<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">GEP</journal-id><journal-title-group><journal-title>Journal of Geoscience and Environment Protection</journal-title></journal-title-group><issn pub-type="epub">2327-4336</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/gep.2017.58017</article-id><article-id pub-id-type="publisher-id">GEP-78249</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth&amp;Environmental Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  Mapping the Spatial Distributions of Water Quality and Their Interpolation with Land Use/Land Cover Using GIS and Remote Sensing in Noyyal River Basin, Tamil Nadu, India
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Geetha</surname><given-names>Selvarani Arumaikkani</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Sivakumar</surname><given-names>Chelliah</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Maheswaran</surname><given-names>Gopalan</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Department of Mechanical Engineering, K.S.R. College of Engineering, Namakkal District, Tamil Nadu, India</addr-line></aff><aff id="aff3"><addr-line>VSA Group of Institutions, VSA School of Engineering &amp;amp; Management Salem, Tamil Nadu, India</addr-line></aff><aff id="aff1"><addr-line>Department of Civil Engineering, K.S.R. College of Engineering, Namakkal District, Tamil Nadu, India</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>geetha_env2004@yahoo.co.in(GSA)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>18</day><month>07</month><year>2017</year></pub-date><volume>05</volume><issue>08</issue><fpage>211</fpage><lpage>220</lpage><history><date date-type="received"><day>June</day>	<month>19,</month>	<year>2017</year></date><date date-type="rev-recd"><day>Accepted:</day>	<month>August</month>	<year>6,</year>	</date><date date-type="accepted"><day>August</day>	<month>9,</month>	<year>2017</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Noyyal River is historically, ecologically and culturally significant river in Kongu region of western Tamilnadu. More than 100 villages are situated along the banks of the Noyyal River and it’s the was the best site of inhabitation on both the sides of the river up to 3 km from the river before the emergence of the issue of industrial pollution. But now river Noyyal was highly polluted by domestic and industrial growth by discharging of both domestic and industrial are discharged without any treatment. So methodology was proposed to identify the suitable zone for groundwater quality by using land use/land cover data along with groundwater quality in analytic hierarchy process. Suitability of groundwater for drinking was identified in the study area by collecting 63 samples in both postmonsoon and premonsoon as per Indian standards. To evaluate the land use pattern of the study area, land use/land cover map was prepared from satellite images of LISS III by using supervised classification according to National Remote Sensing Agency (NRSA) using Erdas imagine 8.4 software. Using ArcGIS software, weighted overlay analyses were carried out to identify the suitable zones for groundwater quality in postmonsoon and premonsoon and finally these two thematic maps were integrated with land use/land cover map to identify the suitable zone for quality of water. The interpretation shows that groundwater in most of the locations were unsuitable for drinking purposes.
 
</p></abstract><kwd-group><kwd>Noyyal River</kwd><kwd> Drinking Water Quality</kwd><kwd> Total Dissolved Solids</kwd><kwd> GIS</kwd><kwd> Land Use</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Groundwater is a vital natural resource and it is used for drinking, irrigation and industrial purposes. Nowadays the quality of groundwater is deteriorating day by day due to over exploitation of groundwater and improper methods of solid waste disposal and untreated effluents into the water bodies [<xref ref-type="bibr" rid="scirp.78249-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.78249-ref2">2</xref>] [<xref ref-type="bibr" rid="scirp.78249-ref3">3</xref>] . And also the temporal changes in the origin and constitution of the recharged water, hydrologic and human factors may cause periodic change in groundwater quality. And this water pollution not only affects water quality but also threatens human health, economic development, and social prosperity. Hence, evaluation of groundwater quality status for human consumption is important for socio-economic growth, development and also for establishing a database for planning future water. Mapping the spatial distributions of major elements and their interpolation with the geology and land use/land cover maps in GIS environment [<xref ref-type="bibr" rid="scirp.78249-ref4">4</xref>] [<xref ref-type="bibr" rid="scirp.78249-ref5">5</xref>] have contributed for the better understanding of the chemical processes of water and the methods of their acquisition. Several studies were carried out in the past two decades for identifying the groundwater quality zones using GIS and remote sensing data and the methodology proposed in the literature are [<xref ref-type="bibr" rid="scirp.78249-ref6">6</xref>] - [<xref ref-type="bibr" rid="scirp.78249-ref18">18</xref>] . Noyyal River is one of the tributaries of the river Cauvery, which originates from the hills of Vellingiri, also termed as southern Kailayam in Western Ghats and flows towards the southwest of Coimbatore district in Tamil Nadu, and finally it ends in river Cauvery at Kodumudi in Karur district. It flows through Coimbatore, Tiruppur, Erode and Karur districts with its catchments in seven taluks (Coimbatore, Tiruppur, Avinashi, Palladam, Dharapuram, Erode and Karur). It flows over a length of about 180 Kms covering an area of 3510 km<sup>2</sup>. Out of the total area in the basin, 1752 km<sup>2</sup> (49.9%) of the area is under cultivation and 178 km<sup>2</sup> (5.1%) is covered by forest and wetland growing teak and eucalyptus and the rest 1580 km<sup>2</sup> (45%) is barren land [<xref ref-type="bibr" rid="scirp.78249-ref19">19</xref>] . The boundary of the river basin is between north latitude 10˚54'00&quot; to 11˚19'03&quot; and east longititude 76˚39'30&quot; to 77˚55'25&quot; which is shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>. More than 100 villages are</p><fig id="fig1"  position="float"><label><xref ref-type="fig" rid="fig1">Figure 1</xref></label><caption><title> Key plan showing the study area details</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/17-2170467x2.png"/></fig><p>situated on both sides of the banks of river Noyyal. Nearly 6000 acres of cultivable land in Coimbatore district is irrigated by using river water [<xref ref-type="bibr" rid="scirp.78249-ref20">20</xref>] .</p><p>The average rainfall in the basin is about 700 mm. The river flows from west to east and its maximum elevation is around 1600 m above mean sea level and the minimum elevation is 100 m above mean sea level [<xref ref-type="bibr" rid="scirp.78249-ref21">21</xref>] . It is also believed that water contains natural medicine and therefore it is good for health. Noyyal is a seasonal river which has good flow only for short periods during the northeast and southwest monsoons. Occasionally flash floods occur when there is heavy rain in the catchment areas [<xref ref-type="bibr" rid="scirp.78249-ref22">22</xref>] . Apart from these periods, there is only scanty flow in most part of the year. Generally, a subtropical climate condition prevails in the river basin. It is divided into, winter from January to February, summer from March to May and it is followed by southwest monsoon from June to September and from October to December constituting the postmonsoon season [<xref ref-type="bibr" rid="scirp.78249-ref21">21</xref>] . The rainfall in western parts is comparatively more during the southwest monsoon season while the eastern parts get more rainfall during the northeast monsoon season [<xref ref-type="bibr" rid="scirp.78249-ref23">23</xref>] . The precipitation is unevenly distributed throughout the year and often completely lacking of rainfall during dry period [<xref ref-type="bibr" rid="scirp.78249-ref23">23</xref>] . The present study is to evaluate the physico-chemical characteristics of groundwater in and around a Noyyal River basin and integrated with land use/land cover data for the assessment and suitability of groundwater for drinking purposes.</p></sec><sec id="s2"><title>2. Materials and Methods</title><p>The base map of the study area was created by using Survey of India (SOI) toposheets of 58A/12, 58A/16, 58B/9, 58B/13, 58E/3, 58E/4, 58E/7, 58E/8, 58E/12, 58E/16, 58F/1, 58F/5, 58F/9, 58F/13 (1:50,000). Sixty three groundwater (bore well) samples were collected in a cleaned polythene bottle in and around the catchments of the basin during the month of January 2015 (postmonsoon) and June 2015 (premonsoon) to know the status of various physico-chemical parameters and their impacts. The sampling locations were marked in the base map which is shown in <xref ref-type="fig" rid="fig2">Figure 2</xref> and its corresponding names are given in the <xref ref-type="table" rid="table1">Table 1</xref>. Standard procedure and methods were followed for preservation and analysis of the groundwater samples [<xref ref-type="bibr" rid="scirp.78249-ref24">24</xref>] . The analysed results were compared with Indian Standard (IS) 10,500-1991 [<xref ref-type="bibr" rid="scirp.78249-ref25">25</xref>] . The suitability of groundwater for drinking was identified based on Total Dissolved Solids (TDS), chlorides, calcium, hardness and alkalinity for both postmonsoon and premonsoon.</p><p>Using ArcGIS software, weighted overlay analyses were carried out to identify the suitable zones for groundwater quality in postmonsoon and premonsoon and finally these two thematic maps were overlaid to identify the suitable zones for Drinking purposes. This analysis has categorised the study area into three zones (good, moderate and poor), which would enable the user to locate the potable water without any problem which is shown in <xref ref-type="table" rid="table2">Table 2</xref>. Each class in every thematic map was assigned a weight. Highest weight was assigned to the class that was most favourable for the drinking and the lowest weight was assigned to the class that was least favourable/unfavourable class. To evaluate the</p><fig id="fig2"  position="float"><label><xref ref-type="fig" rid="fig2">Figure 2</xref></label><caption><title> Key plan showing sampling stations</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/17-2170467x3.png"/></fig><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Details of the sampling locations</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Sl.No</th><th align="center" valign="middle" >Name of Habitation</th><th align="center" valign="middle" >Sl.No</th><th align="center" valign="middle" >Name of Habitation</th></tr></thead><tr><td align="center" valign="middle" >S1</td><td align="center" valign="middle" >Iruttupallam</td><td align="center" valign="middle" >S2</td><td align="center" valign="middle" >Perumalswamykovil</td></tr><tr><td align="center" valign="middle" >S3</td><td align="center" valign="middle" >Thimmekavanporam</td><td align="center" valign="middle" >S4</td><td align="center" valign="middle" >Mathipalayam</td></tr><tr><td align="center" valign="middle" >S5</td><td align="center" valign="middle" >Perur</td><td align="center" valign="middle" >S6</td><td align="center" valign="middle" >Ramachattipalayam</td></tr><tr><td align="center" valign="middle" >S7</td><td align="center" valign="middle" >Ukkadam</td><td align="center" valign="middle" >S8</td><td align="center" valign="middle" >Nanjundapuram</td></tr><tr><td align="center" valign="middle" >S9</td><td align="center" valign="middle" >Varadayyampalayam</td><td align="center" valign="middle" >S10</td><td align="center" valign="middle" >Kalappatti</td></tr><tr><td align="center" valign="middle" >S11</td><td align="center" valign="middle" >Karaiyampalayam</td><td align="center" valign="middle" >S12</td><td align="center" valign="middle" >Irugur</td></tr><tr><td align="center" valign="middle" >S13</td><td align="center" valign="middle" >Pattanampudur</td><td align="center" valign="middle" >S14</td><td align="center" valign="middle" >Kariyampalayam</td></tr><tr><td align="center" valign="middle" >S15</td><td align="center" valign="middle" >Indiranagar</td><td align="center" valign="middle" >S16</td><td align="center" valign="middle" >Alampalaiyam</td></tr><tr><td align="center" valign="middle" >S17</td><td align="center" valign="middle" >Sulur</td><td align="center" valign="middle" >S18</td><td align="center" valign="middle" >Muttukavundampudur</td></tr><tr><td align="center" valign="middle" >S19</td><td align="center" valign="middle" >Rasipalayam</td><td align="center" valign="middle" >S20</td><td align="center" valign="middle" >Apanayakkanpattipudur</td></tr><tr><td align="center" valign="middle" >S21</td><td align="center" valign="middle" >Uppilipalayam</td><td align="center" valign="middle" >S22</td><td align="center" valign="middle" >Puduppalayam</td></tr><tr><td align="center" valign="middle" >S23</td><td align="center" valign="middle" >Karumattampatti</td><td align="center" valign="middle" >S24</td><td align="center" valign="middle" >Senniyandavarkovil</td></tr><tr><td align="center" valign="middle" >S25</td><td align="center" valign="middle" >Semmandampalayam</td><td align="center" valign="middle" >S26</td><td align="center" valign="middle" >Vellandipalayam</td></tr><tr><td align="center" valign="middle" >S27</td><td align="center" valign="middle" >Periyakattupalayam</td><td align="center" valign="middle" >S28</td><td align="center" valign="middle" >Arangattupalayam</td></tr><tr><td align="center" valign="middle" >S29</td><td align="center" valign="middle" >Ayyampalayam</td><td align="center" valign="middle" >S30</td><td align="center" valign="middle" >Rasakkaundampalayam</td></tr><tr><td align="center" valign="middle" >S31</td><td align="center" valign="middle" >Mangalam</td><td align="center" valign="middle" >S32</td><td align="center" valign="middle" >Rasakavundanpalayam</td></tr><tr><td align="center" valign="middle" >S33</td><td align="center" valign="middle" >Nallikavundapalayam</td><td align="center" valign="middle" >S34</td><td align="center" valign="middle" >Tirumuruganpundi</td></tr><tr><td align="center" valign="middle" >S35</td><td align="center" valign="middle" >Murugapalayam</td><td align="center" valign="middle" >S36</td><td align="center" valign="middle" >Karuvampalayam</td></tr><tr><td align="center" valign="middle" >S37</td><td align="center" valign="middle" >Chennimalaipalayam</td><td align="center" valign="middle" >S38</td><td align="center" valign="middle" >Krishnapuram</td></tr><tr><td align="center" valign="middle" >S39</td><td align="center" valign="middle" >Nallur</td><td align="center" valign="middle" >S40</td><td align="center" valign="middle" >Perumanallur</td></tr><tr><td align="center" valign="middle" >S41</td><td align="center" valign="middle" >Uttukkuli</td><td align="center" valign="middle" >S42</td><td align="center" valign="middle" >Molakavundampuam</td></tr><tr><td align="center" valign="middle" >S43</td><td align="center" valign="middle" >Velampalaiyam</td><td align="center" valign="middle" >S44</td><td align="center" valign="middle" >Aruvangattupuram</td></tr><tr><td align="center" valign="middle" >S45</td><td align="center" valign="middle" >Periyakunnampalayam</td><td align="center" valign="middle" >S46</td><td align="center" valign="middle" >Manur</td></tr><tr><td align="center" valign="middle" >S47</td><td align="center" valign="middle" >Kariyampalayam</td><td align="center" valign="middle" >S48</td><td align="center" valign="middle" >Ramakkaranpalayam</td></tr><tr><td align="center" valign="middle" >S49</td><td align="center" valign="middle" >Kavundanpalayam</td><td align="center" valign="middle" >S50</td><td align="center" valign="middle" >Moskuttivalasu</td></tr><tr><td align="center" valign="middle" >S51</td><td align="center" valign="middle" >Chennimalai</td><td align="center" valign="middle" >S52</td><td align="center" valign="middle" >Puchchakkattuvalasu</td></tr><tr><td align="center" valign="middle" >S53</td><td align="center" valign="middle" >Pallakkatupudur</td><td align="center" valign="middle" >S54</td><td align="center" valign="middle" >Uttamapalayam</td></tr><tr><td align="center" valign="middle" >S55</td><td align="center" valign="middle" >Palanikavundanvalasu</td><td align="center" valign="middle" >S56</td><td align="center" valign="middle" >Vettukattuvalasu</td></tr><tr><td align="center" valign="middle" >S57</td><td align="center" valign="middle" >Sengodampalayam</td><td align="center" valign="middle" >S58</td><td align="center" valign="middle" >Subramaniyapuram</td></tr><tr><td align="center" valign="middle" >S59</td><td align="center" valign="middle" >Valliyampalayam</td><td align="center" valign="middle" >S60</td><td align="center" valign="middle" >Velliyankattupudur</td></tr><tr><td align="center" valign="middle" >S61</td><td align="center" valign="middle" >Murugampalayam</td><td align="center" valign="middle" >S62</td><td align="center" valign="middle" >Adiyappakaundanvalasu</td></tr><tr><td align="center" valign="middle" >S63</td><td align="center" valign="middle" >Velaiyampalayam</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Criteria for the classification of thematic maps of groundwater quality and land use/land cover for drinking purpose</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >S.No</th><th align="center" valign="middle" >Parameters</th><th align="center" valign="middle" >Descriptive scale</th><th align="center" valign="middle" >Score</th><th align="center" valign="middle" >Weightage</th></tr></thead><tr><td align="center" valign="middle"  rowspan="3"  >1)</td><td align="center" valign="middle"  rowspan="3"  >Hardness (mg/l)</td><td align="center" valign="middle" >Good</td><td align="center" valign="middle" >3</td><td align="center" valign="middle"  rowspan="3"  >20</td></tr><tr><td align="center" valign="middle" >Moderate</td><td align="center" valign="middle" >2</td></tr><tr><td align="center" valign="middle" >Poor</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle"  rowspan="3"  >2)</td><td align="center" valign="middle"  rowspan="3"  >TDS (mg/l)</td><td align="center" valign="middle" >Good</td><td align="center" valign="middle" >3</td><td align="center" valign="middle"  rowspan="3"  >30</td></tr><tr><td align="center" valign="middle" >Moderate</td><td align="center" valign="middle" >2</td></tr><tr><td align="center" valign="middle" >Poor</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle"  rowspan="3"  >3)</td><td align="center" valign="middle"  rowspan="3"  >Calcium (mg/l)</td><td align="center" valign="middle" >Good</td><td align="center" valign="middle" >3</td><td align="center" valign="middle"  rowspan="3"  >5</td></tr><tr><td align="center" valign="middle" >Moderate</td><td align="center" valign="middle" >2</td></tr><tr><td align="center" valign="middle" >Poor</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle"  rowspan="3"  >4)</td><td align="center" valign="middle"  rowspan="3"  >Alkalinity (mg/l)</td><td align="center" valign="middle" >Good</td><td align="center" valign="middle" >3</td><td align="center" valign="middle"  rowspan="3"  >10</td></tr><tr><td align="center" valign="middle" >Moderate</td><td align="center" valign="middle" >2</td></tr><tr><td align="center" valign="middle" >Poor</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle"  rowspan="3"  >5)</td><td align="center" valign="middle"  rowspan="3"  >Chlorides (mg/l)</td><td align="center" valign="middle" >Good</td><td align="center" valign="middle" >3</td><td align="center" valign="middle"  rowspan="3"  >5</td></tr><tr><td align="center" valign="middle" >Moderate</td><td align="center" valign="middle" >2</td></tr><tr><td align="center" valign="middle" >Poor</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle"  rowspan="9"  >6)</td><td align="center" valign="middle"  rowspan="9"  >Land use/Land cover</td><td align="center" valign="middle" >Land with scrub</td><td align="center" valign="middle" >3</td><td align="center" valign="middle"  rowspan="9"  >30</td></tr><tr><td align="center" valign="middle" >Crop land</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >Fallow land</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >Scrub forest</td><td align="center" valign="middle" >2</td></tr><tr><td align="center" valign="middle" >Built up land</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >Water bodies</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >Land without scrub</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >Forest blank</td><td align="center" valign="middle" >2</td></tr><tr><td align="center" valign="middle" >Open forest</td><td align="center" valign="middle" >2</td></tr></tbody></table></table-wrap><p>land use pattern of the study area, land use/land cover map was prepared from satellite images of LISS III by using supervised classification according to National Remote Sensing Agency (NRSA) [<xref ref-type="bibr" rid="scirp.78249-ref26">26</xref>] with Erdas imagine 8.4 software. Finally land use/land cover map was integrated with quality map to identify the suitable zone for quality of water.</p></sec><sec id="s3"><title>3. Result and Discussion</title><p>By means of ArcGIS superimpose was prepared by adding up the weights of the classified themes of postmonsoon, premonsoon and land use/land cover map were used to prepare a map of groundwater quality zone for drinking purpose of the study area.</p><p>Overlaying was done by adding the weights of the classified themes of hardness, TDS, alkalinity, chlorides and calcium were used to prepare a map of groundwater quality for drinking purpose in ArcGIS platform. This analysis has categorized in the study area into three zones (good, moderate and poor). The spatial variation of suitable zones for drinking purposes based on groundwater quality for both postmonsoon and premonsoon are shown in <xref ref-type="fig" rid="fig3">Figure 3</xref> and <xref ref-type="fig" rid="fig4">Figure 4</xref>. GIS analysis, reveals that the quality of groundwater was predominantly poor category in both premonsoon and postmonsoon, while the good category water found in Thondamuthur block during premonsoon period. The suitable quality found in southwestern, western and southeastern side of the river basin. The discharging of industrial and Drinking effluent on either side of the river were ultimately polluting the groundwater of the study area and this reflects in the downstream of Tiruppur during premonsoon period and also the potable ground water was found in larger area than during the postmonsoon period.</p><p>Land is a prime natural resource and the mapping of land use/land cover is essential for planning and development of land and water resources [<xref ref-type="bibr" rid="scirp.78249-ref27">27</xref>] . But anthropogenic and natural forces modify the landscape. So it is important to monitor and assess these alterations to avoid the misuse of usable land into wastelands. Timely and accurate information on the existing land use/land cover</p><fig id="fig3"  position="float"><label><xref ref-type="fig" rid="fig3">Figure 3</xref></label><caption><title> Spatial distribution of groundwater quality for drinking in postmonsoon</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/17-2170467x4.png"/></fig><fig id="fig4"  position="float"><label><xref ref-type="fig" rid="fig4">Figure 4</xref></label><caption><title> Spatial distribution of groundwater quality for drinking in premonsoon</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/17-2170467x5.png"/></fig><p>pattern and its spatial distribution and changes is a prerequisite for planning, utilisation and formulation of policies and programmes for making micro and macro-level developmental plan [<xref ref-type="bibr" rid="scirp.78249-ref27">27</xref>] . Remote sensing technology along with GIS is cost-effective and best utilised solutions for integration of various data sets for both macro and micro level analysis which helps in identifying the problem areas and suggest conservation measures [<xref ref-type="bibr" rid="scirp.78249-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.78249-ref7">7</xref>] . The mapping and monitoring of the land use/land cover requires land use classification system. One of the most widely used classification scheme was developed by National Remote Sensing Agengy (NRSA 1995) [<xref ref-type="bibr" rid="scirp.78249-ref26">26</xref>] . Land use/land cover change detection mapping of the study area has been done by using software ERDAS Imagine 8.4 from Landsat TM and IRS LISS III data. The ten major levels of land use/land cover categories were interpreted in the image of the study area and is shown in <xref ref-type="fig" rid="fig5">Figure 5</xref> namely built up land having poor sanitary conditions and anthropogenic activities, groundwater quality is deteriorating significantly in the city area as compared to water fields so it has poor groundwater quality zone, fallow land and agriculture land, land with scrub, land without scrub, water bodies fields facilitate the recharge of groundwater during monsoon periods and also provide the water supply to city through production wells [<xref ref-type="bibr" rid="scirp.78249-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.78249-ref7">7</xref>] . So it has very good groundwater quality zone, dense forest, scrub forest, forest blank and open forest having moderate groundwater zone.</p><p>In the study area, groundwater quality map was prepared by overlaying and adding a weightage of classified themes from postmonsoon, premonsoon and land use/land cove map. This analysis has categorized the study area into three zones (good, moderate and poor). The spatial variation for drinking purpose (<xref ref-type="fig" rid="fig6">Figure 6</xref>) based on the thematic map was found under moderate category in south western, eastern and north eastern side of the study area, while good category water was found in Thondamuthur block in south eastern side of the study area. Poor category was found in southern, centre and northern parts of the study area. The highly polluted blocks were Annur, Avinashi, Tiruppur, Sulur,</p><fig id="fig5"  position="float"><label><xref ref-type="fig" rid="fig5">Figure 5</xref></label><caption><title> Land use classification</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/17-2170467x6.png"/></fig><fig id="fig6"  position="float"><label><xref ref-type="fig" rid="fig6">Figure 6</xref></label><caption><title> Spatial distribution of groundwater quality showing suitable zone for drinking</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/17-2170467x7.png"/></fig><p>Sultanpet, Palladam, Pongalaur, Uthukuli and few isolated parts of Kangeyam and Perundurai blocks.</p></sec><sec id="s4"><title>4. Conclusion</title><p>Geospatial techniques are applied to identify and assess the groundwater quality zones for drinking purposes. The quality zone is assessed by integrating water quality map and land use/land cover map with categorized into good, moderate and poor. The spatial distribution shows that the percentage of suitable zones for drinking is higher in postmonsoon as compared to premonsoon due to high recharge and dilution of contaminants during monsoon and postmonsoon. Based on the interpretation, groundwater quality of Noyyal river basin is not suitable in few locations for drinking purposes and also indicates that, the river is heavily polluted only after entering the Sarkar Samakulam area of Coimbatore district and continues till the end of the basin. The drinking water quality is deteriorated at some sites which is indicated by the excess presence of total dissolved solids, hardness, alkalinity and chloride which is due to dense population and discharge of industrial and drinking effluents. So groundwater in these locations can be used for irrigation under special circumstance only. If the improper disposal of municipal and industrial waste is continuously falling in the Noyyal river basin, then there is a chance for over pollution in future, which affects the aquifer system of the basin to a greater extent.</p></sec><sec id="s5"><title>Cite this paper</title><p>Arumaikkani, G.S., Chelliah, S. and Gopalan, M. (2017) Mapping the Spatial Distributions of Water Quality and Their Interpolation with Land Use/Land Cover Using GIS and Remote Sensing in Noyyal River Basin, Tamil Nadu, India. Journal of Geoscience and Environment Protection, 5, 211-220. https://doi.org/10.4236/gep.2017.58017</p></sec></body><back><ref-list><title>References</title><ref id="scirp.78249-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">de A. Eunice, M., Helba, A.Q.P., Ivam, H.S., de O.L. Raimundo, A. and Maria, J.G. (2008) Land Use Effects in Groundwater Composition of an Alluvial Aquifer (Trussu River, Brazil) by Multivariate Techniques. Environmental Research, 106, 170-177. https://doi.org/10.1016/j.envres.2007.10.008</mixed-citation></ref><ref id="scirp.78249-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Yammani, S. (2007) Groundwater Quality Suitable Zones Identification: Application of GIS, Chittoor Ara, Andhra Pradesh, India. Environmental Geology, 53, 201-210. https://doi.org/10.1007/s00254-006-0634-1</mixed-citation></ref><ref id="scirp.78249-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Bridget, R.C. and Reedy, C.R. (2005) Impacts of Land Use and Land Cover Change on Groundwater Recharge and Quality in the Southwestern US. Global Change Biology, 11, 1577-1593. https://doi.org/10.1111/j.1365-2486.2005.01026.x</mixed-citation></ref><ref id="scirp.78249-ref4"><label>4</label><mixed-citation publication-type="other" xlink:type="simple">Zhang, W., Kinniburgh, D. and Gabos, S. (2013) Assessment of Groundwater Quality in Alberta, Canada Using GIS Mapping. 3rd International Conference Medical, Biological and Paramedical Science, Bali, 199-203.</mixed-citation></ref><ref id="scirp.78249-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">Vijay, R., Samal, D.R. and Mohapatra, P.K. (2001) GIS Based Identification and Assessment of Groundwater Quality Potential Zones in Puri City, India. Journal of Water Resource and Protection, 3, 440-447. https://doi.org/10.4236/jwarp.2011.36054</mixed-citation></ref><ref id="scirp.78249-ref6"><label>6</label><mixed-citation publication-type="other" xlink:type="simple">Geetha Selvarani, A. and Elangovan, K. (2009) Hydrogeochemistry Analysis of Groundwater in Noyyal River Basin, Tamilnadu, India. International Journal of Applied Environmental Sciences, 4, 211-227.</mixed-citation></ref><ref id="scirp.78249-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Geetha Selvarani, A. and Elangovan, K. (2008) Assessment of Groundwater Quality of Noyyal River Basin. Journal of Indian Association for Environmental Management, 35, 133-138.</mixed-citation></ref><ref id="scirp.78249-ref8"><label>8</label><mixed-citation publication-type="other" xlink:type="simple">Amer, R., Ripperdan, R., Wang, T. and Encarnacio’n, J. (2012) Groundwater Quality and Management in Arid and Semi-Arid Regions: Case Study, Central Eastern Desert of Egypt. Journal of African Earth Sciences, 69, 13-25. https://doi.org/10.1016/j.jafrearsci.2012.04.002</mixed-citation></ref><ref id="scirp.78249-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Chaudhary, B.S., Saroha, G.P. and Yadav, Manoj (2008) Human Induced Land Use/Land Cover Changes in Northern Part of Gurgaon District, Haryana, India Natural Resources Census Concept. Journal of Human Ecology, 23, 243-252.</mixed-citation></ref><ref id="scirp.78249-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Krishnaraj, S., Kumar, S. and Elango, K.P. (2015) Spatial Analysis of Groundwater Quality Using Geographic Information System a Case Study. IOSR Journal of Environmental Science, Toxicology and Food Technology, 9, 01-06.</mixed-citation></ref><ref id="scirp.78249-ref11"><label>11</label><mixed-citation publication-type="other" xlink:type="simple">Venkateswaran, S., Elangomannan, M. and Vijay Prabhu, M. (2012) Evaluation of Physico-Chemical Characteristics in Groundwater Using GIS—A Case Study of Chinnar Sub-Basin of Cauvery River, Tamil Nadu, India. Ultra Scientist, 24, 387-398.</mixed-citation></ref><ref id="scirp.78249-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">Venkateswaran, S. and Deepa, S. (2013) Assessment of Groundwater Quality Using GIS Techniques in Vaniyar Watershed, Ponnaiyar River, Tamil Nadu. ICWRCOE 2015, 4, 1283-1290.</mixed-citation></ref><ref id="scirp.78249-ref13"><label>13</label><mixed-citation publication-type="other" xlink:type="simple">Nas, B. and Berktay, A. (2010) Groundwater Quality Mapping in Urban Groundwater Using GIS. Environmental Monitoring and Assessment, 160, 215-227.</mixed-citation></ref><ref id="scirp.78249-ref14"><label>14</label><mixed-citation publication-type="other" xlink:type="simple">Dinesh, C and Geetha Selvarani, A. (2016) Relationship between Landuse and Water Quality in Salem District. International Journal for Innovative Research in Science &amp; Technology, 2, 68-72.</mixed-citation></ref><ref id="scirp.78249-ref15"><label>15</label><mixed-citation publication-type="other" xlink:type="simple">Singh, A.A., Singh, P.K., Dhakate, R. and Singh, N.P. (2013) Groundwater Quality Appraisal and Its Hydrochemical Characterization in Ghaziabad (A Region of Indo-Gangetic Plain), Uttar Pradesh, India. Applied Water Sciences, 3, 132-137.</mixed-citation></ref><ref id="scirp.78249-ref16"><label>16</label><mixed-citation publication-type="other" xlink:type="simple">Sharma, T., Satya Kiran, P.V., Singh, T.P., Trivedi, A.V. and Navalgund, R.R. (2001) Hydrologic Response of a Watershed to Land Use Changes: A Remote Sensing and GIS Approach. International Journal of Remote Sensing, 22, 2095-2108. https://doi.org/10.1080/01431160117359</mixed-citation></ref><ref id="scirp.78249-ref17"><label>17</label><mixed-citation publication-type="other" xlink:type="simple">Khan, H.H., Khan, A., Ahmed, S. and Perrin, J. (2011) GIS-Based Impact Assessment of Land-Use Changes on Groundwater Quality: Study from a Rapidly Urbanizing Region of South India. Environmental Earth Sciences, 63, 1289-1302. https://doi.org/10.1007/s12665-010-0801-2</mixed-citation></ref><ref id="scirp.78249-ref18"><label>18</label><mixed-citation publication-type="other" xlink:type="simple">Tu, J. and Xia, Z.G. (2008) Examining Spatially Varying Relationships between Land Use and Water Quality Using Geographically Weighted Regression I: Model Design and Evaluation. Science of the Total Environment, 407, 358-378. https://doi.org/10.1016/j.scitotenv.2008.09.031</mixed-citation></ref><ref id="scirp.78249-ref19"><label>19</label><mixed-citation publication-type="other" xlink:type="simple">Senthilnathan, S.A. (2001) Micro Level Environment Status Report of River Noyyal Basin. Essemm Envirotech Company, Tiruppur.</mixed-citation></ref><ref id="scirp.78249-ref20"><label>20</label><mixed-citation publication-type="other" xlink:type="simple">Appasamy, P. and Nelliyat, P. (2007) Compensating the Loss of Ecosystem Services Due to Pollution in Noyyal River Basin, Tamil Nadu. Madras School of Economics, Chennai, 7 p.</mixed-citation></ref><ref id="scirp.78249-ref21"><label>21</label><mixed-citation publication-type="other" xlink:type="simple">Sankaraaj, L., Subramanian, T.P., Siddhamalai, A. and Farooque Ahmed, N. (2002) Quality of Soil and Water for Agriculture in Noyyal River Basin. Tamil Nadu’, Joint Director of Agriculture (Research), Soil Survey and Land Use Organization, Tamil Nadu Department of Agriculture, Coimbatore, 2-4.</mixed-citation></ref><ref id="scirp.78249-ref22"><label>22</label><mixed-citation publication-type="other" xlink:type="simple">Furn, K. (2004) Effects of Dyeing and Bleaching Industries on the Area around the Orathupalayam Dam in Southern India. This Study Was Carried Out within the Framework of a Scholarship Programme, Minor Field Study (MFS), Which Is Funded by the Swedish International Development Cooperation Agency (Sida).</mixed-citation></ref><ref id="scirp.78249-ref23"><label>23</label><mixed-citation publication-type="other" xlink:type="simple">Shodhganga (2002) Profile of Noyyal River Basin.http://shodhganga.inflibnet.ac.in/bitstream/10603/33831/3/chapter3.pdf</mixed-citation></ref><ref id="scirp.78249-ref24"><label>24</label><mixed-citation publication-type="other" xlink:type="simple">APHA (1995) Standard Methods for the Examination of Water and Waste Water. 19th Edition, American Public Health Association, Washington DC.</mixed-citation></ref><ref id="scirp.78249-ref25"><label>25</label><mixed-citation publication-type="other" xlink:type="simple">BIS (1991) Drinking Water Specification, Bureau of Indian Standards. New Delhi, 10500. http://bis.org.in/bis/html/10500.html</mixed-citation></ref><ref id="scirp.78249-ref26"><label>26</label><mixed-citation publication-type="other" xlink:type="simple">NRSA (1995) Integrated Mission for Sustainable Development (IMSD)—Technical Guidelines. National Remote Sensing Agency, Hyderabad.</mixed-citation></ref><ref id="scirp.78249-ref27"><label>27</label><mixed-citation publication-type="other" xlink:type="simple">Srivastava K., Sinha, A. and Upadhyay, R. (2006) Monitoring Land Use/Land Cover of Maharajganj District of Uttar Pradesh Using Digital Remote Sensing Technique. Remote Sensing Applications Centre, U.P., Lucknow, 188-190.</mixed-citation></ref></ref-list></back></article>