2013
DOI: 10.1007/s11356-013-1746-2
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Evaluation of the groundwater quality feasibility zones for irrigational purposes through GIS in Omalur Taluk, Salem District, South India

Abstract: The present work is employed in Omalur Taluk (study area 538.10 km(2)), Salem District, Tamil Nadu, India. Eighty-nine groundwater samples were collected during pre-monsoon (May) 2011 and were analyzed for major cations and anions. The irrigational parameters like; EC, Kelley's ratio, sodium absorption ratio (SAR) values, Mg(2+) hazards, HCO3 (-) and residual sodium carbonate (RSC) have been worked out to know the suitability of the groundwater for irrigational purpose. Wilcox diagram indicates that out of 89 … Show more

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Cited by 31 publications
(10 citation statements)
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“…Water samples were taken from June to August 2016 with an approximate interval of two weeks according to phonological stage of rice crop. 14 [32] were calculated. Values obtained from each water resource were treated as replicates.…”
Section: Water Quality Assessmentmentioning
confidence: 99%
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“…Water samples were taken from June to August 2016 with an approximate interval of two weeks according to phonological stage of rice crop. 14 [32] were calculated. Values obtained from each water resource were treated as replicates.…”
Section: Water Quality Assessmentmentioning
confidence: 99%
“…It has suggested that the sodium problem in irrigation water could be very conveniently worked out on the basis of the values of ESR or Kelley's ratio. Generally, water is considered as unfavorable for irrigation if ESR be more than one [32]. Therefore, FW and WW are unfavorable and favorable water for irrigation, respectively.…”
Section: Assessment Of Water Quality For Irrigationmentioning
confidence: 99%
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“…Khadangi et al (2009) compared ANFIS with radial basis function (RBF) models in daily stream flow forecasting and demonstrated that ANFIS give better results than RBF. Moreover, geographic information system (GIS) is a powerful tool for use in environmental problem solving and in conducting groundwater modeling such as mapping the groundwater quality parameters, interpretation of groundwater quality data, evaluation of the groundwater quality feasibility zones for irrigational purposes, creating groundwater contamination vulnerability maps as the most common application of this technique and so on (Saraf et al 1994;Durbude and Vararrajan 2007;Karunanidhi et al 2013;Bouzourra et al 2014). Therefore, in order to develop a model using neuro-fuzzy techniques in a GIS to simulate water quality, it is very useful to combine the GIS technique with a neuro-fuzzy model that is very applicable and also has the potential for creating a successful modeling tool (Dixon 2004).…”
Section: Introductionmentioning
confidence: 99%