Correlation Between Hydrochemical Component of Surface Water and Groundwater in Nida Valley, Poland
Więcej
Ukryj
1
Faculty of Environmental Engineering and Land Surveying, University of Agriculture in Krakow, al. Mickiewicza 24/28, 30-059, Kraków, Poland
2
Institute of Chemistry, Biology and Environment, Vinh University, 182 Le Duan St, Vinh City, Nghe An Province, Vietnam
Autor do korespondencji
Cong Ngoc Phan
University of Agriculture in Krakow, al. Mickiewicza 24/28, 31-120 Kraków, Poland
J. Ecol. Eng. 2023; 24(12):167-177
SŁOWA KLUCZOWE
DZIEDZINY
STRESZCZENIE
The Nida valley study area underwent examination to investigate the hydrochemical components and the correlation between groundwater (GW) and surface water (SW). Over a 12-month period from November 2021 to October 2022, 9 monitoring points were established, consisting of 7 GW points and 2 SW points, with a monitoring frequency of once per month. The research findings indicate that the hydrochemical components and direction of GW flow in the study area can be classified into 3 distinct regions. The chemical composition is complex in areas near the Nida River, stable in the region near the Smuga Umianowicka branch, and different in other areas. It was observed that the SW in the Nida River and Smuga Umianowicka branch exhibits a relatively uncomplicated chemical composition due to minimal human impact in the natural area. However, dissimilarities between them were also identified and explained by the flow regulation of the dam built on the branch within the study area.
The application of the Shapiro-Wilk test (α = 0.05) and Kruskal-Wallis test (α = 0.05) revealed statistically significant differences among the recorded hydrochemical component values throughout the measurement period. Furthermore, Pearson’s correlation coefficient analysis (α = 0.001) indicated correlations between the hydrochemical components of SW and GW in the riparian area and strong correlations among GW samples. Principal Component Analysis (PCA) identified significant dissimilarity and similarity between GW and SW samples based on their characteristics.