

Using reference coordinates/grid

Pan Sharpening/Resolution Merging

Mosaicking

Colour balancing

Tiling

Digital Elevation Models

Ortho rectification

Classification

1. Supervised classification

2. Unsupervised classification

3. Hybrid classification

Supervised Classification

1. Training site identification

2. Spectral signature collection

3. Statistical analysis

4. Classification Methods

5. Process running


• Advantages– Analyst has control over the selected classes

tailored to the purpose– Has specific classes of known identity– Does not have to match spectral categories on the

final map with informational categories of interest– Can detect serious errors in classification if

training areas are misclassified


• Disadvantages– Analyst imposes a classification (may not be

natural)– Training data are usually tied to informational

categories and not spectral properties• Remember diversity

– Training data selected may not be representative– Selection of training data may be time consuming

and expensive– May not be able to recognize special or unique

categories because they are not known or small

Unsupervised Classification

1. Algorithm based

2. Inbuilt methods


• Advantages– Requires no prior knowledge of the region– Human error is minimized– Unique classes are recognized as distinct units

• Disadvantages– Classes do not necessarily match informational

categories of interest– Limited control of classes and identities– Spectral properties of classes can change with time

Feature Extraction

Thematic mapping

Land Use Land Cover Mapping

Activities

Input image collection

Geo referencing

LULC schema preparation

Image classification

Topology corrections

Field verification

Post field updation

Final LULC map compilation

PICTORIAL REPRESENTATION OF GROUND WATER QUALITY DETERIORATION

STUDY AREA

LOCATION

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee

HaridwarBhagwampur

Bahaderabad

77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"NºLOCATI ON MAP

DI STRI CT HARI DWAR

0 2.5 5 7.5 101.25Km

53 K/1

53 K/2

53J/453F/16

53G/13

53 G/14

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee

HaridwarBhagwampurBahaderabad

77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"NºGEOLOGI CAL MAP

DI STRI CT HARI DWAR

0 3 6 9 121.5Km

Legend

FormationsDoon Alluvium

Siwaliks

Bhabar

Tarai

Alluvial Plains

GEOLOGY

SIWALIC FORMATIONS

INDO-GANGETIC ALLUVIUM

BHABAR

TARAI

ALLUVIAL PLAINS

STUDY AREA

HYDRO-GEOLOGY

AQUIFER PARAMETERS RANGE

THICKNESS OF SHALLOW AQUIFERS

4 TO 100M

DEPTH TO WATER LEVEL 1.5 TO 17.6 M BGL

COEFFICIENT OF PERMEABILITY 2.16 TO 28.8 M/DAY

STORATIVITY 1 X 10-4 TO 3.74 X 10-4

TRANSMISSIVITY 10 TO 2880 M2/DAY

SPECIFIC YIELD 0.13 TO 0.26

STUDY AREA

HYDRO-GEOLOGY

CROSS SECTION ALONG MANAKPUR - JWALAPUR

CROSS SECTION ALONG GANESHPUR – SHIKARPUR

STUDY AREA

IAWQ MODEL THROUGH GIS

× 5

× 4

× 3

× 2

× 1

× 5

× 3

WeightRatings

9

3

6

5

5

6

4

132

AQUIFER WATER QUALITY INDEX

THE METHOD HAS A LOW COST OF APPLICATION

APPLIED IN EXTENSIVE REGIONS

RELATIVELY FEW, EASY TO COLLECT, AND COMMON DATA IS REQUIRED

SEVERAL PARAMETERS AND THEIR INTERRELATIONSHIP DECREASE THE PROBABILITY OF

IGNORING SOME IMPORTANT PARAMETERS

RESTRICT THE EFFECT OF AN INCIDENTAL ERROR

ENHANCE THE STATISTICAL ACCURACY OF THE MODEL

OTHER SPECIALIZED METHODS WOULD REQUIRE SPECIFIC PARAMETERS.

ADVANTAGES OF AWQI METHOD

DRASTIC MODEL

DISADVANTAGES OF DRASTIC METHOD

SO MANY VARIABLES ARE FACTORED INTO THE FINAL INDEX THAT CRITICAL PARAMETERS IN

GROUND WATER CONTAMINATION MAY BE SUBDUED BY OTHER PARAMETERS THAT HAVE NO

BEARING ON GROUND WATER POLLUTION.

THE SELECTION OF THE PARAMETERS IS BASED ON QUALITATIVE JUDGMENT AND NOT

QUANTITATIVE STUDIES.

MODALITY OF GROUND WATER SAMPLE COLLECTION

PRE FIELD PREPARATIONS

PURGING OF THE WELLS

SAMPLE COLLECTION

FIELD ANALYSIS

pH

ELECTRICAL CONDUCTANCE

TEMPERATURE

STORAGE

LABORATORY ANALYSIS

GROUND WATER QUALITY

LABORATORY ANALYSIS

CONSTITUENT METHODPHYSICAL

pH POTENTIOMETRIC

ELECTRICAL CONDUCTANCE (micro mhos/cm at 250 C)

ELECTROMETRIC

TDS ELECTROMETRIC

MAJOR IONS

Ca2+ TITRIMETRIC

Mg2+ EMPERICAL CALCULATION

N+ PHOTOMETRIC (EMISSION)

K+ PHOTOMETRIC (EMISSION)

Cl- TITRIMETRIC

SO42- GRAVIMETRIC

HCO3- EMPERICAL CALCULATION

CO32- EMPERICAL CALCULATION

Contd…..


LABORATORY ANALYSIS

CONSTITUENT METHODNUTRIENTS

NO3- ION SELECTIVE ELECTRODES

PO42- SPECTRO PHOTOMETRIC

(ABSORPTION)

TOC TOC ANALYSER

HEAVY METALS

Cd VOLTAMETRIC

Cu VOLTAMETRIC

Pb VOLTAMETRIC

Zn VOLTAMETRIC


DISTRIBUTION OF pH AND TDS

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendpH Value

High : 8.8

Low : 7.1

POTENTI AL HYDROGEN I ON CONCENTRATI ON (pH) MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendTDS (mg/l)

0- 500

500 - 1,010

TOTAL DI SSOLVED SOLI DS (TDS) MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km


DISTRIBUTION OF Ca+AND Mg2+

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendCalcium Concentration (mg/l)

0 - 75

75 - 150

150 - 225

225 - 300

300 - 408

CALCI UM CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendMagnisium Concentration (mg/l)

15- 30

30 - 60

60 - 90

90 - 98

MAGNI SI UM CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km


DISTRIBUTION OF Na+ AND K+

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendSodium Concentration (mg/l)

High : 259

Low : 0

SODI UM CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendPotassium Concentration (mg/l)

High : 66

Low :0

POTASSI UM CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km


DISTRIBUTION OF Cl- AND SO42-

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendChloride Concentration (mg/l)

High : 87.0844

Low : 2.11874

CHLORI DE CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendSulphate Concentration (mg/l)

0 - 200

200 - 400

SULPHATE CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km


DISTRIBUTION OF TA AND NO3-

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendTotal Alkalinity (mg/l)

0 - 200

200 - 400

400 - 600

TOTAL ALKALI NI TY MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendNitrate Concentration (mg/l)

0- 45

45 - 90

90 - 135

135 - 180

180 - 225

225 - 230

NI TRATE CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km


DISTRIBUTION OF Cd AND Pb

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendCadmium Concentration (mg/l)

High : 0.00775389

Low : 0

CADMI UM CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendLead Concentration (mg/l)

High : 0.027918

Low : 0.00100244

LEAD CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km


DISTRIBUTION OF Cu AND Zn

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendCopper Concentration (mg/l)

High : 0.0607936

Low : 0.00101479

COPPER CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km

"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendZinc Concentration (mg/l)

High : 3.43757

Low : 0.00583

ZI NC CONCENTRATI ON MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km


PIPPER DIAGRAM


STATISTICAL SUMMARYCONSTITUENT MIN MAX MEAN SD BIS DESIRABLE

LIMITS

PHYSICAL

pH 7.1 8.8 7.7 0.35 6.5-8.5

ELECTRICAL CONDUCTANCE (micro mhos/cm at 250 C)

234 1562 673.8 282.26 -

TDS (mg/l) 154 1020 448.8 184.7 500

MAJOR IONS

Ca2+ (mg/l) 61.6 408 178.5 74.21 75

Mg2+ (mg/l) 15 99.1 43.59 17.94 -

N+(mg/l) ND 259.6 30.87 59.45 -

K+ (mg/l) ND 66.8 7.33 17.35 -

Cl- (mg/l) 1 144.9 22.69 29.88 250

SO42- (mg/l) 64 358 188.8 62.26 200

HCO3- (mg/l) 103 602 277 84.88 200

CO32- (mg/l) 0.21 10.71 1.77 1.51 -

CONTD…..


CONSTITUENT MIN MAX MEAN SD BIS DESIRABLE

LIMITSNUTRIENTS

NO3- (mg/l) 1.6 230 34.95 38.09 45

PO42- (mg/l) Trace

TOC (mg/l) Trace HEAVY METALS

Cd (mg/l) ND 0.008 0.005 0.001 0.01Cu (mg/l) ND 0.061 0.009 0.0117 0.05Pb (mg/l) 0.001 0.028 0.004 0.0056 0.05Zn (mg/l) 0.001 3.442 0.295 0.61 5

STATISTICAL SUMMARY


INDEX OF AQUIFER WATER QUALITY

DEVELOPED BY A.J.MELLOUL AND M COLLIN IN 1988.

IT WILL GIVE AN IDEA OF OVERALL GROUND WATER QUALITY STATUS .

IT IS AN EMPIRICAL INDEX SIMULTANEOUSLY USING A NUMBER OF PARAMETERS.

IT ALSO USES RATING AND WEIGHING SYSTEM.

IT CAN BE ESTIMATED IN GIS ENVIRONMENT.


• SELECTION OF PARAMETERS IAWQ

THOSE CHEMICAL PARAMETERS FOR WHICH MORE THAN 10 % OF THE SAMPLES SHOWING HIGHER CONCENTRATION THAN THE DESIRED LIMITS ARE CONSIDERED.

Parameters

% of samples exceeding BIS desirable l imits BIS desirable l imits

TDS 27 500Ca2+ 57 75TA 66 200

SO42- 32 200

NO3- 15 45

EVEN THOUGH HEAVY METAL CONCENTRATIONS ARE WITHIN DESIRED LIMITS, LEAD AND CADMIUM ARE CONSIDERED FOR INDEXING BECAUSE THESE ARE HIGHLY TOXIC TO HUMAN AND OTHER FAUNA AND FLORA


PROCEDURE FOR ESTIMATION OF IAWQ

WEIGHTING COEFFICIENTS IS CALCULATED BASED ON IMPACT OF EACH PARAMETERS ON HUMAN HEALTH AND ITS GROUND WATER POLLUTION POTENTIAL

GROUP PARAMETERS WEIGHTI Cd 5

Pb 5II NO3

- 4

III TDS 3IV Ca2+ 1

TA 1SO4

2- 1



1. STANDARDISATION OF FIELD DATA

Xij = Pij/Dij where

Xij = STANDARDISED FIELD DATA

Pij = FIELD DATA

Dij = DESIRED BIS LIMIT

• RATING OF STANDARDISED DATA

Yi HAS BEEN ASSIGNED TO EACH Xij

1. FOR GOOD WATER QUALITY Xij IS EQUAL TO 0.1 THE CORRESPONDING INDEX RATING IS 1

• FOR ACCEPTABLE WATER QUALITY Xij IS 1 THE CORRESPONDING INDEX RATING IS 5



C. FOR UNACCEPTABLE GROUND WATER QUALITY Xij EQUAL OR MORE THAN 3.5 CORRESPONDING INDEX RATING IS 10

NOW AS X1 = 0.1, Y1 = 1

X2 = 1, Y2 = 5

X3 = 3.5, Y3 = 10

Yij = f (Xij) CAN BE A PARABOLIC FUNCTION

THIS CAN BE CONVERTED TO A POLYNOMIAL

Yi = -0.712 * Xi2 + 5.228 * Xi + 0.484



3. THE FINAL IAWQ IS CALCULATED USING THE FORMULA

IAWQ = C / n ∑ =

n

iYriWri

1)]*(

C CONSTANT (10)n NO. OF PARAMETERS (7)Wri Wi / Wmax

Yri Yi / Ymax

Wi WEIGHTING COEFFICIENTWmax MAXIMUM WEIGHTING COEFFICIENT(5)Yi RATES AS CALCULATED FROM EQUATIONYmax MAXIMUM RATE (10)


FINAL IAWQ

CALCULATED IAWQ THROUGH GIS"

"

"

"

""

"

Narsan

Laksar

Khanpur

Roorkee


77°50'0"E

77°50'0"E

78°0'0"E

78°0'0"E

78°10'0"E

78°10'0"E

29°40'0"N 29°40'0"N

29°50'0"N 29°50'0"N

30°0'0"N 30°0'0"N

30°10'0"N 30°10'0"Nº

LegendIAWQ

High : 2.42364

Low : 0.739088

I NDEX OF AQUI FER WATER QUALI TY ( I AWQ) MAP DI STRI CT HARI DWAR

0 5 10 15 202.5Km


CONCLUSION

IN GENERAL, GROUND WATER QUALITY IS FIT FOR DRINKING AND AGRICULTURAL

PRACTICES.

CHEMICAL ANALYSIS RESULTS REVEALS THAT GROUND WATERS OF THE STUDY AREA IS

SLIGHTLY ALKALINE.

URBAN AREA OF THE STUDY AREA SHOWS HIGH TDS.

AMONG THE CATIONS CALCIUM AND MAGNESIUM ARE THE DOMINANT ONES, SODIUM

AND POTASSIUM ARE HAVING LOW VALUES IN MOST OF THE AREA.

SULPHATES ARE THE DOMINANT ANIONS. HIGH CHLORIDES ARE ASSOCIATED WITH

INTENSIVE CULTIVATION.

TOTAL ALKALINITY IS DOMINANT IN MAJORITY OF THE AREA.

HIGH VALUES OF NITRATES ARE DUE TO DECOMPOSITION OF URBAN WASTE.

HEAVY METALS ARE WELL WITHIN THE DESIRABLE LIMITS. HIGH VALUES ARE ASSOCIATED WITH URBAN AND INDUSTRIALIZED AREAS.

GIS IS AN APT TOOL IN ASSESSMENT OF GROUND WATER VULNERABILITY TO POLLUTION.

WATER QUALITY IS NOT REFLECTED THE WAY VULNERABILITY TO POLLUTION.

AQUIFER RESISTIVITY AND LAND USE ARE BETTER PARAMETERS TO VALIDATE THE VULNERABILITY INDICES IN SUCH CASES.

CONCLUSION

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