Assessment of Domestic Water Resources for Sustainable Utilization Using Geospatial Techniques. The Case of Pune City, India

Water resources have played a crucial role in the growth and development of human civilisation. Increasing demands of water resources to meet the needs of growing population have led to tremendous pressure on water resources. Water resources conservation and management need relevant information regarding the quality and quantity of water bodies, as well as the related driving factors responsible for the deterioration and depletion of water resources. In literature, conventional methods are limited to point locations that have sparse datasets. However, with the advent of geospatial techniques, it has become very easy to explore digital information that can quickly support extensive data analysis and interpretation on a larger scale. The aim of this study is to assess water resources such as water supply, distribution and coverage using geospatial techniques, and also to identify the water stress zones whilst forecasting the water demand in the future, which is indispensable for sustainable urban planning. The results show that water supply and duration per capita are unequal in the study area. The water demand of Pune city has continuously increased from 508 MLD in 2001 to 857 MLD in 2022, and will maintain this trend up to 1421 MLD by 2031. The composite water stress map indicates that Ghole Road, Nagar Road, Dhankawadi and Hadapsar wards have a high level of water stress, whereas Sangamwadi, Kothrud, Dhole Patil Road, Bhawani Peth, Kasba Vishrambagh and Sahakranagar experience low water stress. The values of water scarcity index in the study area have significantly changed, i.e., from 0.68 in 2001, to 0.54 in 2011 and to 0.64 in 2022, which indicates that Pune city falls into the serious water shortage category. This index is expected to be around 1.05 in 2031, demonstrating that Pune will be subjected to major water deficiency, a condition which is clearly reflected in the composite water stress map.