Abstract
This study analyzes changes in the water temperature in the Pilica River (Poland), encompassing both historical data (1958–2023) and projections extending to the year 2100. We use multi-model ensembles (MMEs) with Bayesian Model Averaging (BMA) to integrate various Global Climate Model (GCM) datasets for current and projected climate data. Additionally, a Random Forest (RF) machine learning method is applied to project future water temperatures in the Pilica River. It has been demonstrated that over a period of more than sixty years, the average annual water temperature has increased by nearly 2 °C. Further changes are expected to continue in a similar direction with a gradual rise in this parameter, reaching a temperature increase of 3 °C by the end of the 21st century (SSP585). In the distant future, with average monthly water temperature changes at the Przedbórz station ranging from 0.27 °C to 0.87 °C·decade−1 and at the Białobrzegi station from 0.22 °C to 1.06 °C·decade−1. The results of these changes are concerning, especially considering the crucial role of water temperature in shaping seasonality and the dynamics of processes occurring within the river. In the context of the sustainability of the river itself, but also of the entire catchment area, strategies developed by relevant public administration bodies are needed to mitigate the impacts of global warming observed in the thermal regime of the Pilica River.
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