Filters
Return to Nature: Renaturisation of Dried-Out Lakes in Poland
Over the centuries, extensive changes have occurred in the functioning of the hydrosphere. In the case of Poland, the hydrographic network has been significantly transformed, and many of its elements have ceased to exist. The aim of this study was to investigate renaturalised lakes and to determine their original volume, which is a fundamental parameter in the context of stabilising water relationships. Based on archival cartographic materials, the locations of 15 such lakes were determined, with their volume totaling 11.7 million m3. This indicates a significant potential for renaturalised lakes in the context of increasing water resources. In the long term, the methodology adopted in this work may complement water-management efforts aimed at increasing retention and offering new ecosystem services. Such an approach is less invasive to the natural environment and more economically justified compared to new investments in artificial hydrotechnical infrastructure.
Challenges and Prospects for Modeling Lake Water Temperature in a Changing Climate
Climate change is having a significant impact on the temperature dynamics of lakes worldwide, affirming the need for accurate modeling to inform management and conservation strategies.
150-year daily data (1870–2021) in lakes and rivers reveals intensifying surface water warming and heatwaves in the Pannonian Ecoregion (Hungary)
Daily water‐level forecasting for multiple polish lakes using multiple data‐driven models
AbstractWater level in lakes fluctuates frequently due to the impact of natural and anthropogenic forcing. Frequent fluctuations of water level will impact lake ecosystems, and it is thus of great significance to have a good knowledge of water‐level dynamics in lakes. However, forecasting daily water‐level fluctuation in lake systems remains a tough task due to its non‐linearity and complexity. In this study, two deep data‐driven models, including gated recurrent unit (GRU) and long short‐term memory (LSTM), were coupled with attention mechanism for the forecasting of daily water level in lakes for the first time. Daily water‐level times series in five lowland lakes in Poland were used to evaluate the models. Root mean squared error (RMSE) and mean average error (MAE) were used for the evaluation of model performance. The modelling results were compared with the traditional feed‐forward neural networks (FFNN), GRU, LSTM, and zero‐order forecast. The modelling results showed that sequential deep learning models do not outperform feed‐forward models in all cases. In most cases, LSTM with attention mechanism (average RMSE = 0.88 cm, average MAE = 0.69 cm) outperforms GRU with attention mechanism (average RMSE = 1.00 cm, average MAE = 0.81 cm). However, attention mechanism did not help to improve the accuracy of the GRU and LSTM for most cases. Based on the average performance in different lakes, GRU performs the best among the deep learning models (average RMSE = 0.84 cm, average MAE = 0.66 cm). Zero‐order forecast models perform better than deep learning models for predicting tomorrow (average RMSE = 0.71 cm, average MAE = 0.39 cm), while deep learning models perform better as the horizon of prediction increases.
A novel optimized model based on NARX networks for predicting thermal anomalies in Polish lakes during heatwaves, with special reference to the 2018 heatwave
Effect of Hydraulic Structure on Mitigating Extreme Hydrological Conditions of a Small River in the Temperate Zone (Główna River, Central Europe)
Water resources are of elementary economic and environmental importance, and the observed global transformations as well as regional environmental conditions necessitate activities aimed at providing an optimal amount of water at different levels. One such solution is hydrotechnical infrastructure that permits the precise control of the amount of water in the catchment. This paper presents results concerning changes in the water flow in the Główna River in Poland before (1955–1983) and after (1984–2021) the construction of the Kowalski Reservoir. In the former period, there were no changes in water flow, and the obtained results were not statistically significant (p 0.05). In the period after the construction of the reservoir, a decreasing trend in monthly flow was observed in December, April, July, September, and October. Moreover, a decrease in 1, 3, 7, and 90 day maximum flow was observed. For maximum 30 day flow, the changes were below the threshold of the adopted significance level. Moreover, minimum flow in the period after the construction of the reservoir showed no significant decreasing trend. In hydrological terms, the reservoir served its purpose by contributing to the stabilisation of the water flow. This information is important from the point of view of an increase in retention and corresponds with a broader programme conducted in the territory of Poland. In the context of the construction of further reservoirs, it is important to investigate the current range of changes in water circulation for objects of the type already functioning in the environment, constituting an actual point of reference.
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.
How Useful Are Moderate Resolution Imaging Spectroradiometer Observations for Inland Water Temperature Monitoring and Warming Trend Assessment in Temperate Lakes in Poland?
Continuous software development and widespread access to satellite imagery allow for obtaining increasingly accurate data on the natural environment. They play an important role in hydrosphere research, and one of the most frequently addressed issues in the era of climate change is the thermal dynamics of its components. Interesting research opportunities in this area are provided by the utilization of data obtained from the moderate resolution imaging spectroradiometer (MODIS). These data have been collected for over two decades and have already been used to study water temperature in lakes. In the case of Poland, there is a long history of studying the thermal regime of lakes based on in situ observations, but so far, MODIS data have not been used in these studies. In this study, the available products, such as 1-day and 8-day MODIS land surface temperature (LST), were validated. The obtained data were compared with in situ measurements, and the reliability of using these data to estimate long-term thermal changes in lake waters was also assessed. The analysis was conducted based on the example of two coastal lakes located in Poland. The results of 1-day LST MODIS generally showed a good fit compared to in situ measurements (average RMSE 1.9 °C). However, the analysis of long-term trends of water temperature changes revealed diverse results compared to such an approach based on field measurements. This situation is a result of the limited number of satellite data, which is dictated by environmental factors associated with high cloud cover reaching 60% during the analysis period.
Use of Landsat Satellite Images in the Assessment of the Variability in Ice Cover on Polish Lakes
Despite several decades of observations of ice cover in Polish lakes, researchers have not broadly applied satellite images to date. This paper presents a temporal and spatial analysis of the variability in the occurrence of ice cover on lakes in the Drawskie Lakeland in the hydrological years 1984–2022 based on satellite data from Landsat missions 4, 5, 7, 8, and 9. The range of occurrence of ice cover was determined based on the value of the Normalised Difference Snow Index (NDSI) and blue spectral band (ρλblue). The determination of ice cover extent adopted ρλblue values from 0.033 to 0.120 as the threshold values. The analysis covered 67 lakes with an area from 0.07 to 18.71 km2. A total of 53 images were analysed, 14 and 39 out of which showed full and partial ice cover, respectively. The cluster analysis permitted the designation of two groups of lakes characterised by an approximate range of ice cover. The obtained results were analysed in the context of the morphometric parameters of the lakes. It was evidenced that the range of the ice cover on lakes is determined by the surface area of the lakes; their mean and maximum depth, volume, length, and width; and the height of the location above sea level. The results of analyses of the spatial range of ice cover in subsequent scenes allowed for the preparation of maps of probability of ice cover occurrence that permit the complete determination of its variability within each of the lakes. Monitoring of the spatial variability in ice cover within individual lakes as well as in reference to lakes not subject to traditional observations offers new research possibilities in many scientific disciplines focused on these ecosystems.
A stacked machine learning model for multi-step ahead prediction of lake surface water temperature
River Thermal Dynamics and Heatwaves of Polish Rivers Under Climate Change
AbstractProgression of global warming poses a significant risk to river ecosystems. However, how river heatwaves' characteristics across complex hydrological systems alter under climate change is still poorly understood. In this study, long‐term reconstructed daily river water temperatures (RWTs) from 125 hydrological stations in 70 rivers across Poland, were used. Bayesian estimator of abrupt change, seasonal change, and trend (BEAST) method was used to track the abrupt changes of RWTs. Moreover, the characteristics of river heatwaves, including number, duration, intensity, and category, were evaluated. BEAST analysis revealed pronounced spatiotemporal variability in RWT trends in Poland, influenced by natural and anthropogenic factors. Notably, the maximum abrupt changes of RWT were observed during the 1980s and 1990s. Southern Poland, particularly mountainous regions, exhibited more pronounced river temperature changes and severe heatwaves compared to the milder northern regions. Our results also showed a statistically significant increase in frequency and intensity of river heatwaves at 121 out of the 125 studied stations (p‐value < 0.05), which were consistent with the warming of air temperatures. For all the designated stations, the majority of river heatwaves belonged to the category “moderate,” followed by “strong,” “severe,” and “extreme.” Number, duration, and intensity of the river heatwaves were highly correlated with air temperatures, with the correlation coefficients being 0.624, 0.631, and 0.604, respectively. Our findings further suggest that mitigation measures shall be taken to reduce the effects of climate warming on Polish river ecosystems, especially under low flow conditions which are more vulnerable to the intensified river heatwaves.
Less and thinner ice: seven decades of change in the ice cover of temperate lakes (Central Europe, Poland)
A Century of Changes in the Surface Area of Lakes in West Poland
Lakes are an important element of the hydrosphere that contribute to the stabilisation of water circulation by providing biodiversity conditions or supporting the development of different branches of the economy. All these properties depend on the longevity of lakes in the environment and the processes related to their evolution. Based on archival morphometric data from historical maps and modern cartographic studies, this paper presents an analysis of changes in their surface area over a period of 100 years. Among 169 lakes, a decrease in surface area was recorded in 156 cases (including the complete disappearance of two lakes); no change was observed in four lakes; and seven lakes increased their surface area. The total surface area of all the lakes has decreased by 11.4% in comparison with the initial state in the early 20th century. The highest rate of decline concerned the shallowest lakes with a maximum depth of up to 5.0 m and lakes with the smallest surface area of up to 20 ha, averaging 24.1% and 22.2%, respectively. The spatial distribution of changes in the surface area of lakes is variable, and at a larger scale it presents no similarities. This suggests that factors determining the rate and direction of changes in the surface area of lakes depend on their individual features and local conditions, which is in accordance with similar studies from the territory of Poland. The obtained results reveal the scale of the changes in the surface area of the lakes, potentially providing important information for authorities in charge of water management in the context of activities aimed at slowing down the disappearance of these valuable ecosystems.