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GEOINFORMATICS BASED IDENTIFICATION of GROUNDWATER POTENTIAL ZONE in ARIYALUR DISTRICT, TAMIL NADU Anandakumar.I1* and Madha Suresh

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GEOINFORMATICS BASED IDENTIFICATION of GROUNDWATER POTENTIAL ZONE in ARIYALUR DISTRICT, TAMIL NADU Anandakumar.I1* and Madha Suresh Journal of Information and Computational Science ISSN: 1548-7741 GEOINFORMATICS BASED IDENTIFICATION OF GROUNDWATER POTENTIAL ZONE IN ARIYALUR DISTRICT, TAMIL NADU Anandakumar.I1* and Madha Suresh. V2 1 * Research Scholar, CNHDS, University of Madras, Chennai – 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. India 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 Ariyalur district 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 Perambalur was divided to form the present Ariyalur. The Ariyalur is surrounded by following districts, on the North by Cuddalore, Perambalur on west and on the south by Nagaipattinam and Thanjavur District. Administrative setup consists of three taluks namely, Ariyalur, Udayarpalayam andSendurai and six blocks Andimadam, Ariyalur, Jayankondan, Sendurai, 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).
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