Determination of Changes in the Quality of Surface Water in the River-Reservoir System

Assessing the changing parameters of water quality at different points in the river-reservoir system can help prevent river pollution and implement remedial policies. It is also crucial in modeling water resources. Multivariate statistical analysis is useful for the analysis of changes in surface water quality. It helps to identify indicators that may be responsible for the eutrophication process of a reservoir. Additionally, the analysis of the water quality profile and the water quality index (WQI) is useful in assessing water pollution. These tools can support and verify the results of a multivariate statistical analysis. In this study, changes in water quality parameters of the Turawa reservoir (TR), and the Mala Panew river at the point below the Turawa reservoir (bTR) and above the Turawa reservoir (aTR), were analyzed. The analyzed period was from 2019 to 2020 (360 samples were analyzed). It was found that TN, NO2-N, and NO3-N decreased after passing through the Turawa reservoir. Nevertheless, principal component analysis (PCA) and redundancy analysis (RDA) showed that NO2-N and NO3-N contribute to the observed variability of the water quality in the river-reservoir system. PCA showed that pH and PO4-P had a lower impact on the water quality in the reservoir than nitrogen compounds. Additionally, RDA proved that the values of the NO3-N and NO2-N indicators obtained the highest values at the aTR point, PO4-P at the bTR, and pH at the TR. This allows the conclusion that the Turawa reservoir reduced the concentration of NO2-N and NO3-N in comparison with the concentration of these compounds flowing into the reservoir. PCA and RDA showed that both parameters (NO2-N and NO3-N) may be responsible for the eutrophication process of the Turawa reservoir. The analysis of short-term changes in water quality data may reveal additional sources of water pollution. High temperatures and alkaline reaction may cause the release of nitrogen and phosphorus compounds from sediments, which indicates an increased concentration of TP, PO4-P, and N-org in the waters at the TR point, and TP, PO4-P, and NH4-N concentrations at the bTR point. The water quality profile combined with PCA and RDA allows more effective monitoring for the needs of water management in the reservoir catchment area. The analyzed WQI for water below the reservoir (bTR) was lower than that of the reservoir water (TR), which indicates an improvement in water after passing through the reservoir.

Automated summary

Assessing water quality parameters in the river-reservoir system is essential for preventing pollution and implementing policies. Multivariate statistical analysis is useful in identifying key indicators, with NO2-N and NO3-N playing a significant role in water quality variability. The Turawa reservoir has been effective in reducing concentrations of these compounds, as indicated by PCA and RDA.