Assessing the impacts of industrial wastewater on the inland surface water quality: An application of analytic hierarchy process (AHP) model-based water quality index and GIS techniques

Abstract

The main objective of the present work is to provide a clear insight into receiving inland surface water quality in Kashipur city of Uttarakhand state, India, due to the impact of industrial discharges using a novel Water Quality Index method based on the Analytic Hierarchy Process (AHP) approach. Surface water samples were collected monthly from 12 locations between September 2020 and March 2021. The locations were chosen based on their potential to acquire the most contaminants from surrounding industries and analyzed for their physicochemical characteristics. Geostatistical analysis results represented the spatial variation of the parameter concentrations in the study area. Statistical analyses were performed using Principal Component Analysis and Hierarchical Cluster Analysis. PCA results revealed that two factor loadings impact the surface water chemistry in the study region, where factor 1 represents 50.051% of the variance with six dominant water parameters, and factor 2 represents 33.222% of the total variance. HCA classified the sampling locations randomly into two major clusters. Analytic Hierarchy Process results in establishing the weights of the parameters revealed that dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, and total dissolved solids were the dominant parameters for assessing water quality with a consistency ratio of 0.097. The WQI results showed that 8% of the water samples depict “very poor” inland surface water quality. The anthropogenic sources might be the reason for such poor water quality. This model can be effectively applied at any location and with as many parameters as required to assess surface water quality.