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International Journal of Civil, Structural, Environmental and Infrastructure Engineering Research and Development (IJCSEIERD) ISSN 2249-6866 Vol. 3, Issue 2, 2013, 155-164 © TJPRC Pvt. Ltd.

ESTIMATION OF AQUIFER VOLUME USING GEOPHYSICAL AND GPS STUDIES FOR A PART OF MEHADRIGEDDA RESERVOIR CATCHMENT, VISAKHAPATNAM, INDIA A 3-DIMENSIONAL MODELLING APPROACH USING GIS T. VENKATESWARA RAO1, D. RAMPRASAD NAIK2, V. VENKATESWARA RAO3 & C. JANARDHANA SWAMY4 1,2,3

Department of Geo-Engineering, A.U. College of Engineering (A), Andhra University, Visakhapatnam, Andhra Pradesh, India

4

Department of Civil Engineering, College of Engineering, Sri Venkateswara University, Tirupati, Andhra Pradesh, India

ABSTRACT The importance of aquifer mapping and computing its volume is discussed in the paper. The increasing demand on water resources has created pressure on both surface as well as groundwater reserves. As the aerial extent of the aquifer system is not known, a sub-watershed was considered for the study. Differential Global Positioning System (DGPS) survey was carried out for topographic surface modeling, which is an accurate and less time consuming process when compared to traditional methods of land survey. Electrical resistivity method, a geophysical technique, was used for subsurface mapping. ArcGIS – 3D Analyst module was used to generate 3-Dimensional models, Triangulated Irregular Network (TIN) and GRID formats, of surface and subsurface. Isopach map was prepared, which can be used for planning of rainwater conservation structures, to recharge the aquifers.

KEYWORDS: Aquifer Mapping, Isopach, Geophysical Technique, 3-Dimensional Models, TIN, DEM, DTM, DSM INTRODUCTION Aquifers are geologic formations – layers of sand, gravel and rock – where significant amounts of water can be stored, transported or supplied to well or a spring. They are irregular in shape, and can be close to the surface, or very deep. We use aquifers as a source of drinking water and to irrigate crops or to use in industry by pumping water from the aquifer using a well. As with any container of water, pumping from the aquifer empties it or at least decreases the amount of water it holds. The unregulated development of groundwater occurred particularly in the arid and semi-arid areas and emerged the problems with over-draft and associated quality (Devinder K. Chadha, 2002). Aquifers are refilled or recharged in areas where they are exposed on the surface of the earth. Water can re-enter the aquifer in these recharge areas. Groundwater flows through aquifers from areas of recharge to areas of discharge and it is not well known what the potential capacity of subsurface storage is (Albert, 2002). The need for subsurface storage is steadily growing because of increasing water demands due to growing population, catchment degradation, changes in rainfall regime as a result of climate change etc. The volume assessment becomes one of the prime factors in risk analysis applied to groundwater reservoir evaluations (Davis, 1982). Hence, the study is focused on estimating the aquifer volume using 3-Dimensional modeling and geostatistical techniques, which provide best linear unbiased estimations of unknown thicknesses (Matheron, 1971; Chayes and Suzuki, 1963; Davis, 1973).

STUDY AREA The study area lies between 170 46' 00'' N to 170 49' 00'' N latitudes and 830 11' 30'' E to 830 14' 45'' E longitudes covering an aerial extent of 17.15 km2. It is a part of Survey of India (SOI) toposheet – 65 O/1 SE of 1:25,000 scale and is


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T. Venkateswara Rao, D. Ramprasad Naik, V. Venkateswara Rao & C. Janardhana Swamy

within the administrative boundaries of Greater Visakhapatnam Municipal Corporation of Visakhapatnam, Andhra Pradesh Figure 1. The study area forms an integral part of the plains, undulating terrain and hill ranges. Geomorphologically the area consists of structural hills, denudational and residual hills as well as buried pediment zones. The area is covered with rocky soils, alluvium, red loamy and sandy clays. The area falls under semi-arid type of climate and the average annual rainfall is 1184 mm and there is high variation with minimum annual rainfall of 585 mm recorded during year 2002 to a maximum of 1680 mm recorded during the year 2006.

Figure 1: Location Map of the Study Area

METHODOLOGY The study is based on the combination of geophysical and GIS analysis using 3-Dimensional terrain modeling. 3-Dimensional modeling is the process of developing a mathematical, wireframe representation of any three-dimensional object via specialized software used in a computer simulation of physical phenomena (Jaligama et al., 2006). A digital model used to represent a topographic surface should contain adequate elevation and planimetric measurements compatible in number and distribution with the terrain being modeled, so that the elevation of any location can be interpolated accurately for any given application (Ayeni, 1982). 3-Dimensional models of surface and subsurface layers are created and processed in a GIS environment for estimating the aquifer volume, which are discussed below:

Surface Modelling The observations on 3-Dimensional (3D) view will enhance the perception and accurate identification of the objects, as compared to the interpretation of the same on a 2-Dimensional map / image. 3D models represent any object having three dimensions, using a collection of points in 3- Dimensional space, connected by various geometric entities such as triangles, lines, curved surfaces, etc. There are three data structures commonly used to store elevation surfaces; Triangulated Irregular Networks (TIN), sampling at regularly spaced grids (DEM/DTM/DSM) and lines of equal elevation (contours).


Estimation of Aquifer Volume Using Geophysical and GPS Studies for a Part of Mehadrigedda Reservoir Catchment, Visakhapatnam, India - A 3-Dimensional Modelling Approach Using GIS

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Figure 2: Triangulated Irregular Network of the Topographic Surface Showing the Elevations with Respect to Mean Sea Level Digital Elevation Model (DEM) is a generic term for digital topographic and/or bathymetric data, in all its various forms, generally refers to a representation of the Earth's surface (or subset of this), excluding features such as vegetation, buildings, bridges, etc. This bare earth DEM is generally synonymous with a Digital Terrain Model (DTM) (DEM User Manual, 2001). A Digital Surface Model (DSM) on the other hand includes buildings, vegetation, and roads, as well as natural terrain features. A Triangulated Irregular Network (TIN) is a digital terrain model that is based on an irregular array of points which form a sheet of non-overlapping contiguous triangle facets (Peuker et al., 1978). In general, TIN model is generated for 3D modeling using all measuring points (Huan, 1989). It is a vector model that supports the incorporation of point, line and area based features to capture and represent the surface morphology. An accurate, well-designed TIN maintains consistency with the degree of variation in surface heights found in the terrain. As the terrain becomes more complex the resolution of the TIN should increase accordingly. This occurs because more points are sampled and included in the TIN model in areas of high complexity (Weibel and Heller, 1991). In computations, such as spot height estimation, elevation values are interpolated for a given location based on the triangle in which it falls. Differential Global Positioning System (DGPS) survey has been carried out in the study area, used along with the contours extracted from 1:25,000 SOI toposheet, to construct TIN for the topographic surface, using ArcGIS – 3D Analyst module, which is shown in Figure 2.

Subsurface Modelling Geophysical methods are surface application methods to delineate subsurface layer boundaries and physical nature of the geological formations, using the physics of the earth. Seismic and Electrical methods are presently being used extensively for oil and groundwater prospecting respectively. In the present study Electrical Resistivity method has been utilized to delineate subsurface lithology and is described below.


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Method of Resistivity Survey In electrical resistivity survey an artificial source of current is introduced into the ground through point electrodes and the potentials is measured at other electrodes in the vicinity of the current‟s flow. It is then possible to determine an effective or apparent resistivity of the subsurface. The basic principle of this method is based on Ohm‟s law.

Figure 3: Schlumberger Electrode Configuration Linear four electrode Schlumberger configuration is adopted to carry out the Vertical Electrical Soundings (VES). The electrode configuration consists of two current electrodes (iron stakes) for sending the current into subsurface and two non-polarisable potential electrodes that consist of porous pots filled with CuSO 4 solution and copper rods placed to measure the potential difference between the equi-potential lines and are arranged linearly, as shown in Figure 3. Resistivity meter with D.C power pack of 180 volts is used for current input. In this linear array of electrodes C 1, P1, P2 and C2, the apparent resistivity can be computed using the following equation: a = π *( (L2-a2)/2a) * V /I Where a =

Apparent Resistivity in ohm-m

L = Distance between centre point and current electrode

V =

Potential difference in milli volts

a = Distance between Potential electrode

I

Current input in milli amps

O = VES location

=

Resistivity Data Interpretation The apparent resistivity (a) is calculated using the above equation and the field resistivity data, shown in Table 1 (APPENDIX 1.1), was plotted on log-log graph of 62.5 mm modulus between electrode separation (L) on X-axis and apparent resistivity (a) on Y-axis for each Vertical Electrical Sounding data. A freehand curve is drawn by joining all the points, which is the field resistivity curve, is shown in Figure 4(a). The increase or decrease of resistivity with electrode separation (depth) depends on the thickness and resistivity of the subsurface layers. Normally, the field curves are smooth and any sudden change in the resistivity at one or two reading are taken as spurious values and the curve is smoothened.


Estimation of Aquifer Volume Using Geophysical and GPS Studies for a Part of Mehadrigedda Reservoir Catchment, Visakhapatnam, India - A 3-Dimensional Modelling Approach Using GIS

Figure 4: (a) Field Resistivity Curve at VES Location No. 19 (Chintala Agraharam Village)

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(b) Subsurface Lithological Vertical Cross-Section Along Traverse A-A'

Field curves are matched with the set of theoretical curves prepared for two layer, three layer and multi layer cases prepared by Orellana and Moony (1966) and broadly 3 to 4 layers are demarcated, which are classified into top soil, weathered rock, fractured rock and hard rock. Other than the curve matching, field curves are also interpreted visually as per the hydrogeological and topographical conditions of the area. The locations of the VESs are referred with respect to (w.r.t.) Mean Sea Level (MSL), using DGPS data, and the corresponding elevations for weathered, fractured and hard rock surfaces are determined, which are shown in Table 2 (APPENDIX 1.2). In order to have an illustration of subsurface lithology, vertical cross sections are prepared by selecting the VES in a linear direction (Figure 5 (a)), choosing three traverses in west- east direction (A-A', B-B' and C-C') and three traverses in south- north direction (D-D', E-E' and F-F '). The vertical cross section along the traverse A-A' is shown in Figure 4(b). In total, 50 numbers (Figure 5 (a)) of VES data has been interpreted and the subsurface lithological information is also collected from the quarrying pits and rock outcrops exposed over the hill slopes, in and around the study area, for extrapolating the layers up to the basin boundary.

Figure 5: (a) VES Locations Map with Traverses in East-West (A,B,C) and North-South (D,E,F) Directions (b) TIN of the Weathered Rock Surface Showing the Elevations w.r.t MSL Generation of 3-Dimensional Models Resistivity of a formation is influenced by the type of formation material, degree of weathering of the rock,


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percentage of water saturation and quality of fluid filled in the pore space. 3-Dimensional models (TIN) are generated from the interpreted resistivity data, using ArcGIS – 3D Analyst module, for weathered rock (Figure 5 (b)), fractured rock (Figure 6 (a)) and hard rock (Figure 6 (b)) surfaces.

Figure 6: (a) TIN of the Fractured Rock Surface and (b) TIN of the Hard Rock Surface Showing the Elevations w.r.t MSL

VOLUME ESTIMATION OF THE AQUIFER SYSTEM The volumetric difference calculated between the topographic surface TIN and hard rock surface TIN, using TIN Difference utility in ArcGIS - 3D Analyst module, resulted 993.44 x 106 m3 of water holding / yielding zone.

Figure 7: (a) Raster GRID Map of the Topographic Surface and (b) Raster GRID Map of the hard rock surface Showing the Elevations w.r.t MSL However, being a network of triangular features with every triangle having the unique properties of slope, aspect and constantly changing elevation, as a function of the terrain characteristics that it represents over the entire feature, a TIN cannot be directly used for statistical operations such as subtractions, which are necessary when the differences between two surface features are to be extracted. To overcome this problem, the TIN is converted into a GRID format, in which each pixel represents a constant elevation. A GRID is a plain surface represented as rows and columns of raster cells. Each cell (pixel) in such matrices has a value, which is represented by a digital number. If the digital numbers are referring to the terrain elevations of an area, the GRID map therefore represents the topography of that area. The GRID maps, being matrices of numbers, facilitate


Estimation of Aquifer Volume Using Geophysical and GPS Studies for a Part of Mehadrigedda Reservoir Catchment, Visakhapatnam, India - A 3-Dimensional Modelling Approach Using GIS

161

performance of statistical functions like subtractions to extract elevation differences between two surfaces. Therefore, the TINs of the topographic surface and the hard rock surface are converted into raster format, using „TIN-to-Rasterconversionâ€&#x; function in 3-D Analyst module of ArcGIS, and the resultant GRID formats are shown in Figure 7(a) and Figure 7(b) respectively.

ISOPACH GENERATION Isopachs are the lines joining the points of equal thickness of the different units used generally to represent the subsurface layers. The thickness of the overburden at any location in the area is the difference between the topographic surface elevation and the hard rock surface elevation.

Figure 8: Isopach Map of the Aquifer Showing the Thickness of the Water Yielding Zone The elevation value that a given raster cell represents in the hard rock surface of the area, if subtracted from the value of the corresponding cell in the topographic surface, yields the thickness of the overburden at that location. Therefore, raster analysis of subtraction was performed using these two GRID formats, by subtracting the hard rock surface (Figure 7 (b)) from the topographic surface (Figure 7 (a)) of the study area and the thickness values were classified in ArcGIS, by grouping all the cells into 5 classes. The output is a GRID surface with each raster cell in it representing the thickness of the water yielding zone in the area (Figure 8).

RESULTS & CONCLUSIONS There is a large potential for subsurface storage, notably in areas with deep groundwater tables and no risks for collateral problems such as water logging. The thickness of the water bearing formations i.e., weathered and fractured rock zones has increased from the foot hill regions to the low lying areas of the study area. Over the hill slopes and hill ridges, hard rock is present immediately below the top soil. Even though there is few fractured rock zones noticed over the hill slopes, these may not contain aquifer system but may guide the rainwater to percolate from the top soils into the aquifer system down below. However, the hill slopes are useful to retain rainwater for some time and release it into the aquifer system existing down below the foot hill region. Therefore this zone is considered to be suitable for constructing harvesting


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structures, like contour trenches. Isopach map reveals that the thickness of the water yielding zone is within 20 meters range in the hilly and pediment zones whereas the maximum thickness of more than 60 meters is in the central parts of the area, which is supposed to be high groundwater potential zone.

APPENDICES APPENDIX 1.1 Table 1: Vertical Electrical Sounding data at VES Location No.19

Potential Electrode Separation (a/2 in m)

Current Electrode Separation (L in m)

0.5

1 2 3 5 7 7 10 13 16 20 20 25 30 30 35 40 40 50 60 60 70 80 80 90 100

1.0

2.0

3.0

5.0

7.0

10.0

Configuration Constant (Ď€ (L2-a2)/2a) 2.36 11.77 27.47 77.71 153 75.36 155.4 263.7 401.9 626.4 310.8 487.4 703.3 466.2 636.3 832.6 494.5 771 1122.5 796.43 1088.01 1424.43 989.1 1256 1554.3

Current (mA) 27.6 26.5 30.0 27.2 31.6 31.5 33.5 24.4 20.4 20.3 20.1 16.1 16.6 15.1 16.21 21.1 20.7 25.2 18.5 18.4 16.5 14.4 14.0 19.9 18.2

Voltage (mV) 890 142 69.0 21.0 12.3 24.1 13.1 6.0 3.3 2.3 4.4 2.4 1.8 2.4 2.2 2.1 3.3 2.9 1.5 2.4 1.7 1.5 1.9 1.9 1.4

APPENDIX 1.2 Table 2: Elevation Data of Surface and Subsurface Layers w.r.t. MSL (m) VES Location 1

Surface

Weathered Rock

Fractured Rock

22.02

19.02

12.02

Hard Rock -27.98

2

23.30

21.80

17.30

-16.70

3

42.64

41.64

22.64

2.64

4

40.00

37.00

25.00

-20.00

5

24.52

21.52

14.52

-25.48

6

31.18

28.18

1.18

-58.82

7

63.85

62.85

57.85

43.85

8

53.97

51.97

45.97

23.97

9

40.74

36.74

15.74

-39.26

Apparent Resistivity (Ohm-m) 76.10 63.07 63.18 60.00 59.55 57.66 60.77 64.84 65.01 70.97 68.04 72.66 76.26 74.10 86.36 82.87 78.83 88.73 91.01 103.88 112.10 148.38 134.24 119.92 119.56


Estimation of Aquifer Volume Using Geophysical and GPS Studies for a Part of Mehadrigedda Reservoir Catchment, Visakhapatnam, India - A 3-Dimensional Modelling Approach Using GIS

Table 2: Contd., 10

42.12

39.12

22.12

-37.88

11

45.91

44.91

35.91

-24.09

12

68.57

62.57

48.57

28.57

13

77.06

74.06

67.06

47.06

14

53.86

51.86

33.86

-16.14

15

80.00

79.00

79.00

70.00

16

44.29

40.29

24.29

-5.71

17

32.00

30.00

22.00

-18.00

18

52.92

49.92

27.92

-27.08

19

23.21

21.21

8.21

-36.79

20

23.32

22.32

17.32

3.32

21

41.76

38.76

21.76

-28.24

22

22.02

20.02

12.02

-27.98

23

31.80

28.80

21.80

-18.20

24

80.00

78.00

78.00

70.00

25

200.00

198.00

198.00

198.00

26

70.00

68.00

68.00

60.00

27

80.00

78.00

78.00

70.00

28

230.00

228.00

228.00

228.00

29

90.00

88.00

88.00

80.00

30

290.00

287.00

287.00

287.00

31

130.00

128.00

128.00

120.00

32

170.00

168.00

168.00

160.00

33

90.00

88.00

80.00

60.00

34

290.00

288.00

288.00

288.00

35

80.00

78.00

70.00

30.00

36

280.00

277.00

277.00

277.00

37

150.00

147.00

147.00

135.00

38

150.00

148.00

148.00

140.00

39

90.00

88.00

80.00

60.00

40

280.00

277.00

277.00

277.00

41

90.00

88.00

88.00

82.00

42

240.00

238.00

238.00

238.00

43

270.00

267.00

267.00

267.00

44

80.00

78.00

78.00

74.00

45

31.00

26.00

15.00

-29.00

46

20.00

15.00

0.00

-40.00

47

22.00

19.00

-3.00

-48.00

48

15.00

11.00

-5.00

-35.00

49

15.00

12.00

5.00

-15.00

50

120.00

117.00

117.00

100.00

163


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Albert Tuinhof, Theo Olsthoorn, Jan Piet Heederik and Jacobus de Vries, 2002, Management of aquifer recharge and subsurface storage - A promising option to cope with increasing storage needs, Netherlands National Committee of the International Association of Hydrogeologists, NNC-IAH Publication No.4

2.

Ayeni, O.O., 1982. “Optimum sampling for digital terrain models: A trend towards automation,” Photogrammetric Engineering and Remote Sensing, 48 (11), pp. 1687-1694.

3.

Chayes, F. and Y. Suzuki, 1963, Geological contours and trend surfaces, Journal of Petrology, V. 4, pp. 307-312.

4.

Davis, G.H. 1982, Prospect risk analysis applied to groundwater reservoir evaluation, Grounwater Vol. 20, No. 6, pp 657-662

5.

Davis, J. C. 1973, Statistics and Data Analysis in Geology, John Wiley and Sons, Inc., New York, 550 pp.

6.

DEM User Manual, Digital Elevation Model Technologies and Applications, 2001: The American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland.

7.

Devinder K. Chadha, 2002, State of art of artificial recharge applied on village level schemes in India, Netherlands National Committee of the International Association of Hydrogeologists, NNC-IAH Publication No.4

8.

Huan Y. P., 1989. Triangular irregular network generation and topographical modeling, Computer in industry, pp.203 -213.

9.

Jaligama, G., Cerucci M., Bergstrom J. and Goodrow. S., 2006. “Combining Digital Elevation Datasetsand Field Surveys for Stormwater Modeling”, Preceedings, May 8-10.

10. Matheron G. 1971, The theory of regionalized variable and its applications, Les cahiers du Centre de Morphologic Mathematique de Fountainbleau 5, Ecole Nationale Superieur de Mines de Paris, 211 pp. 11. Orellana, E. and Mooney, H.M. (1966) Master Tables and Curves for Vertical Electrical Soundings over Layered Structures: Interciencia, Madrid. 12. Peukar, T.K., R.J. Fowler J.J. Little and Mark, D.M.., 1978. “The Triangulated irregular network,” Proceedings of the Digital Terrain Models (DTM) Symposium, St. Louis, Americal Society of Photogrammetry, 516-540. 13. Wiebel, R. and M Heller., 1991. “Digital Terrain Modelling,” In Geographic Information Systems: Principles and Applications, edited by D. Maguire et al., England: Longman Scientific, Vol. 1, 269-297.


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