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Three Environments, One Problem: Forecasting Water Temperature in Central Europe in Response to Climate Change

cris.lastimport.scopus2025-10-23T06:57:17Z
cris.virtual.author-orcid0000-0002-1453-0374
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cris.virtualsource.author-orcid917b05fe-6da6-4828-82f0-08b7c58485fd
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dc.abstract.enWater temperature is a fundamental parameter influencing a range of biotic and abiotic processes occurring within various components of the hydrosphere. This study presents a multi-step, data-driven predictive modeling framework to estimate water temperatures for the period 2021–2100 in three aquatic environments in Central Europe: the Odra River, the Szczecin Lagoon, and the Baltic Sea. The framework integrates Bayesian Model Averaging (BMA), Random Sample Consensus (RANSAC) regression, Gradient Boosting Regressor (GBR), and Random Forest (RF) machine learning models. To assess the performance of the models, the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) were used. The results showed that the application of statistical downscaling methods improved the prediction of air temperatures with respect to the BMA. Moreover, the RF method was used to predict water temperature. The best model performance was obtained for the Baltic Sea and the lowest for the Odra River. Under the SSP2-4.5 and SSP5-8.5 scenario-based simulations, projected air temperature increases in the period 2021–2100 could range from 1.5 °C to 1.7 °C and 4.7 to 5.1 °C. In contrast, the increase in water temperatures by 2100 will be between 1.2 °C and 1.6 °C (SSP2-4.5 scenario) and between 3.5 °C and 4.9 °C (SSP5-8.5).
dc.affiliationWydział Inżynierii Środowiska i Inżynierii Mechanicznej
dc.affiliation.instituteKatedra Melioracji, Kształtowania Środowiska i Gospodarki Przestrzennej
dc.contributor.authorPtak, Mariusz
dc.contributor.authorSojka, Mariusz
dc.contributor.authorSzyga-Pluta, Katarzyna
dc.contributor.authorAmnuaylojaroen, Teerachai
dc.date.access2025-10-10
dc.date.accessioned2025-10-10T11:35:31Z
dc.date.available2025-10-10T11:35:31Z
dc.date.copyright2025-05-29
dc.date.issued2025
dc.description.abstract<jats:p>Water temperature is a fundamental parameter influencing a range of biotic and abiotic processes occurring within various components of the hydrosphere. This study presents a multi-step, data-driven predictive modeling framework to estimate water temperatures for the period 2021–2100 in three aquatic environments in Central Europe: the Odra River, the Szczecin Lagoon, and the Baltic Sea. The framework integrates Bayesian Model Averaging (BMA), Random Sample Consensus (RANSAC) regression, Gradient Boosting Regressor (GBR), and Random Forest (RF) machine learning models. To assess the performance of the models, the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) were used. The results showed that the application of statistical downscaling methods improved the prediction of air temperatures with respect to the BMA. Moreover, the RF method was used to predict water temperature. The best model performance was obtained for the Baltic Sea and the lowest for the Odra River. Under the SSP2-4.5 and SSP5-8.5 scenario-based simulations, projected air temperature increases in the period 2021–2100 could range from 1.5 °C to 1.7 °C and 4.7 to 5.1 °C. In contrast, the increase in water temperatures by 2100 will be between 1.2 °C and 1.6 °C (SSP2-4.5 scenario) and between 3.5 °C and 4.9 °C (SSP5-8.5).</jats:p>
dc.description.accesstimeat_publication
dc.description.bibliographyil., bibliogr.
dc.description.financepublication_nocost
dc.description.financecost0,00
dc.description.if3,2
dc.description.number2
dc.description.points20
dc.description.versionfinal_published
dc.description.volume7
dc.identifier.doi10.3390/forecast7020024
dc.identifier.issn2571-9394
dc.identifier.urihttps://sciencerep.up.poznan.pl/handle/item/5386
dc.identifier.weblinkhttps://www.mdpi.com/2571-9394/7/2/24
dc.languageen
dc.relation.ispartofForecasting
dc.relation.pagesart. 24
dc.rightsCC-BY
dc.sciencecloudnosend
dc.share.typeOPEN_JOURNAL
dc.subject.enrivers
dc.subject.ensea
dc.subject.enclimate change
dc.subject.enprediction
dc.titleThree Environments, One Problem: Forecasting Water Temperature in Central Europe in Response to Climate Change
dc.typeJournalArticle
dspace.entity.typePublication
oaire.citation.issue2
oaire.citation.volume7