Dissolved Ion Distribution in a Watershed: A Study Utilizing Ion Chromatography and Non-Parametric Analysis

This study presents a unique approach for characterizing ion distribution within the Kushiro River catchment basin, which is characterized by exceptionally high dissolved ion concentrations. principal component analysis, Mann–Whitney U test, and neural network modeling were employed to analyze data from 11 distinct locations in two different seasons. The 11 sampling locations were subsequently classified into five distinct groups to facilitate precise analysis of the ion distribution using neural networks. Two principal components were also employed to visualize and interpret our dataset. Compositional similarities and seasonal variations in ion distribution were identified, as well as the key variability patterns, thereby revealing underlying correlations among the dissolved ions. Our findings highlighted that Group 1, encompassing a caldera lake, exhibits the highest dissolved ion concentrations. This observation may be attributed to the geological characteristics of the underlying rock formation. Furthermore, a significant correlation was observed between the major dissolved ions present in the catchment basin, as evidenced by positive correlation coefficients. Conversely, nitrate ions exhibited a negative correlation with F−, Cl−, and Na+ ions. This comprehensive analytical framework offers a robust and insightful tool for determining ion distribution within catchment basins with significant implications for environmental monitoring and sustainable resource management.