Determinants of geographical inequalities in domestic water supply across city of Pune, India

Abstract

Abstract The water supply system in the city of Pune is affected due to the fast and chaotic development in and around the city. The quantity of per capita water supply and hours of supply per day varies substantially across the city. Some central parts of the city benefit from a large availability of water as compared to peripheral areas. This research employed Ordinary Least Squares (OLS) Regression, Geographically Weighted Regression (GWR), and the new version of GWR termed Multi-scale Geographically Weighted Regression (MGWR) models to better understand the factors behind observed spatial patterns of water supply distribution and to predict water supply in newly merged and proposed villages in the Pune city's periphery. Results showed statistical significance of slope; distance from service reservoirs; and water supply hour. MGWR and GWR models improved our results (adjusted R2: 0.916 and 0.710 respectively) significantly over those of the OLS model (adjusted R2: 0.252) and proved how local conditions influence variables. The maps of GWR display how a particular variable is highly important in some areas but less important in other parts of the city. The results from the current study can help decision-makers to make appropriate decisions for future planning to achieve Sustainable Development Goal number 6 (SDG #6), which focuses on achieving universal and equitable access to safe and affordable drinking water for all.