Appraisal of urban lake water quality through numerical index, multivariate statistics and earth observation data sets

The earth observation data sets were employed to study the land use/land cover change in study area from year 2000-2010. Vegetation, built-up area and agriculture classes had shown maximum changes. The lake water samples were analyzed, and further, Water Quality Index (WQI) was computed to categorize the lake water. The average value of WQI is 64.52, 52.23 and 42.45 in pre-monsoon, monsoon and post-monsoon seasons, respectively. Generally, pre-monsoon samples have higher number of polluted samples. Moreover, we applied the multivariate statistical techniques for handling large and complex data sets in order to get better information about the lake water quality. Factor analysis and principal component analysis are applied to understand the latent structure of the data sets, and we have identified a total of four factors in pre-monsoon, three factors in monsoon and three factors in post-monsoon season, which are responsible for the whole data structure. These factors have explained that 90.908, 89.078 and 85.456 % of the cumulative percentage variance of the pre-monsoon, monsoon and post-monsoon data sets. Overall analysis reveals that the agricultural runoff, waste disposal, leaching and irrigation with wastewater, land transformation in the surrounding areas are the main causes of lake water pollution followed by some degree of pollution from geogenic sources such as rock weathering. Hence, there is an urgent need of proper attention and management of resources.