Dissolved Ion Distribution in a Watershed: A Study Utilizing Ion Chromatography and Non-Parametric Analysis Article Swipe
Selline Okechi
,
Keisuke NAKAYAMA
,
Katsuaki KOMAI
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/hydrology12120310
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/hydrology12120310
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.
Related Topics
Concepts
Principal component analysis
Ion
Ion chromatography
Drainage basin
Nitrate
Caldera
Environmental science
Environmental chemistry
Hydrology (agriculture)
Chemistry
Distribution (mathematics)
Inorganic ions
Soil science
Sampling (signal processing)
Dissolved organic carbon
Mineralogy
Watershed
Resource (disambiguation)
Nitrogen
Total dissolved solids
Biological system
Geology
Analytical Chemistry (journal)
Water quality
Fractionation
Positive correlation
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/hydrology12120310
- https://www.mdpi.com/2306-5338/12/12/310/pdf?version=1763803149
- OA Status
- gold
- References
- 22
- OpenAlex ID
- https://openalex.org/W7106491079
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W7106491079Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/hydrology12120310Digital Object Identifier
- Title
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Dissolved Ion Distribution in a Watershed: A Study Utilizing Ion Chromatography and Non-Parametric AnalysisWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
-
2025-11-22Full publication date if available
- Authors
-
Selline Okechi, Keisuke NAKAYAMA, Katsuaki KOMAIList of authors in order
- Landing page
-
https://doi.org/10.3390/hydrology12120310Publisher landing page
- PDF URL
-
https://www.mdpi.com/2306-5338/12/12/310/pdf?version=1763803149Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://www.mdpi.com/2306-5338/12/12/310/pdf?version=1763803149Direct OA link when available
- Concepts
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Principal component analysis, Ion, Ion chromatography, Drainage basin, Nitrate, Caldera, Environmental science, Environmental chemistry, Hydrology (agriculture), Chemistry, Distribution (mathematics), Inorganic ions, Soil science, Sampling (signal processing), Dissolved organic carbon, Mineralogy, Watershed, Resource (disambiguation), Nitrogen, Total dissolved solids, Biological system, Geology, Analytical Chemistry (journal), Water quality, Fractionation, Positive correlationTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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22Number of works referenced by this work
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| abstract_inverted_index.Cl−, | 168 |
| abstract_inverted_index.basin, | 15, 152 |
| abstract_inverted_index.basins | 188 |
| abstract_inverted_index.groups | 58 |
| abstract_inverted_index.neural | 32, 68 |
| abstract_inverted_index.offers | 176 |
| abstract_inverted_index.robust | 178 |
| abstract_inverted_index.unique | 4 |
| abstract_inverted_index.within | 10, 186 |
| abstract_inverted_index.Kushiro | 12 |
| abstract_inverted_index.analyze | 38 |
| abstract_inverted_index.between | 143 |
| abstract_inverted_index.caldera | 115 |
| abstract_inverted_index.highest | 119 |
| abstract_inverted_index.network | 33 |
| abstract_inverted_index.nitrate | 160 |
| abstract_inverted_index.precise | 61 |
| abstract_inverted_index.present | 148 |
| abstract_inverted_index.thereby | 99 |
| abstract_inverted_index.analysis | 62 |
| abstract_inverted_index.approach | 5 |
| abstract_inverted_index.dataset. | 81 |
| abstract_inverted_index.distinct | 42, 57 |
| abstract_inverted_index.employed | 36, 75 |
| abstract_inverted_index.exhibits | 117 |
| abstract_inverted_index.findings | 108 |
| abstract_inverted_index.modeling | 34 |
| abstract_inverted_index.negative | 164 |
| abstract_inverted_index.observed | 142 |
| abstract_inverted_index.positive | 156 |
| abstract_inverted_index.presents | 2 |
| abstract_inverted_index.resource | 197 |
| abstract_inverted_index.sampling | 50 |
| abstract_inverted_index.seasonal | 85 |
| abstract_inverted_index.seasons. | 47 |
| abstract_inverted_index.analysis, | 27 |
| abstract_inverted_index.catchment | 14, 151, 187 |
| abstract_inverted_index.component | 26 |
| abstract_inverted_index.different | 46 |
| abstract_inverted_index.dissolved | 22, 105, 120, 146 |
| abstract_inverted_index.evidenced | 154 |
| abstract_inverted_index.exhibited | 162 |
| abstract_inverted_index.framework | 175 |
| abstract_inverted_index.interpret | 79 |
| abstract_inverted_index.locations | 43, 51 |
| abstract_inverted_index.networks. | 69 |
| abstract_inverted_index.patterns, | 98 |
| abstract_inverted_index.principal | 25, 71 |
| abstract_inverted_index.revealing | 100 |
| abstract_inverted_index.visualize | 77 |
| abstract_inverted_index.analytical | 174 |
| abstract_inverted_index.attributed | 127 |
| abstract_inverted_index.classified | 54 |
| abstract_inverted_index.components | 72 |
| abstract_inverted_index.facilitate | 60 |
| abstract_inverted_index.formation. | 136 |
| abstract_inverted_index.geological | 130 |
| abstract_inverted_index.insightful | 180 |
| abstract_inverted_index.monitoring | 194 |
| abstract_inverted_index.underlying | 101, 134 |
| abstract_inverted_index.variations | 86 |
| abstract_inverted_index.Conversely, | 159 |
| abstract_inverted_index.correlation | 140, 157, 165 |
| abstract_inverted_index.determining | 183 |
| abstract_inverted_index.highlighted | 109 |
| abstract_inverted_index.identified, | 91 |
| abstract_inverted_index.management. | 198 |
| abstract_inverted_index.observation | 124 |
| abstract_inverted_index.significant | 139, 190 |
| abstract_inverted_index.sustainable | 196 |
| abstract_inverted_index.variability | 97 |
| abstract_inverted_index.Furthermore, | 137 |
| abstract_inverted_index.correlations | 102 |
| abstract_inverted_index.distribution | 9, 66, 89, 185 |
| abstract_inverted_index.encompassing | 113 |
| abstract_inverted_index.implications | 191 |
| abstract_inverted_index.similarities | 83 |
| abstract_inverted_index.subsequently | 53 |
| abstract_inverted_index.Compositional | 82 |
| abstract_inverted_index.characterized | 18 |
| abstract_inverted_index.coefficients. | 158 |
| abstract_inverted_index.comprehensive | 173 |
| abstract_inverted_index.environmental | 193 |
| abstract_inverted_index.exceptionally | 20 |
| abstract_inverted_index.Mann–Whitney | 28 |
| abstract_inverted_index.characterizing | 7 |
| abstract_inverted_index.characteristics | 131 |
| abstract_inverted_index.concentrations. | 24, 122 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile |