Assessment of Groundwater Quality Using GIS - A Case Study of the Churu District of Rajasthan - Page 03

Case Study

Description of the Study Area

The study area is the Churu district of the Rajasthan state of India. It is located between latitudes 27°28'12"N to 29°0' 02"N and longitudes 73°37'41"E to 75°40'01"E (Figure 1), and covers an area of about 16,830 km2.

 

Fig01
Figure 1: Map of the study area showing sampling points.

 

The area is characterized by dry and hot seasons with arid to semi arid climatic conditions. The rainy season commences in June and ends in mid September. The average rainfall is about 100 mm, and the mean annual evapo-transpiration of about 1200 mm, and the mean minimum and maximum temperatures of 1°C and 51.7°C. The major occupation of the people is agriculture, salt production and stone quarrying and the area is characterized by rural and urban settings. Sources of water supply are from electricity run deep bore wells and shallow boreholes. Some villages and towns are getting the water supply from Indira Gandhi Canal, but it is very irregular. There have been some cases where livestock had rejected this water for drinking. These sources of water supply are unreliable as the quality of the water is poor coupled with poor sanitary conditions. The type of waste disposal practice in the area is the open dump waste disposal system for household solid waste, and most residents use pit latrines. As the area is free from surface water and has very low rainfall, the possibility of waste leaching during rain is very rare. The main objectives of the present study involve analysis of water samples for physico-chemical parameters and development of a Water Quality Index, and mapping of their spatial distribution using GIS techniques. The study is also aimed at determining the processes responsible for controlling groundwater chemistry. The area is underlain by the Quaternary (late Pleistocene) age deposits and consists of Aeolian sediments (Figure 2). The Thar Desert covers the Quaternary (aeolian sediment) deposits.

 

Fig02
Figure 2: Geological map of the study area

 

Materials and Methods

88 water samples were collected from the different locations and the same type of well. The positions of the different water locations were determined using GIS and recorded by GPS. After collection of the samples, field parameters such as Temperature, Colour, Turbidity, pH, Nitrate as NO3-, Nitrite as NO2-, Fluoride as F-, and TDS were determined in the laboratory using (standard methods 19th edition, 1995) the titration method. The samples for chemical analysis were delivered within 48 hours of collection to laboratory. The sampling was done in the pre and post monsoon season of 2012. The summary of values of various parameters is given in Table 1.

The cluster analysis result is presented by dendrogram (Figure 8), in which these 8 parameters are grouped and their proximity of association is shown.

The 2 methods were used to calculate WQI in the study area in which both are derived from empirical formulas used by many authors.

GIS Geo-data base

A map showing sampling points (Figure 1) was generated using the grid point generation toll in Arc GIS version 9.2 using the study area boundary map which was scanned, geo referenced and digitized. After the grid was generated in Arc GIS, the sampling points were transferred to GPS and taken to the study area for sample collection. The water samples were collected and analyzed for different physico-chemical parameters and then used for calculation of WQI.

The different locations of the sampling points were introduced in GIS software through point layer. Each sample point was assigned a unique code and stored in the attribute table. The geo-database was used to generate the spatial distribution maps of WQI. The present study used the Inverse Distance Weighting (IDW) method for spatial interpolation of WQI as IDW is an interpolation technique in which interpolated estimates are made based on values at nearby locations weighted only by distance from the interpolation location (Naoum and Tsanis, 2004)

 

Tab01