Spatio-temporal analysis of the Brantas river water quality status by using principal component weighted index (PCWI)

Abstract

River, as one of the surface water resources, has faced many contaminations due to domestic and industrial activities in its surrounding, and thus routine water quality monitoring is required. This activity yields a large number of water quality characteristics that can be very useful to evaluate the status of river quality status. In this study, we integrated a statistical multivariate analysis such as Principal Component Analysis (PCA) and conventional Water Quality Index (WQI) measure to produce a data-driven composite index for water quality assessment. We implemented this technique to evaluate the status of Brantas River, the largest river in East Java Province-Indonesia, using a long-term dataset collected from 2012 to 2021. The study area was divided into three classes: upstream, midstream, and downstream. Results of the study suggested that the pollution level in the Brantas River fluctuates yearly. Meanwhile, the degree of contamination increased from upstream to downstream.