Assessment of Groundwater Quality Using GIS - A Case Study of the Churu District of Rajasthan

A. N. Singh1, Anuradha D.1 and Satish Mohanty2


1 Department of Civil Engineering, BITS-Pilani, Rajasthan, India; E-mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it

2 Department of EEE, BITS-Pilani, Rajasthan, India



Assessment of Groundwater quality using the Water Quality Index (WQI) and the Geographic Information System (GIS) was carried out in the Churu district of Rajasthan. The results of 8 physico-chemical parameters were used for the calculation of the WQI. The results indicated that the WQI values range from 0 to 789 and thus indicates very poor groundwater quality status in the region in one case. The results of 8 physico-chemical parameters were used in the second case resulting in a WQI range from 0 to 3,279. The geographical information system using the Inverse Distance Weighted method (IDW) delineated three groundwater quality zones into good to very poor. The hierarchal cluster analysis identified anthropogenic contamination and natural mineralization as the major processes controlling groundwater chemistry. From the correlation matrix, it could be said that Turbidity, Fluorides as F- and TDS are responsible for high WQI values in the region. The trend of WQI is very similar in both cases used to determine WQI. In arid regions the WQI should be high.

Keywords: WQI, GIS, Dendrogram, Anthropogenic Contamination, Natural Mineralization.



The determination of groundwater quality for human consumption is important for the well being of the ever increasing population (Ishaku, 2011). The supply of good quality water is one of the important components of groundwater protection and conservation strategies and therefore useful in the planning and management of groundwater. Groundwater quality depends on the quality of recharged water, atmospheric precipitation, inland surface water and subsurface geochemical processes (Reza and Singh, 2010; Vasanthavigar et al., 2010). The authors further stressed that temporal changes in the origin and constitution of the recharged water, hydrologic and human factors may cause periodic change in groundwater quality. Water pollution not only affects water quality but also threatens human health, economic development, and social prosperity (Milovanović, 2007). Hence, evaluation of groundwater quality status for human consumption is important for socio-economic growth, development and also for establishing a database for planning future water resource development strategies.

Water Quality Index (WQI) is an important technique for demarcating groundwater quality and its suitability for drinking purposes (Tiwari and Mishra, 1985).

Assessment of groundwater quality through Water Quality Index (WQI) studies and spatial distribution of WQI utilizing GIS technology could be useful for policy makers to take remedial measures. GIS can be a powerful tool for developing solutions for water resources problems to assess water quality, determining water availability, understanding the natural environment on a local and/or regional scale (Swarna and Nageswara Rao, 2010). The geographical information system and WQI, which synthesizes different available water quality data into an easily understandable format, provide a way to summarize overall water quality conditions that can be clearly communicated to policy makers (Strivastava et al., 2011). Therefore, this study is focused on the results of physico-chemical analysis of various parameters for domestic use and development of WQI, and mapping of their spatial distribution using GIS techniques. The study is also aimed at determining the major processes controlling groundwater chemistry.

Nelson et al. (2004), says that WQI is defined as an evaluation of the physical, chemical and biological nature of water with respect to its natural quality, human effects and intended uses. It reduces a list of parameters to a simpler expression to enable easier interpretation of monitoring data. Insaf et al. (2007), worked on groundwater quality index using GIS, where he calculated the normalised sub indices and then ranked them. His study area is a few km2 and the parameters he used are only chemical parameters containing ions. The final index is represented in % not in values. He then selected the combination of parameters to show the variability of groundwater.