Recommending Surface Water Quality Monitoring for the Nature Reserve Using Multivariate Statistical Methods

Lung Ngoc Hoang Nature Reserve has a crucial role in conserving and protecting the natural ecosystem and biodiversity in the Mekong Delta, Vietnam, and the local communities also receive great benefits from aquatic resources in this nature reserve. This study was conducted to assess water quality in the Lung Ngoc Hoang Nature Reserve and to provide important information for the monitoring program using multivariate statistical methods. Water samples were collected bimonthly from fifteen locations belonging to five functional zones of the nature reserve (i.e., buffer zone, main canal, administrative and service zone, ecological restoration zone, and strictly protected zone). The physiochemical properties of water samples were measured, including temperature, pH, electrical conductivity (EC), total suspended solids (TSS), dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), sulfate (SO42-), iron (Fe2+), and aluminum (Al3+). The results showed that the levels of TSS, COD, and Fe2+ exceeded the Vietnamese standard on surface water quality, and the DO level was also far below the standard. Besides, the concentrations of TN, TP, and Al3+ in the nature reserve area showed the risk of eutrophication and negative effects on aquatic organisms. Problems of water quality were observed in the main canal and the administrative and service zones more than in the other zones. Cluster analysis (CA) suggested a reduction in the number of monitoring frequencies and locations to four months (i.e., January, April, July, and September) and twelve locations, respectively. This reduction allows for a decrease in the effort and cost of the monitoring program with adequate information to evaluate water quality. Moreover, principal component analysis (PCA) identified five principal components, which could explain 80.98% of the total variance of the initial dataset. Potential pollution sources were also recognized based on PCA, including the nature properties of sulfate-acid soils, livestock, fertilizer, and domestic activities. The findings of this study can enhance our understanding of water quality in the nature reserve area and the effectiveness of future monitoring programs.