Apply Multivariate Statistical Analyses to Assess Surface Water Quality in the Quang Binh River System
Main Article Content
Abstract
This paper applies multivariate statistical analyses to identify the key factors influencing surface water quality during the socio-economic development period 2016-2020 in Quang Binh Province. A comprehensive water quality dataset, comprising ten parameters across 15 locations of the Quang Binh River system, was collected four times per year. Socioeconomic data, including population density, aquaculture land area, agricultural production land area, forestry land area, the number of farms, the number of enterprises engaged in production, and business activities, were collected from administrative units within the monitoring area. The factor analysis using the principal component method identified two main components that explain around 57.82% of the total variance. Based on the loading values of the variables, these components were interpreted as representing anthropogenic and natural-environmental influences. The cluster analysis of socio-economic development conditions identified three distinct regions: urban areas, coastal rural areas, and mountainous rural areas. The results of the study of variance using one-way ANOVA demonstrated the impact of socio-economic indicators on the differentiation of environmental characteristics of water quality in rivers (coliform, BOD5, COD, and N-NH4+), with statistically significant differences (p < 0.05). This study highlights the practical application of multivariate statistical techniques in informing decision-makers involved in environmental quality monitoring in Quang Binh province, thereby providing actionable insights for effective environmental management and policy development.
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