Vol. 8, Issue 1 (2020)
Indexing of ground water vulnerability in Guntur district, Andhra Pradesh using GIS based agricultural drastic model
Author(s): Priya PGL, Krupavathi K and Rohit Minz
Abstract: Agricultural activities especially application of fertilizers, pesticides and fumigants have been identified as one of the non-point sources of pollutants which leach various pollutants from agricultural land through the unsaturated zone and groundwater zone gives rise to contamination to groundwater and soil, which poses serious detrimental risk in rural areas. To assess the groundwater vulnerability and analyze the risk, research was carried out in Agricultural areas of Guntur District, Andhra Pradesh. The GIS-based Agricultural vulnerability indexing method (DRASTIC) is selected in this study, which identifies vulnerability zones and is helpful in formulation of strategies to mitigate adverse impact of factors responsible for ground water pollution. Seven DRASTIC layers using parameters such as groundwater influencing parameters were created. Rates and weights were assigned to each parameter layer. By overlapping the layers in ArcGIS, the aquifer vulnerability map was prepared. By multiplying each parameter rate by its weight and adding for all layers Agricultural DRASTIC index number is determined. The results indicated that the Agricultural vulnerability Index in the study area ranged from 72-196 is determined. The developed maps are validated with nitrate concentrations. Different parameters like EC, pH, Ca, Mg, K Na, and NO3 was estimated and correlated to estimate the degree of association. It was observed from the developed Agricultural vulnerability maps for Guntur District that 10.56% of the study area falls under low vulnerable zone, 39.98% under moderate zone and 49.46% under high vulnerable zone due to agricultural leachates in cropped areas.
DOI: 10.22271/chemi.2020.v8.i1k.8354
Pages: 751-757 | 522 Views 100 Downloads
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How to cite this article:
Priya PGL, Krupavathi K, Rohit Minz. Indexing of ground water vulnerability in Guntur district, Andhra Pradesh using GIS based agricultural drastic model. Int J Chem Stud 2020;8(1):751-757. DOI: 10.22271/chemi.2020.v8.i1k.8354
