Analysis of spatiotemporal variation in river water quality using clustering techniques: a case study in the Yeongsan River, Republic of Korea.

Abstract

Herein, cluster analysis was applied to evaluate the spatiotemporal variations in water quality variables of a river. The analysis was performed using the data obtained from 15 monitoring stations during 2007-2018 in the Yeongsan River, Republic of Korea. The spatiotemporal analysis successfully clustered the annual water quality variables temporally into years of poor water quality (2007-2012) and good water quality (2013-2018), and spatially into stations observing bad water quality (midstream) and good water quality (upstream and downstream). For the spatial cluster analysis results before and after a large river engineering project, the water quality was grouped into four clusters according to regional effects and water pollutant sources. The clustering analysis results clearly reflected changes in the water quality along the river due to the project. Overall, this study demonstrates that cluster analysis can be effectively used for evaluating spatiotemporal variations in river water quality.