Spatially-referred and up-to-date information system is one of the useful tools for effective watershed management and environmental protection. Since water quality-related documents and information on treatment systems are specifically designed for specific area and specific localities and local conditions, they show strong spatial relationships. Therefore, it is necessary to have a system which provides facilities through geo-spatial relationships.

The Upper Mahaweli catchment is one of the most important watersheds in Sri Lanka in terms of providing water for domestic, agricultural and industrial purposes and for electricity generation. Thus, protection of this important water source is crucial in national development. But, only very few point source treatment plants are currently in operation and non-point source treatment plants are required to be established to protect the catchment from pollution.

Locating wastewater treatment systems is one of the essential components, and that needs spatially-oriented data gathering, analyzing and visualizing. Further, GIS-based decision support systems for available treatment plants are well suited for informing improved analysis and understanding of the existing situation of treatment processes to managers and policy makers.

This study was undertaken to identify the critical socio-economical and environmental factors, and to find a more comprehensive and convenient way to optimize the locations for wastewater treatment facilities that are suitable for different local conditions in the Upper Mahaweli Catchment of Sri Lanka.

Domestic, agricultural, industrial and activities which affect water quality in the catchment were identified through a transect walk and a spatially-referred 1:50,000 map by obtaining coordinates by using GPS (Global Positioning System). In addition, land use patterns and Digital Terrain Model (DTM) were used to locate the treatment facilities for point source pollutants. For locating treatment facilities for non-point source pollution by agriculture and other sources, the catchment was divided into sub-catchments and micro-catchments and the end points of those micro-catchments were identified. For non-point source pollutants, relationship between land use and the water quality of the end points was established in micro catchments. Thematic maps of stream characteristics, land use and vegetation cover and socio-economic characteristics with DTM were prepared to be used in determining the most suitable locations for putting up the treatment plants for non-point source pollutants.