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12-14 September, 2011, Lucknow - Earth Science India

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National Conference on <strong>Science</strong> of Climate Change and <strong>Earth</strong>’s Sustainability: Issues and Challenges ‘A Scientist-People Partnership’<br />

<strong>12</strong>-<strong>14</strong> <strong>September</strong>, <strong>2011</strong>, <strong>Lucknow</strong><br />

STUDY OF SPATIAL VARIABILITY OF GROUND WATER<br />

DEPTH AND QUALITY PARAMETERS IN HARIDWAR<br />

DISTRICT OF UTTARAKHAND<br />

Pradipika Verma<br />

<strong>India</strong>n Institute of Remote Sensing, 4 Kalidas Road, Dehradun 248 001<br />

Ground water is a key source of drinking water that is essential to life on <strong>Earth</strong>.<br />

Assessing the quality of groundwater is important to ensure sustainable safe use of these<br />

resources. Geostatistical methods have been used widely as a convenient tool for<br />

assessing groundwater depth and ground water quality parameters. The objective of the<br />

study is to determine the groundwater quality and to assess the risk of groundwater<br />

pollution in Haridwar district of Uttarakhand, <strong>India</strong> by using geostatistic techniques.<br />

The groundwater quality parameters were analyzed from the existing wells of the<br />

Haridwar district and the thematic maps were generated using geostatistical concepts.<br />

Ordinary kriging was used to analyze the spatial variability of groundwater depth and<br />

quality parameters such as electrical conductivity (EC), bicarbonate, calcium, chloride,<br />

magnesium, sodium, potassium and sulphate with concentrations equal or greater than<br />

their respective groundwater pollution cutoff value, whereas indicator kriging was used<br />

to analyze groundwater quality parameters equal to or greater than the pollution<br />

threshold values. It was observed that the semi-variogram parameters fitted well in the<br />

gaussian for water depth and in the spherical model for water quality parameters. (EC<br />

followed a log-normal distribution and demonstrated a moderate spatial dependence<br />

according to the nugget ratio) (Cross-validation errors are within an acceptable level).<br />

The indicator kriging method is useful to assess the risk of groundwater pollution by<br />

giving the conditional probability of concentrations of different chemical parameters<br />

exceeding their cutoff values. Thus, risk assessment of groundwater pollution is useful<br />

for proper management of groundwater resources and minimizing the pollution threat.<br />

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