Journal of Information and Computational Science ISSN: 1548-7741

GEOINFORMATICS BASED IDENTIFICATION OF GROUNDWATER POTENTIAL ZONE IN , Anandakumar.I1* and Madha Suresh. V2

1 * Research Scholar, CNHDS, University of Madras, – 25 2Professor and Head, CNHDS, University of Madras, Chennai – 25 *Corresponding Author Abstract Climate change combined with oversaturation of groundwater in recent years resulting since population explosion and rapid urbanisation as lead to serious pressure on the groundwater resource. is one of the largest users of groundwater with 60 per cent for agriculture and 85 per cent for drinking, hence it is essential in trapping the rainwater to improve groundwater resources. The Present study is intended to explore the groundwater potential zone in using the geospatial combination of Geographical Information System and Remote Sensing. Eight parameters were incorporated for demarcating groundwater potential zone namely; Geology, Geomorphology, Soil, Landuse / Landcover, Slope, Drainage Density, Lineament Density and Rainfall. The techniques used for identification of the potential zones are Inverse Distance Weighted (IDW) and Weighted Overlay, 8 parameters were assigned weightage based on their physical characteristics and its influence in determining the suitable zone. The results derived from Weighted Overlay are classified into five groups based on its potentiality namely, Very High (0.12 percent), High (3.04 percent), Moderate (47.12 per cent), Low (42.08 percent) and Very Low (7.6 percent). Outcome demonstrated the usefulness of the GIS and Remote Sensing as an effective tool in identification and management of Groundwater resource, in order to tackle acute shortages during extreme conditions. Keywords Groundwater Potential Zone, Weighted Overlay, Inverse Distance Weighted (IDW), Geographical Information System, Remote Sensing.

1. Introduction

“Groundwater” is part of the water cycle which is stored beneath the ground at certain depth, due to the process of precipitation, feed by the stream, waterbodies which seeps into ground through cracks, factures, unsaturated zones, infiltrated to reach the groundwater table which acts vis-versa to supply water (International Groundwater Resource Assessment Centre).Tamil Nadu is the southernmost state in India with 6per cent in total population, 4per centin geographical space and 2.5per cent in water resource. The 80per cent of the groundwater resource is utilised, demand rate as increased sharply due to population explosion, industrialization and urbanisation which as lead to shortage of water resources (Tamil Nadu Environmental Information System).In Recent year the climatic trend as affected the water cycle, because monsoonal rainfall is essential in recharging the

Volume 9 Issue 11 - 2019 1623 www.joics.org Journal of Information and Computational Science ISSN: 1548-7741

waterbodies, groundwater which had gone to extreme conditions. It is estimated that 80per cent of the rural and 50 per cent of urban region utilizes the groundwater for domestic purpose. Geographical location coupled with dependence on groundwater and improper management had led to depletion of groundwater resource. 1.2 Study Area

Figure 1: Study Area

Ariyalur is one of the administrative district located in Tamil Nadu which covers an area of 1,949 sq.km (District Survey Report, 2017). District was formed in the year 2001, when southern part was divided to form the present Ariyalur. The Ariyalur is surrounded by following , on the North by Cuddalore, Perambalur on west and on the south by Nagaipattinam and District. Administrative setup consists of three taluks namely, Ariyalur, andSendurai and six blocks , Ariyalur, Jayankondan, , T. Palur, Thirumanur. The population of the district consists of 754894 persons of which 380191 are female and 374703 are male (District Hand Book, 2016–17). It is well-known for the mining, quarry and industrial based activity concentrated on the cement manufacturing. The minerals extracted are classified into Major and Minor; Major mineral consists of Limestone, Marl, Crude Oil, Fire clay and Minor minerals consists of Gravel, Kankar, Pebble and Black clay (District Survey Report, 2017). The district is situated in sub-tropical zone, the normal rainfall ranges from 843.5 to 1123.3 mm, with highest Jayankondan and lowest in vembavur(District Survey Report, 2017).The study area also experiences 57 per cent of the rainfall during the onset of northeast monsoon and 42 per cent in southwest monsoon (Tamil Nadu

Environmental Information System). Climate is hot and humid during summer with maximum of 40Oc

and minimum of 23Oc recorded.

Volume 9 Issue 11 - 2019 1624 www.joics.org Journal of Information and Computational Science ISSN: 1548-7741

2. Material and Methods The following datasets used to delineate the groundwater potential zone, consists of Geology, Geomorphology, Soil, Rainfall, LULC, Slope, Lineament and Drainage. The materials were collected from various government and non-government organization like Geological Survey of India (Geology, Geomorphology), National Bureau of Soil Survey (Soil), IMD (Rainfall) and USGS (DEM and Sentinel Imagery). The processed data had been projected to the local projection – Universal Transverse Mercator – 44 (UTM). Landuse / Landcover and lineament were prepared using the Sentinel Imagery with spatial resolution 10 m. SRTM DEM was used to produce Drainage and Slope maps. Rainfall data was collected based on the available station, which was interpolated using Inverse Distance Weighted (IDW) tool in ArcGIS. Eight parameters were converted into raster layers, in order to calculate weightages for generating groundwater potential zone. The raster layers were assigned weightage based on its role in finding groundwater potential zone, each layer consists of high to low value namely; 15, 10 and5. Further each raster was re-classified and provide with rank based on its influence high to low (5 to 1) within the specific thematic map. In order to locate the groundwater potential zone, the raster layers were overlaid and output derived based on the weightage.

Groundwater Potential Zone

Data Collection

Image Satellite Imagery Processing Conventional Data

Sentinel Imagery DEM Geology

Geomorphology LULC Weighted Overlay Analysis Soil Slope

Rainfall Lineament

Drainage Groundwater Potential Zone

Figure 2: Methodology flow chart for Proposed Study Table 1: Data used to delineate the Groundwater Potential zone

Volume 9 Issue 11 - 2019 1625 www.joics.org Journal of Information and Computational Science ISSN: 1548-7741

Sl. No. Input Data Source Scale / Resolution 1. LULC USGS – Sentinel-2 10 m 2. Slope USGS - SRTM 30 m 3. Lineament USGS – Landsat -8 30 m 4. Drainage USGS - SRTM 30 m 5. Geology Geological Survey of India 1:50,000 6. Geomorphology Geological Survey of India 1:50,000 7. Soil National Bureau of Soil Survey 1:50,000 8. Rainfall Indian Meteorological Department NA

3. Result and Discussion (Factors influencing Groundwater)

Figure.3 LULC Classification Map Figure 4: Slope Classification Map

3.1 Landuse/ Land Cover Landuse / Landcover map (fig.3) is prepared using the Sentinel-2 satellite derived imagery which as high spatial resolution (10 m) and accuracy. Two scenes were used to study the entire Ariyalur district (Thirumalai and Anand2017)which wasradiometrically corrected to remove the noise and haze. Mosaic tool used to merge two imageries to single scene. Landuse / landcover was generated using Supervised classification, which is basically training the computer to identify each feature. Landuse / landcover features consist of Agricultural land, fallow land, built-up, plantation, waterbodies, waste land and forest. LU/LC plays important role in groundwater recharging based on the ground cover and nature. Agriculture land covers the largest area with 1000.44 sq.km with 51.3per cent, followed by plantation which covers 360.12 sq.km (18.4per cent), fallow land with 245.67 sq.km (12.5per cent), Waterbodies with 134.65 sq.km (6.9per cent), Forest with 88.59 sq.km (4.5per cent), Built-Up with 78.16 sq.km (4per cent) and Waste land with 41.76 sq.km (2.1per cent).

Volume 9 Issue 11 - 2019 1626 www.joics.org Journal of Information and Computational Science ISSN: 1548-7741

3.2 Slope Slope is one of important aspect in mapping of groundwater potential zone, because it provides the valuable information of water accumulation zone based on the gradients. The Slope map (fig.4) was generated using the SRTM DEM data and ArcGIS which calculates the slope degree with respect to the elevation. The slope map had been prepared using the following class interval namely; 0 – 2o, 2 – 5o and 5-7obased on the physiography of the terrain. The study area comprises of very gentle slope with 0 to 2ocovers 903.5 sq.km (46.3per cent), followed by 2 to 5owith 820.4 sq.km (42.1per cent) and 5 to 7owith 224.9 sq.km (11.5per cent).

Figure 5: Lineament Classification Map Figure 6: Drainage Density Classification Map

3.3 Lineament Density Lineament (fig.5) is good source of trapping and storing of water resources and provides recharge toward the increase in groundwater table. The lineament map was produced using the Landsat – 8 imagery and Elevation data and processed using Remote Sensing and GIS software. The lineament was used to create the lineament density which grouped into 5 class namely, 0 - 0.339 km/km2covering 1523.8 sq.km (78.1per cent), 0.339 – 0.679 km/km2 with 278.65 sq.km (14.2per cent), 0.679 - 1.019 km/km2 with 19.23 sq.km (0.9per cent), 1.019 – 1.359 km/km2 with 123.8 sq.km (6.3per cent) and 1.359 – 1.699 km/km2 with 3.79 sq.km (0.19per cent).

3.4 Drainage Density Drainage Density map (fig.6) produced using the Elevation Data (SRTM), the data is void filled to rectify the errors recorded during the mission. The drainage map was obtained from calculating flow direction, flow accumulation and stream generation. Stream Order is important product, Ariyalur district have 4 order stream (strahler method). The weightage given based on the stream order, stream order 4 is larger and goes on reduced to stream order 1. The drainage density is calculated based on the formula “Stream length / Basin Area, the drainage density is grouped into 5

Volume 9 Issue 11 - 2019 1627 www.joics.org Journal of Information and Computational Science ISSN: 1548-7741

namely; 0 - 0.449 km/km2 covers 1116.31 sq.km (57.27per cent), 0.449 – 0.998 km/km2 with 462.5 sq.km (23.73per cent), 0.998 - 1.498 km/km2 with 287.7 sq.km (14.76per cent), 1.498 – 1.997 km/km2 with 66.9 sq.km (3.43per cent) and 1.997 – 2.497 km/km2 with 15.78 sq.km (0.81per cent). The high ranks areassigned to high drainage density and low rank to low drainage density.

Figure 7: Geology Classification Map Figure 8: Geomorphological Classification Map 3.5 Geology

The geology map prepared using the data obtained from Survey of India, which was digitized using the GIS and grouped with unique class. Ariyalur district has the following geological formation namely; Pink Migmatite, Fluvio-Marine, Sand Stone (clay) and Sand Stone (limestone). Each feature is assigned weightage based on its water holding properties. Geology map (fig.7) divided into four groups namely; Pink Migmatite covers 153.8 sq.km (7.89per cent), Fluvio-Marine with 453 sq.km (23.84per cent), Stand Stone (Clay) with 1122.86 sq.km (57.6per cent) and Stand Stone (Lime Stone) with 219.8 sq.km (11.27per cent).

3.6 Geomorphology Geomorphology is important factor in determining the groundwater potential zone, because it contains structures and landforms vital (Gnanachandrasamy, 2019) for water storage and extraction. The geomorphological features (fig.8). identified in the study area and classified into four groups namely; Pediplain, Flood Plain, Alluvial Plain and Upland. The weightage is based on the feature water holding capacity, the Pediplain covers 1377 sq.km (70.63per cent), Flood Plain with 81.57 sq.km (4.18per cent), Alluvial Plain with 110.8 (5.69per cent) and Upland with 380 (19.49per cent).

3.7 Soil Soil is essential element for various activities, it also provides a good support in harvesting water which ultimately helps in increase(Magesh et.al 2012) groundwater table. The different types of

Volume 9 Issue 11 - 2019 1628 www.joics.org Journal of Information and Computational Science ISSN: 1548-7741

soils (fig. 9) available in that area are clay, clay loam, sandy loam, loamy sand, sandy clay loam. Sandy loam covers 35per cent of the area, followed by clay 31per cent and clay loam cover the smallest area with 2.36per cent. The Clay covers 620 sq.km (31.83per cent), waterbodies with 24.81 sq.km (1.27per cent), clay loam with 46 (2.36per cent), Sandy Loam with 698.14 (35.81per cent), Loamy Sand with 508.19 (26 per cent) and Sandy Clay Loam with 52.46 (2.69per cent).

3.8 Rainfall Rainfall (fig. 10) is the vital factor contributing in groundwater recharge, through various hydrological processes. Rainfall is estimated using annual rainfall data collected from Indian Meteorological Department (IMD) for five station in Ariyalur District. Rainfall is classified into five groups namely; 608 – 669 mm, 669 – 731 mm, 731 – 793 mm, 793 – 855 mm and 855 – 916 mm. GIS tool is used to plot the station in spatially and Inverse Distance Weighted (IDW) used to interpolate the rainfall across the Ariyalur district. The 608 – 669 mm covers 431.37 sq.km, 669 – 731 mm with 785.42 sq.km, 731 – 793 mm with 439.87 sq.km, 793 – 855 mm with 170.93 sq.km and 855 – 916 mmwith 126.08 sq.km.

Figure 9: Soil Classification Map Figure 10: Rainfall Classification Map

3.9 Groundwater Potential Zone Groundwater potential zone (fig. 11) was delineated using eight parameters with assigned weightage (i) Landuse / Landcover (ii) Slope (iii) Lineament Density (iv) Drainage Density (v) Geology (vi) Geomorphology (vii) Soil and (viii) Rainfall. Weighted Overlay method used to explore the potential zone, based oneach parameter taken, it was subdivided based on the observing nature of the sub-features and classified using ranking 1(Very High) to 5 (Very Low).The results are divided into five groups namely; Very High, High, Moderate, Low and Very Low. The result reveals that Very High Potential is covered by 2.31 sq.km (7.6per cent),high Potential with 59.31 sq.km (3.04per cent), Moderate Potential with 918.68 sq.km (47.13per cent), Low Potential with 820.36 sq.km (42per cent) and Very Low Potential with 148.41 sq.km (7.61per cent).

Volume 9 Issue 11 - 2019 1629 www.joics.org Journal of Information and Computational Science ISSN: 1548-7741

Table 2: Groundwater Potential zone

Ground Water Potential Zone Area (km2) Percentage Very Low 148.41 7.61per cent Low 820.36 42.09per cent Moderate 918.68 47.13per cent High 59.31 3.04per cent Very High 2.31 0.12per cent 1949.07 100.00per cent

Figure 11: Groundwater Potential Map

Table3: Parameter wise Weightage and Ranking

SL.NO PARAMETER SUB_CLASSES POTENTIAL WEIGHTAGE RANK 1 Geology 1. Pink Migmatite Very High 1 2. Fluvio-Marine Medium 3 3.Sand stone (Clay) Low 20 4 4. Sand Stone (Lime Low 4 Stone) 2 Soil 0. Clay Very Low 5 1. Water body Very High 1 2. Clay loam Low 4 3. Sandy loam High 5 2 4. Loamy sand High 2 6. Sandy clay loam Medium 3 3 Landuse /Land 1.Agriculture High 2 Cover (LU/LC) 2.Fallow Land Low 4 3. Built up Very Low 5 4. Plantation High 15 2 5.Waterbodies Very High 1 6.WasteLand Medium 3 7.Forest High 2

Volume 9 Issue 11 - 2019 1630 www.joics.org Journal of Information and Computational Science ISSN: 1548-7741

4 Geomorphology 1. Pediplain High 2 2. Flood Plain High 2 3. Alluvial Plain Medium 20 3 4. Upland Medium 3

5 Slope 1. 0– 2o Very High 1 2. 2- 5 o High 2 3. 5 - 7 o High 5 2

6 Drainage 1. 0- 0.449 km/km2 Very Low 5 Density 2. 0.449 – 0.998 km/km2 Low 4 3. 0.998 - 1.498 km/km2 Medium 3 4. 1.498 – 1.997 km/km2 High 2 15 5. 1.997 – 2.497 km/km2 Very High 1

7 Lineament 1. 0- 0.339 km/km2 Very Low 5 2. 0.339 – 0.679 km/km2 Low 4 3. 0.679 - 1.019 km/km2 Medium 3 5 4. 1.019 – 1.359 km/km2 High 2 5. 1.359 – 1.699 km/km2 Very High 1 8 Rainfall 1. 608 – 669 mm Very Low 5 2. 669 – 731 mm Very Low 5 3. 731 – 793 mm Medium 3 4. 793 – 855 mm Medium 3 15 5. 5. 855 – 916 mm High 2

4. Conclusion

The study highlighted the usefulness of Geographical Information System and Remote Sensing in identification of Groundwater Potential Zone using the following parameter namely; Geology, Geomorphology, Soil, Rainfall, Landuse / Landcover, Slope, Lineament and Drainage Density. The analysis was performed with weightage units, based on the following characteristics of the eight parameter like permeability, porosity and specific yield. The result indicated that the northern patches and central part had few coverages which is Highly Potential for groundwater. Observation obtained from the result suggests that has more coverage of high potential zone, followed by the . Less Potential zone is mostly found along the Ariyalur Taluk and . It is important to maintain the ground water table in Ariyalur district because of the deficit in rainfall and various forms of mining activity carried on. The resulting factors from analysiswill provides the local bodies and government to manage and develop centre for storing and extraction of water during drought period.

Volume 9 Issue 11 - 2019 1631 www.joics.org Journal of Information and Computational Science ISSN: 1548-7741

References: 1. Agarwal, E., Agarwal, R., Garg, R.D and Garg, P.K(2013). Delineation of groundwater potential zone: An AHP/ANP approach. Journal Earth System Science. 122 (3) pp. 887–898.

2. Arulbalaji, D., Padmalal and Sreelash, K(2019). GIS and AHP Techniques Based Delineation of Groundwater Potential Zones: a case study from Southern Western Ghats, India. Science Report. 9(2082)pp 1-17.

3. Avtar, R., Singh, C. K., Shashtri, S., Singh, A and Mukherjee, S. (2014). Identification and analysis of groundwater potential zones in Ken–Betwariver linking area using remote sensing and geographic information system. Geocarto International. 25(5)pp. 379-396.

4. Chaudhary, B. S. and Kumar, S (2018). Identification of Groundwater Potential Zones using Remote Sensing and GIS of K-J Watershed, India. Journal Geological Society of India.Vol.97 17-721.

5. District Hand Book (2016). “District Statistical Hand Book (Ariyalur)”. .

6. District Survey Report Ariyalur District (2017). District Environment Impact Assessment Authority (Deiaa), Ariyalur.

7. Gnanachandrasamy, G., Zhou, Y., Bagyaraj, M., Venkatraman, S., Ramkumar, T and Wang, S. (2018). Remote Sensing and GIS Based Groundwater Potential ZoneMapping in Ariyalur District, Tamil Nadu. Journal Geological Society of India. Vol. 92 pp. 484-490.

8. Kumari, L(2018). Delineation of Potential Groundwater Zone Using RS and GIS: A Review. International Journal of Current Microbiology and Applied Sciences. 7(12) pp.196-203.

9. Lakshmi, S.V. and Reddy, Y.V.K(2018). Identification of Groundwater Potential Zones Using GIS and Remote Sensing. International Journal of Pure and Applied Mathematics. 119(17) pp. 3195-3210.

10. Margat, J. and Gun, J.V.D (2013). Groundwater around the World: A Geographic Synopsis. International Groundwater Resource Assessment Centre.

11. Magesh, N.S.,Chandrasekar, N and Soundranayagam, J.P (2012). Delineation of groundwater potential zones in , Tamil Nadu, using remote sensing, GIS and MIF techniques. Geoscience Frontiers. 3(2) pp. 189-196.

12. Marghany, M. and Hashim, M(2010). Lineament mapping using Multispectral Remote Sensing satellite data. International Journal of the Physical Sciences. 5(10) pp. 1501-1507.

13. Nadun, S. N.E.M., Maarof, I., Ghazali, R., Samad, A. M. and Adnan, R(2016). Sustainable Groundwater Potential Zone using Remote Sensing and GIS.6th International Colloquium on Signal Processing and Its Applications (CSPA). pp 104-109.

14. Reis, S. (2008). Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey. Sensor.Vol.8 pp. 6188-6202.

15. Ramli, M. F(2009). Lineament mapping in a tropical environment using Landsat imagery. International Journal of Remote Sensing. 30(23) pp. 277–6300.

16. Thirumalai, P. and Anand, P.H. (2017). A geographical analysis of land use in Ariyalur district. using remote sensing data and GIS. International Journal of Applied Research. 3(1) pp. 725-731.

17. CCCandAR and TNSCCC (2015). Climate Change Projection (Rainfall) for Ariyalur. In: District-Wise Climate Change Information for the State of Tamil Nadu. Centre for Climate Change and Adaptation Research (CCCandAR), Anna University and Tamil Nadu State Climate Change Cell (TNSCCC), Department of Environment (DoE), Government of Tamil Nadu, Chennai, Tamil Nadu, India.

Volume 9 Issue 11 - 2019 1632 www.joics.org