Filters
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.
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.
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)
Innowacje technologiczne oraz system monitoringu, prognozowania i operacyjnego planowania działań melioracyjnych, dla precyzyjnego gospodarowania wodą w skali obiektu melioracyjnego
A novel optimized model based on NARX networks for predicting thermal anomalies in Polish lakes during heatwaves, with special reference to the 2018 heatwave
Impact of Water Meadow Restoration on Forage Hay Production in Different Hydro-Meteorological Conditions: A Case Study of Racot, Central Poland
Water meadows in river valleys are a source of very valuable forage. Due to their specificity, an appropriate approach to water management is required. This study assessed the impact of the reclamation of a traditional gravity irrigation system, aimed at saving and reducing water loss from meadows through controlled drainage. The main purpose of this study was to evaluate the investment in drainage system restoration in the context of improving the yield of fodder hay in water meadows under changing hydrometeorological conditions. The analysis was performed on the basis of meteorological and hydrological data from 30 years in the period 1989–2018. The research was conducted on the basis of two assumptions. The first concerned management of meadows without the use of subsoil irrigation based only on the amount of water supplied from rainfall. The second variant assumed deficit irrigation based on periodic water meadows with systems of ditches and drainage channels that supplied water depending on the currently available amount of water in a nearby river. The field research was performed during the crop season of 2019 and 2020. Drainage restoration investment allowed the amount of water supplied to the meadows to be increased. In the analysed period, on average, almost 30 mm of water was delivered through the ditch system. There was also an increase in hay yields of 32%. However, the investment costs, which amounted to EUR 23,382.48, were too high for this type of farm production. A positive net present value (NPV) was obtained only for 25% of cases of hydrometeorological conditions (first quartile). For the other years, the investment was not profitable.
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.
Reconstruction of Surface Water Temperature in Lakes as a Source for Long-Term Analysis of Its Changes
One of the key parameters of lakes is water temperature, which influences many physical and biochemical processes. In Poland, in situ temperature measurements are or have been conducted in only about 30 lakes, whereas there are over 3000 lakes with an area larger than 10 hectares. In many cases, the length of existing observation series is not always sufficient for long-term analysis. Using artificial neural networks of the multilayer perceptron network (MLP) type, the reconstruction of average monthly water temperatures was carried out for nine lakes located in northern Poland. During the validation stage of the reconstruction results, BIAS values were obtained in the range of −0.33 to 0.44 °C, the mean absolute error was 0.46 °C, and the root mean square error was 0.61 °C. The high quality of the reconstructed data allowed for an assessment of water temperature changes in the analyzed lakes from 1993 to 2022 using the Mann–Kendall and Sen tests. It was found that, on an annual basis, the water temperature increased by an average of 0.50 °C per decade, ranging from 0.36 °C per decade to 0.64 °C per decade for individual lakes. For specific months, the largest increase was observed in November, about 0.99 °C per decade, and the smallest in May, 0.07 °C per decade. The obtained results confirm previous studies in this field while adding new data from lakes, which are particularly significant for the western part of Poland—a region with a previously limited number of monitored lakes. According to the findings, the analyzed lakes have undergone significant warming over the past three decades, which is important information for water management authorities.
Lake Water Temperature Modeling in an Era of Climate Change: Data Sources, Models, and Future Prospects
AbstractLake thermal dynamics have been considerably impacted by climate change, with potential adverse effects on aquatic ecosystems. To better understand the potential impacts of future climate change on lake thermal dynamics and related processes, the use of mathematical models is essential. In this study, we provide a comprehensive review of lake water temperature modeling. We begin by discussing the physical concepts that regulate thermal dynamics in lakes, which serve as a primer for the description of process‐based models. We then provide an overview of different sources of observational water temperature data, including in situ monitoring and satellite Earth observations, used in the field of lake water temperature modeling. We classify and review the various lake water temperature models available, and then discuss model performance, including commonly used performance metrics and optimization methods. Finally, we analyze emerging modeling approaches, including forecasting, digital twins, combining process‐based modeling with deep learning, evaluating structural model differences through ensemble modeling, adapted water management, and coupling of climate and lake models. This review is aimed at a diverse group of professionals working in the fields of limnology and hydrology, including ecologists, biologists, physicists, engineers, and remote sensing researchers from the private and public sectors who are interested in understanding lake water temperature modeling and its potential applications.
River water temperature prediction using hybrid machine learning coupled signal decomposition: EWT versus MODWT
150-year daily data (1870–2021) in lakes and rivers reveals intensifying surface water warming and heatwaves in the Pannonian Ecoregion (Hungary)
Spatial distribution of trace and rare earth elements of bottom sediments in Lake Ostrowite, Bory Tucholskie National Park, Poland
AbstractLake pollution has attracted concerns worldwide; especially the excessive accumulation of trace elements (TEs) and rare earth elements (REEs) in bottom sediments can pose a serious threat to ecosystem health. However, there is still a knowledge gap on the level of sediment pollution in lakes isolated from the direct impact of pollution sources, their spatial variability, and also on the factors influencing this state. The aim of this study is to investigate the level and spatial variability of TEs and REEs concentrations, as well as to determine their source and the factors determining their distribution in the bottom sediments of Lake Ostrowite. Lake Ostrowite is the largest and deepest water body located in the Bory Tuholskie National Park (in northern Poland), which completely isolates the lake from the direct impact of pollution sources. The study covered analyses of 32 surface samples of bottom sediments. The concentrations of 24 TEs and 14 REEs were determined using inductively coupled plasma mass spectrometry (ICP‐QQQ‐MS). The assessment of the enrichment of bottom sediments in TEs and REEs employed geochemical background values (GBV) that provided the basis for the calculation of relative concentrations and geochemical indices. The determination of their sources and supply routes was based on the cluster analysis and principal component analysis. The obtained results point to the enrichment of the bottom sediments with TEs and REEs. Relative concentration values of TEs and REEs in reference to geochemical background values were in ranges from 0.01 to 7.31, at an average of 0.99, and from 0.03 to 4.29, averaging 1.76, respectively. The enrichment factor values show moderately severe enrichment of sediments at the study sites. This was primarily determined by the concentrations of Ag (from the TEs group) and Lu (from the REEs group). The metal pollution index values showed an approximate spatial distribution of points in terms of the presence of TEs and REEs. The lowest concentrations of TEs and REEs occurred on the eastern shore of the western basin of Lake Ostrowite. TEs and REEs concentrations in sediments are positively correlated with the content of organic matter and depth and negatively correlated with distance of the sampling point from the river outflow from Lake Ostrowite. On the eastern shore of the western basin, TEs and REEs concentrations are additionally shaped by wind, predominantly from the western direction. With water wave action, organic matter is transported to the central part of the western basin, where it is accumulated. Since the lake is isolated from point and nonpoint pollution sources, relevant from a biogeochemical point of view are dry and wet depositions from the atmosphere as well as aquatic vegetation, shoreline vegetation, forest litter, soil, and groundwater.
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.
Diversification of macrophytes within aquatic nature-based solutions (NBS) developing under urban environmental conditions across European cities
Analysis of the impact of road noise on urban green spaces: a case study of the dendrological garden in Poznań, Poland
Abstract Green parks and gardens in urban areas are an essential part of ecosystem services for inhabitants, especially in cities where people are affected by road noise. These problems have been the subject of many studies worldwide. Such works have been carried out at many levels—both in the contexts of spatial planning and ecological analyses. In relation to this, the design of noise maps and related spatial modelling is significant. The paper presents the results of a survey of the acoustic environment in the Dendrological Garden in Poznań—the fifth largest city in Poland—which is a vital part of the city’s green zone. The analysis of the noise distribution across the park’s zones was carried out at frequent intervals using sound-level surveys during 2014 and 2020. Moreover, acoustic maps developed for Poznań in 2012 and 2017 were compared with these recent studies. The changes (gain or loss) in those areas with a particular noise level are based on the area variability index.
How Climate Change Affects River and Lake Water Temperature in Central-West Poland—A Case Study of the Warta River Catchment
Climate change has a significant impact on the abiotic and biotic environment. An increase in air temperatures translates into higher temperatures of water constituting the habitat of a wide range of species. The purpose of this study is to present the direction and extent of water temperature increases in eight rivers and three lakes on a monthly and annual basis. The analysis of river water temperatures used both measured data and data reconstructed using artificial neural networks from the period of 1984–2020. The analysis of the direction and extent of changes in air and water temperatures was performed using Mann-Kandall tests and a modified Sen test. The analysis of water temperature changes was conducted against the background of climatic conditions and catchment characteristics. The results indicate that in the Warta River basin in the period of 1984–2020, the average annual temperature rise reached 0.51 °C decade−1, ranging from 0.43 to 0.61 °C decade−1. This translated into an increase in mean annual water temperatures in lakes in a range from 0.14 to 0.58 °C decade−1, and for rivers in a range from 0.10 to 0.54 °C decade−1. The greatest changes in air temperature occurred in April, June, August, September, and November. It was reflected in an increase in water temperature in lakes and rivers. However, these changes did not occur in all rivers and lakes, suggesting the role of local factors that modify the effect of climate change. The study showed that the extent of air temperature changes was significantly higher than the extent of water temperature changes in rivers.
Hydrological methods in environmental flows. Is it really simple? a critical study of selected catchments in central Europe
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.
