Geospatial Approach for Mapping of Ground Water Quality of Outer Plains of Samba District, J and K, India
Journal: International Journal of Science and Research (IJSR) (Vol.5, No. 12)Publication Date: 2016-12-05
Authors : Priya Kanwar; Pragya Khanna;
Page : 1472-1477
Keywords : Ground water; Ground water quality parameters; BIS; Basanter; Samba;
Abstract
Ground water is ultimate, most suitable fresh water resource with nearly balanced concentration of the salts suitable for human consumption. Therefore, it is very important to monitor the quality of ground water especially if an area has all possible sources of pollution viz. Agriculture, Industry and Human population. The Outer Plains of Samba District was the area selected to assess the ground water quality. Mainly the area is agriculture based and along its perennial river Basanter an Industrial Estate is established since long time. The aim of the study is to present the distribution of various chemical constituents in the ground water of the study area in GIS environment for better understanding of the spatial distribution of each chemical parameter and mapping of the current situation of ground water quality. The most important chemical parameters of ground water like Electrical Conductivity (EC), Sulphate (SO4), Nitrate (NO3), Sodium (Na), Potassium (K), Calcium (Ca), Chloride (Cl), Magnesium (Mg), pH, Fluoride (F), Total Hardness (TH) and Iron (Fe) were selected and compared to the guideline values presented by Bureau of Indian Standards (BIS). The spatial distribution maps for each ground water parameter are prepared by interpolation of values by using natural neighbour method.
Other Latest Articles
- Surface Modification of Polycarbonate by Treatment with 50Hz Dielectric Barrier Discharge at Near Atmospheric Pressure
- Electrodeposition of Metal Alloys (Ni, Zn and Fe) and their Characterization: A Review
- Gender Differential in the Prevalence of Rheumatoid Arthritis
- Review on Privacy Preserving Deep Computation Model on Cloud for Big Data Feature Learning
- Review on Medical Secure Systems Using Machine Learning Algorithm
Last modified: 2021-07-01 14:48:53