Ideal methodology for the investigation of groundwater quality and its estimation using GIS software

3. Land
29 %
Water
71 %
Saline
(Ocean)
97 %
Fresh
3 %
Ground
30.1 %
Glaciers
68. 7%
Other
0.9 %
Surface
0.3 %
Rivers
2 %
Swamps
11 %
Lakes
87 %
Distribution of Water on Earth
 Climatic variability
 Uneven distribution of rainfall
 Uneven distribution of water
 Uneven distribution of Groundwater

4. Water Surplus or Water Deficit is not main issue
Issue is that, what is current situation of water ?
 Each year thousand of policy, plan, rules regulations with crore of rupees provisions
 But, outcomes even are not satisfactory….

5. 16 May 2006 1 May 2018
Bhima Riverwater hyacinth indicator of industrial pollution
© Sainath Aher, May 2018

6. 1. China
2. United States
3. India
4. Japan
5. Germany
6. Indonesia
7. Brazil
Biggest Water-Polluting Countries

7. Water Contamination
Process
Important water contaminants
Microbial pathogens, nutrients, oxygen-consuming materials, heavy metals and persistent
organic matter, suspended sediments, nutrients, pesticides and oxygen-consuming substances
Land-use changes
Rainfall
Surface Water
Aquifers Recharge
Groundwater (high contamination)
Industry
Urbanization
Agriculture

8. WHO reported
Due to water contamination …
3 Million People Die Every Year,
mostly under the age of 5 in the world

9. Thus, the investigation of water
contamination is required

10. Scientific ground inventory: Groundwater sampling
1. APHA (2012) suggested the standard
procedure for collecting the samples
(collect in a pre-cleaned polythene bottles)
2. Groundwater sample collection from
borewell/ hand pumps/well
3. Labeling to sample Well
Well

11. Sampling scheme

12. Physico-chemical parameters such as pH,
EC, and TDS can be measured immediately
in the field after collection of samples by
using portable digital pH/EC/TDS meter
Ground inventory: Groundwater sampling, field measurement

13. pH
Electrical Conductivity (EC)
Total dissolved solids (TDS)
Fluoride (F-)
Chloride (Cl-)
Nitrate (NO3
-)
Sulphate (SO4
2-)
Bicarbonate (HCO3
-)
Calcium (Ca2+)
Magnesium (Mg2+)
Sodium (Na+)
Potassium (K+)
Chemistry Laboratory, Sangamner College
physico-chemical parameters and methods for physico-chemical analysis
In chemical laboratory
collected sample should need
stored at a < 4 degree C temp
prior to physico-chemical
analysis
Parameters Unit Analytical Method Reagents
pH / pH digital meter pH 4, 7 and 9.2
EC μS/cm EC digital meter Potassium chloride
TDS mg/L TDS digital meter Potassium chloride
TH mg/L Titrimetric
EDTA, ammonia buffer and Eriochrome Black-T (EBT)
indicator
Ca2+ mg/L Titrimetric EDTA, sodium hydroxide and murexide
Mg2+ mg/L Calculation
MgH = TH - CaH Mg2+ = MgH X Eq. Wt of Mg2+ X Normality
of EDTA
Na+ mg/L Flame photometric Sodium chloride (NaCl) and KCl
K+ mg/L Flame photometric NaCl and KCl
SO4
2− mg/L UV visible spectrophotometer HCl, ethyl alcohol, NaCl, barium chloride, sodium sulfate
NO3
−
mg/L UV visible spectrophotometer HCl, ethyl alcohol, NaCl, barium chloride, sodium sulfate
Cl
−
mg/L Titrimetric Silver nitrate (AgNO3), and potassium chromate (K2CrO4)
HCO3
−
mg/L Titrimetric Hydro sulfuric acid (H2SO4) and methyl orange indicator
F
−
mg/L ISE (Ion selective electrode) TISAB III and NaF

14. Parameters
WHO (1997) BIS (2003) (IS 10500)
Maximum
desirable
Highest
permissible
Maximum
desirable
Highest
permissible
General
Parameters
pH 7.0-8.5 6.5-9.2 6.5-8.5 8.5-9.2
EC 500 -
TDS 500 1500 500 2000
Major
Cations
Ca2+ 75 200 75 200
Mg2+ 30 150 30 100
Na+ 50 200 - -
K+ 100 200 - -
Major
Anions
HCO3
- 200 600 200 600
Cl- 250 600 250 1000
NO3
- - 50 45 100
SO4
2- 200 600 200 400
F- 0.6-1.5 1.5 1.0 1.5
Comparison of physico-chemical analysis with standards
WQI Groundwater Quality
>300 Unsuitable (Unfit)
200-300 Very Poor (VPW)
100-200 Poor (PW)
50-100 Good (GW)
<50 Excellent (E)
Water Quality Index
(Tiwari et al. 2017)
Water quality of sample

15. Sample based physico-chemical analysis (results)
6.7
7.1
8.0
7.2
8.2
6.76.7
6.7
6.7
9.7
9.1
8.7
6.7
7.9
Parameters
WHO (1997)
Maximum
desirable
Highest
permissible
General
Parameters
pH 7.0-8.5 6.5-9.2
EC
TDS 500 1500
Major
Cations
Ca2+ 75 200
Mg2+ 30 150
Na+ 50 200
K+ 100 200
Major
Anions
HCO3
- 200 600
Cl- 250 600
NO3
- - 50
SO4
2- 200 600
F- 0.6-1.5 1.5
Regional water quality ?

16. Spatial Estimation of results
Spatial estimation / interpolation is the process of using a
set of point data to create surface data
Interpolation predicts values for cells in a raster from a limited number of sample points. It can be
used to predict unknown values for any geographic point data
point data surface data
Source: http://resources.esri.com/help/9.3/ArcGISDesktop

17. Source: http://resources.esri.com/help/9.3/ArcGISDesktop
Interpolation predicts values for cells in a raster from a limited number of sample points. It can be
used to predict unknown values for any geographic point data
What kind of
data required
for estimation ?

18. Geographical coordinate of sample location is required
Well
Longitude
Handheld GPS
Latitude

19. Results Incorporation in GIS softwareSample Latitude Longitude TDS (2010)
W1 19.54 74.10 650
W2 19.54 74.13 3386
W3 19.55 74.16 4875
W4 19.59 74.16 4688
W5 19.61 74.18 572
NW6 19.63 74.21 904
W7 19.59 74.22 1496
W8 19.56 74.19 520
W9 19.52 74.18 2798
W10 19.49 74.19 3776
NW11 19.45 74.18 702
W12 19.53 74.23 1894
W13 19.51 74.26 1425
W14 19.56 74.25 3515
NW15 19.64 74.25 787
NW16 19.65 74.33 611
NW17 19.62 74.29 533
W18 19.58 74.27 1365
W19 19.55 74.28 5138
W20 19.55 74.29 3315
W21 19.53 74.31 2707
W22 19.57 74.31 5980
W23 19.58 74.34 1568
W24 19.56 74.33 3054
W25 19.56 74.36 2009
x y z
Latitude Longitude TDS
Need -

20. 15050
15050
15050
y
x
y
x100
60 70 80 90 100 110 120 130 140
xyz data need x is latitude, y is longitude, and z is selected parameters
Interpolate/estimate the value for unknown area using known values
TDS known
value
TDS known
value TDS Unknown values
Spatial estimation : mathematical logic

21. • A point data set has data values only for certain locations
• Surface data divides the study area into cells, with a data value for each cell.
• With the same algorithm and same input data points, these different
parameters can create different surfaces.
Spatial estimation : mathematical logic
https://mgimond.github.io/Spatial/spatial-interpolation.html

22. Sample Latitude Longitude TDS (2010) TDS (2015)
W1 19.54 74.10 650 717
W2 19.54 74.13 3386 3661
W3 19.55 74.16 4875 4896
W4 19.59 74.16 4688 4424
W5 19.61 74.18 572 582
NW6 19.63 74.21 904 897
W7 19.59 74.22 1496 1612
W8 19.56 74.19 520 646
W9 19.52 74.18 2798 2953
W10 19.49 74.19 3776 3784
NW11 19.45 74.18 702 621
W12 19.53 74.23 1894 1926
W13 19.51 74.26 1425 1472
W14 19.56 74.25 3515 4133
NW15 19.64 74.25 787 847
NW16 19.65 74.33 611 646
NW17 19.62 74.29 533 591
W18 19.58 74.27 1365 1562
W19 19.55 74.28 5138 5376
W20 19.55 74.29 3315 4096
W21 19.53 74.31 2707 3450
W22 19.57 74.31 5980 6214
W23 19.58 74.34 1568 1670
W24 19.56 74.33 3054 3661
W25 19.56 74.36 2009 1990

23. https://www.researchgate.net/publication/333204052_Identifying_the_impact_of_intensive_agriculture_practices_on_groundwater_quality_using_GIS_and_multi-tracer_techniques_around_Sangamner_City_Maharashtra_India

24. LULC and Groundwater Quality
Case study of Chandanapuri valley

26. Link: https://link.springer.com/chapter/10.1007/978-3-319-31759-5_14
Link: https://link.springer.com/article/10.1007/s11269-016-1299-5

27. We can perform the spatial interpolation using
Inverse Distance Weighted (IDW)
Kriging
Spline
Which is most reliable and accurate ?

28. In quantitative assessment, it was observed
that IDW and kriging performed similarly,
and both are better than spline.

29. We can get the idea of overall areas groundwater
quality instead of points based results for further
groundwater resource management
Conclusion

30. Thank You
Contact:
Dr. Sainath Parasram Aher
Department of Geography, Sangamner College, Sangamner 422605, India
Email: aher@sangamnercollege.edu.in
Mob: + 91- 99 21 22 38 84
https://www.researchgate.net/profile/Sainath_Aher