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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 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).
Role of Lake Morphometric and Environmental Drivers of Ice Cover Formation and Occurrence on Temperate Lakes: A Case Study from the Eastern Baltic Lakeland, Poland
The presence of ice cover on temperate lakes is a crucial factor in determining the functioning of these ecosystems. The isolation of water from atmospheric influences significantly alters physical, chemical, and biological processes, and the intensity of this impact depends on the duration of the ice cover. This study analyzed the basic parameters of ice cover on several dozen lakes in Northeastern Poland. The aim of this study is to investigate the influence of morphometric parameters, alongside environmental factors, on the variation of ice cover characteristics in lakes located within the Eastern Baltic Lakeland. Characterization of ice conditions in the analyzed lakes was based on basic statistics such as minimum and maximum values, mean, standard deviation, coefficients of variation, skewness, and kurtosis. Given that the dataset contains variables describing ice phenomena in the studied lakes and data describing location, morphometric parameters, and land cover directly adjacent to the lake (treated as independent variables), a method of Spearman’s rank correlations and constrained ordination method were decided upon. Despite the relatively small study area, significant variability was observed, with average differences as follows: 26 days for the onset of ice cover, 17 days for the end date, 15 cm for ice thickness, and a 30-day difference in the average duration of ice cover. Key factors included parameters such as lake volume, average depth, and land use (urbanized and agricultural areas). Understanding parameters such as the onset and end of ice cover is essential for lake ecosystems, both from an ecological and economic perspective. This knowledge is crucial for interpreting the behavior of living organisms, water quality, and economic considerations.
Historical and Future Changes in Water Temperature in the Pilica River (Central Europe) in Response to Global Warming
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.
Utilizing Multi-Source Datasets for the Reconstruction and Prediction of Water Temperature in Lake Miedwie (Poland)
Water temperature is a fundamental parameter of aquatic ecosystems. It directly influences most processes occurring within them. Hence, knowledge of this parameter’s behavior, based on long-term (reliable) observations, is crucial. Gaps in these observations can be filled using contemporary methodological solutions. Difficulties in reconstructing water temperature arise from the selection of an appropriate methodology, and overcoming them involves the proper selection of input data and choosing the optimal modeling approach. This study employed the air2water model and Landsat satellite imagery to reconstruct the water temperature of Lake Miedwie (the fifth largest in Poland), for which field observations conducted by the Institute of Meteorology and Water Management—National Research Institute ended in the late 1980s. The approach based on satellite images in this case yielded less accurate results than model analyses. However, it is important to emphasize the advantage of satellite images over point measurements in the spatial interpretation of lake thermal conditions. In the studied case, due to the lake’s shape, the surface water layer showed no significant thermal contrasts. Based on the model data, long-term changes in water temperature were determined, which historically (1972–2023) amounted to 0.20 °C per decade. According to the adopted climate change scenarios by the end of the 21st century (SSP245 and SSP585), the average annual water temperature will be higher by 1.8 °C and 3.2 °C, respectively. It should be emphasized that the current and simulated changes are unfavorable, especially considering the impact of temperature on water quality. From an economic perspective, Lake Miedwie serves as a reservoir of drinking water, and changes in the thermal regime should be considered in the management of this ecosystem.
Assessment of the Impact of Meteorological Variables on Lake Water Temperature Using the SHapley Additive exPlanations Method
The water temperature of lakes is one of their fundamental characteristics, upon which numerous processes in lake ecosystems depend. Therefore, it is crucial to have detailed knowledge about its changes and the factors driving those changes. In this article, a neural network model was developed to examine the impact of meteorological variables on lake water temperature by integrating daily meteorological data with data on interday variations. Neural networks were selected for their ability to model complex, non-linear relationships between variables, often found in environmental data. Among various architectures, the Artificial Neural Network (ANN) was chosen due to its superior performance, achieving an R2 of 0.999, MSE of 0.0352, and MAE of 0.1511 in validation tests. These results significantly outperformed other models such as Multi-Layer Perceptrons (MLPs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTM). Two lakes (Lake Mikołajskie and Sławskie) differing in morphometric parameters and located in different physico-geographical regions of Poland were analyzed. Performance metrics for both lakes show that the model is capable of providing accurate water temperature forecasts, effectively capturing the primary patterns in the data, and generalizing well to new datasets. Key variables in both cases turned out to be air temperature, while the response to wind and cloud cover exhibited diverse characteristics, which is a result of the morphometric features and locations of the measurement sites.
Long-Term Changes in the Thermal and Ice Regime of the Biebrza River (Northeastern Poland) in the Era of Global Warming
In the context of ongoing environmental changes, particularly against the backdrop of global warming, significant attention is being given to areas of exceptional natural value that, in many aspects, retain a pristine character. One such area is the Biebrza River in northeastern Poland, which, together with the wetlands in its basin, forms one of the most valuable ecosystems of its kind in Europe. This study analyses the changes in the thermal and ice regime for two hydrological stations, Sztabin and Burzyn, in the period from 1959 to 2023. It was found that the average annual water temperature in this period for the Biebrza River increased by 0.28 °C/decade, and in the case of ice phenomena, statistically significant changes for both stations showed a decline, with an acceleration of the ice cover disappearance by an average of 3 days/decade. These recorded changes should be considered unfavourable, as they will affect the transformation of both the biotic and abiotic characteristics of the river itself, as well as the natural elements associated with it.
Seven Decades of Surface Temperature Changes in Central European Lakes: What Is Next?
Lakes are vital components of the hydrosphere, holding both environmental and economic significance. In recent times, they have undergone transformations in one of their key characteristics—water temperature. Assessing the scale and pace of these changes depends on the length and accuracy of the available data. This study focuses on the two lakes in Poland (Białe Augustowskie and Studzieniczne) with the longest continuous water temperature records, ranging from 1954 to 2023. The results reveal a relatively stable thermal regime until the late 1980s (with changes that were statistically insignificant) and a significant shift over the past three decades, during which the water temperature increased at a rate of 0.5 °C per decade. Importantly, simulations indicate further warming of the water by the end of the 21st century. Depending on the chosen climate change scenario, the warming of both lakes is expected to continue, with the Shared Socioeconomic Pathways (SSP585) scenario projecting a steady increase of 0.5 °C per decade. Given the fundamental importance of water temperature in determining factors such as water quality, these future changes present a significant challenge for water management authorities in terms of maintaining and managing these ecosystems.