Determination of Groundwater Quality Index of a Highland Village of Kerala (India) Using Geographical Information System
Rejith, P. G., Jeeva, S. P., Vijith, H., Sowmya, M., Hatha, A. A. Mohamed, Journal of Environmental Health
Fresh water is a precious and finite resource central to sustainable development, economic growth, social stability, and poverty alleviation. Fresh water quality, quantity, and security have grown to become the major international issues in recent years. Global environmental changes induced by natural variability and human activities influence both water quantity and quality at regional and local scales as well as at the global scale (Chang, 2004). Urban growth, increased industrial activities, intensive farming, and overuse of fertilizers in agricultural production have been identified as drivers responsible for these changes (Patwardhan, 2003). It is a well-known fact that a polluted environment has a detrimental effect on the health of people, animal life, and vegetation (Sujatha & Reddy, 2003). Hence, the maintenance of water quality at acceptable levels is an essential requirement for successful use of these water resources.
Shallow groundwater is the main source of drinking water in rural areas, but reliable data on its quality are currently insufficient (Melian, Myrlian, Gouriev, Moraru, & Radstake, 1999), especially from developing countries. In India, more than 90% of rural and nearly 30% of urban populations depend on groundwater for their drinking and domestic requirements (Jaiswal, Mukherjee, Krishnamurthy, & Saxena 2003; Reddy, Vinod, & Seshadri, 1996). More than 50% of the population of Kerala uses dug-well water for drinking (Kerala Water Authority, 1991; Pillai & Ouseph, 2000; Roy, 2004). Further, the density of dug-wells in the highlands is 25 No.s/ Km2 with a total of approximately three million wells in Kerala. The present situation calls for developing systems of conservation, sustainable use, and equitable sharing of water in the country as a whole. In view of this fact, water quality monitoring becomes essential for identifying problems and formulating measures to minimize deterioration of water quality. Environmental issues are likely to aggravate in the future; an evaluation of the present situation is therefore highly necessary.
Geographical Information Systems (GIS) are designed to collect diverse data to represent spatially variable phenomena by applying a series of overlay analysis of data that are in spatial register (Bonham Carter, 1996). GIS has grown rapidly in groundwater management and research. The spatial patterns of chemical constituents are useful in deciding the water use strategies for various purposes (Bonham-Carter, 1996).
The present study is an attempt to generate baseline groundwater quality data of a highland village and to apply a GIS-based tool to determine the water quality index of the study area.
The highland village chosen for the present study is located in the high altitude headwaters region in Western Ghats, which comes under Idukki district of Kerala, India. The study area is located between 9[degrees]48'00" to 9[degrees]52'00" N and 77[degrees]06'00" to 77[degrees]15'00" E, covering an area of 71.95 [km.sup.2] (Figure 1). Geologically, the majority of the area is covered with acid charnockite. The measured rainfall in this area varies from 350 mm to 900 mm per day during the southwest monsoon (June-August) and northeast monsoon (October-December) seasons. The major river flowing through the area is the Kallar River, which joins into the Periyar River. The elevation varies between 400 m in the west to 1100 m above mean sea level in the east with a temperature range from 60.8[degrees]F in winter to 89.6[degrees]F in summer.
Spatial Database Construction and Selection of Sampling Wells
Survey of India (SOI) toposheet on 1:50,000 scale was used to prepare the base map and drainage map and to understand the general nature of the study area. The toposheet was scanned and digitized to generate a digital output using ArcInfo GIS software to obtain a baseline data. …