Chapter 7 - Establishing spatial relationships between land use and water quality influenced by urbanization

Abstract

Abstract Unplanned urbanization, coupled with rapid population growth, puts tremendous pressure on the infrastructure of Indian cities. The population of Raipur city, capital of Chhattisgarh state in India, has doubled since the turn of the millennium. Today, the city faces major challenges concerning its water supply and quality, sewage system, waste treatment, and waste disposal. Various ponds and lakes that are used for irrigation, washing, and bathing are affected by deteriorating water quality. To contribute to solutions of how water quality can be restored and protected, this work focuses on relationships between land use and water quality. To identify and quantify such relationships, surface water quality data of 38 ponds and land use data of Raipur city were connected through an analysis of GIS-based spatial correlation. Twenty-two different water quality parameters and six different land use types were analyzed. Industrial land use produced the strongest correlation coefficients. Applying circular buffer zones with a diameter of 1 km (buffer type A), industrial land use showed very strong negative correlations with total alkalinity ( r = − 0.86), dissolved oxygen ( r = − 0.89), hydrogen carbonate ( r = − 0.98), sodium ( r = − 0.93), and a very strong positive correlation with turbidity ( r = 0.94). Buffer zones with a length of 2.5 km and a width of 1 km, directed upstream toward drainage pathways (buffer type B), produced somewhat weaker correlations. Because only few data pairs were used in the calculation of correlation with industrial land use, the confidence levels are mainly below 0.80. The correlation results are mostly relevant to Raipur city, and this knowledge may be further utilized by local authorities and stakeholders of this city. However, in general the relationships between water quality and land use should be tried with a greater number of samples for closer correlation leading to fair conclusions.