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Analyzing spatio-temporal dynamics of dissolved oxygen for the River Thames using superstatistical methods and machine learning

He, Hankun ; Boehringer, Takuya; Schäfer, Benjamin ORCID iD icon 1; Heppell, Kate; Beck, Christian
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)

Abstract:

By employing superstatistical methods and machine learning, we analyze time series data of water quality indicators for the River Thames (UK). The indicators analyzed include dissolved oxygen, temperature, electrical conductivity, pH, ammonium, turbidity, and rainfall, with a specific focus on the dynamics of dissolved oxygen. After detrending, the probability density functions of dissolved oxygen fluctuations exhibit heavy tails that are effectively modeled using q‑Gaussian distributions. Our findings indicate that the multiplicative Empirical Mode Decomposition method stands out as the most effective detrending technique, yielding the highest log‑likelihood in nearly all fittings. We also observe that the optimally fitted width parameter of the q‑Gaussian shows a negative correlation with the distance to the sea, highlighting the influence of geographical factors on water quality dynamics. In the context of same‑time prediction of dissolved oxygen, regression analysis incorporating various water quality indicators and temporal features identify the Light Gradient Boosting Machine as the best model. SHapley Additive exPlanations reveal that temperature, pH, and time of year play crucial roles in the predictions. ... mehr

Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 2045-2322
KITopen-ID: 1000174431
HGF-Programm 37.12.02 (POF IV, LK 01) Design,Operation & Digitalization of the Future Energy Grids
Weitere HGF-Programme 46.21.04 (POF IV, LK 01) HAICU
Erschienen in Scientific Reports
Verlag Nature Research
Band 14
Heft 1
Seiten Art.-Nr.: 21288
Vorab online veröffentlicht am 12.09.2024
Nachgewiesen in Dimensions
Web of Science
OpenAlex
Scopus
Globale Ziele für nachhaltige Entwicklung Ziel 3 – Gesundheit und WohlergehenZiel 6 – Sauberes Wasser und Sanitär-Einrichtungen

Verlagsausgabe §
DOI: 10.5445/IR/1000174431
Veröffentlicht am 23.09.2024
Originalveröffentlichung
DOI: 10.1038/s41598-024-72084-w
Scopus
Zitationen: 1
Web of Science
Zitationen: 1
Dimensions
Zitationen: 2
Seitenaufrufe: 72
seit 23.09.2024
Downloads: 18
seit 26.09.2024
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