GIS Aided Groundwater Quality Mapping of Central Brahmaputra Valley Zone of Assam, India

Thakuria, I. H. and Hazarika, P. P. and Deka, K. and Medhi, B. K. and Rahman, N. and Baruah, N. and Baruah, S. (2019) GIS Aided Groundwater Quality Mapping of Central Brahmaputra Valley Zone of Assam, India. Current Journal of Applied Science and Technology, 34 (6). pp. 1-14. ISSN 2457-1024

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Abstract

Groundwater is an essential resource for sustainable development all over the world. To understand the use of water resources, the fundamental characteristics and recharge of the groundwater need to be analyzed. GIS is considered as an effective and powerful tool for collecting, storing, transforming the spatial information for the need-based site-specific decision-making process. Thus, GIS tools have opened new paths in land and water resource studies. In the present study, GIS-based mapping of the groundwater in the central Brahmaputra Valley Zone is done with a view to observing the various quality characters. The results of this investigation could be used by decision-makers for the sustainable management of groundwater resources. The groundwater pH of the district was found to be within the desirable limit as recommended by WHO but 67.30% sample covering 79% of the total geographical area of the district was slightly alkaline in nature. Groundwater quality parameters that surpassed the desirable limit recommended by WHO, were electrical conductivity and nitrate which accounted for 41.22% and 0.79% of the total samples. Total Dissolved Solids, calcium, magnesium, carbonate, bicarbonate and nitrate in groundwater were recorded within the desirable limit of WHO and thus could be considered as safe. Spatial autocorrelation run for all the quality parameters with respect to their positions and values over the entire district envisaged the possibilities of forming different pattern namely CLUSTER for pH, EC, As, F, Fe, Al, Mn,HCO3, RANDOM for Mg, Ca, CO3, NO3, SO4 and DISPERSED for TDS. GIS-aided mapping of groundwater quality parameters embracing their category wise spatial distribution, area, maximum and minimum values, surface autocorrelation of observed values could give a better idea to opt for suitable need-based management strategy for the entire district.

Item Type: Article
Subjects: STM Digital Library > Multidisciplinary
Depositing User: Unnamed user with email support@stmdigitallib.com
Date Deposited: 15 Apr 2023 07:56
Last Modified: 13 Sep 2024 07:13
URI: http://archive.scholarstm.com/id/eprint/823

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