Three Environments, One Problem: Forecasting Water Temperature in Central Europe in Response to Climate Change
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 aquati...
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MDPI AG
2025-05-01
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| Series: | Forecasting |
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| author | Mariusz Ptak Mariusz Sojka Katarzyna Szyga-Pluta Teerachai Amnuaylojaroen |
| author_facet | Mariusz Ptak Mariusz Sojka Katarzyna Szyga-Pluta Teerachai Amnuaylojaroen |
| author_sort | Mariusz Ptak |
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| description | 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 (<i>MAE</i>), and root mean square error (<i>RMSE</i>) 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). |
| format | Article |
| id | doaj-art-e470eabd69a64811b0b6c2a911c10e8d |
| institution | Kabale University |
| issn | 2571-9394 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Forecasting |
| spelling | doaj-art-e470eabd69a64811b0b6c2a911c10e8d2025-08-20T03:27:18ZengMDPI AGForecasting2571-93942025-05-01722410.3390/forecast7020024Three Environments, One Problem: Forecasting Water Temperature in Central Europe in Response to Climate ChangeMariusz Ptak0Mariusz Sojka1Katarzyna Szyga-Pluta2Teerachai Amnuaylojaroen3Department of Hydrology and Water Management, Adam Mickiewicz University, Krygowskiego 10, 61-680 Poznań, PolandDepartment of Land Improvement, Environmental Development and Spatial Management, Poznań University of Life Sciences, Piątkowska 94E, 60-649 Poznań, PolandDepartment of Meteorology and Climatology, Adam Mickiewicz University, Krygowskiego 10, 61-680 Poznań, PolandSchool of Energy and Environment, University of Phayao, Phayao 56000, ThailandWater 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 (<i>MAE</i>), and root mean square error (<i>RMSE</i>) 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).https://www.mdpi.com/2571-9394/7/2/24riversseaclimate changeprediction |
| spellingShingle | Mariusz Ptak Mariusz Sojka Katarzyna Szyga-Pluta Teerachai Amnuaylojaroen Three Environments, One Problem: Forecasting Water Temperature in Central Europe in Response to Climate Change Forecasting rivers sea climate change prediction |
| title | Three Environments, One Problem: Forecasting Water Temperature in Central Europe in Response to Climate Change |
| title_full | Three Environments, One Problem: Forecasting Water Temperature in Central Europe in Response to Climate Change |
| title_fullStr | Three Environments, One Problem: Forecasting Water Temperature in Central Europe in Response to Climate Change |
| title_full_unstemmed | Three Environments, One Problem: Forecasting Water Temperature in Central Europe in Response to Climate Change |
| title_short | Three Environments, One Problem: Forecasting Water Temperature in Central Europe in Response to Climate Change |
| title_sort | three environments one problem forecasting water temperature in central europe in response to climate change |
| topic | rivers sea climate change prediction |
| url | https://www.mdpi.com/2571-9394/7/2/24 |
| work_keys_str_mv | AT mariuszptak threeenvironmentsoneproblemforecastingwatertemperatureincentraleuropeinresponsetoclimatechange AT mariuszsojka threeenvironmentsoneproblemforecastingwatertemperatureincentraleuropeinresponsetoclimatechange AT katarzynaszygapluta threeenvironmentsoneproblemforecastingwatertemperatureincentraleuropeinresponsetoclimatechange AT teerachaiamnuaylojaroen threeenvironmentsoneproblemforecastingwatertemperatureincentraleuropeinresponsetoclimatechange |