Relationship between Water Temperature of Polish Rivers and Large-Scale Atmospheric Circulation

Combined Effect of Climate and Anthropopressure on River Water Quality

This study was a continuation of our investigation of the spatio-temporal variability of the Bzura River's water chemistry. Our research is of particular importance in the context of the recent ecological disaster on the Oder River and concerns the international problem of surface water contamination. The study area was a 120 km section of the Bzura River. We tested more measurement points and with a higher sampling frequency than those used in the national monitoring of river water quality. During two hydrological years, 360 water samples were collected. The selected parameters: electrical conductivity, temperature, dissolved oxygen, dissolved organic carbon, nitrates, phosphates, bicarbonates, chlorides, sodium, potassium, calcium, and magnesium were determined. Numerous results exceeded the Polish threshold limits. Spatio-temporal variability and water quality were assessed using principal component analysis (PCA), cluster analysis (CA), and water quality index (WQI) approaches. Many point sources of pollution related to urbanization, agriculture, and industry were detected. Moreover, due to the changing climatic conditions, a significant difference between temporal variability in both years was observed. Our results indicated that it is necessary to increase the number of measurement stations for surface water monitoring; it will allow for a faster detection of the threat.

Multi-scale variability of hydrothermal regime based on wavelet analysis - The middle reaches of the Yangtze River, China

Water temperature is a major driver of riverine ecosystems and has an extremely significant impact on them. Understanding the multi-scale water temperature dynamics in a river basin is critical to analyze the water temperature status of rivers. In this study, the intra-annual and inter-annual time series of water temperature (WT) at Yichang station in the middle reaches of the Yangtze River over the past 62 years was analyzed using complex Morlet wavelet functions to reveal the complex structure of water temperature variation at multiple time scales. The ecological impact of water temperature changes on the reproduction of the "Four Major Chinese Carp" under the influence of the Three Gorges Dam (TGD). The results showed that the water temperature at Yichang Station has a multi-level time scale structure, with an increasing trend at the inter-annual scale from 1956 to 2017, but different variations at the seasonal scale, and the water temperature cycles at both the inter-annual and seasonal scales have time scale variations of about 8-14 years and 4-7 years, with obvious characteristics of WT variation stages. The inter-annual and summer scales will have low WT in 2017-2022 and high WT in 2023-2027, while the other seasonal scales will have high WT in the next few years, either in the short or medium term. The correlation between air temperature and WT is the most significant among the three drivers of air temperature, flow and rainfall, and the correlation between WT and the air temperature is the most significant in winter scale under the influence of the Three Gorges Dam construction. Since the completion of TGD in 2003, the summer drainage temperature has decreased and the breeding period of the "Four Major Chinese Carp" has been shortened by 30-40 days compared to that before the construction of TGD. The results of this study can be used as a basis for further exploration of the formation mechanism of river water temperature and provide a scientific basis for river ecological protection.

Effects of Oceanic–Atmospheric Oscillations on Rivers

In this Special Issue, we invited scientists devoted to research on the impacts of the ocean and atmosphere oscillations on the climate and weather patterns, resulting in disturbances in the hydrological phenomena. In our view, the main goal has been successfully reached. This Special Issue received investigations based on measurements, modelling and experiments, related to a wide array of changes in river and lake hydrology on different scales, from local and regional to global approaches. We strongly believe that the readers of journal Water can benefit from these new findings and learn more about effects of the ocean and atmosphere on hydrology using the published papers and share the presented results with the scientific community, policymakers and stakeholders [...]

Daily River Water Temperature Prediction: A Comparison between Neural Network and Stochastic Techniques

The temperature of river water (TRW) is an important factor in river ecosystem predictions. This study aims to compare two different types of numerical model for predicting daily TRW in the Warta River basin in Poland. The implemented models were of the stochastic type—Autoregressive (AR), Moving Average (MA), Autoregressive Moving Average (ARMA) and Autoregressive Integrated Moving Average (ARIMA)—and the artificial intelligence (AI) type—Adaptive Neuro Fuzzy Inference System (ANFIS), Radial Basis Function (RBF) and Group Method of Data Handling (GMDH). The ANFIS and RBF models had the most fitted outputs and the AR, ARMA and ARIMA patterns were the most accurate ones. The results showed that both of the model types can significantly present suitable predictions. The stochastic models have somewhat less error with respect to both the highest and lowest TRW deciles than the AIs and were found to be better for prediction studies, with the GMDH complex model in some cases reaching Root Mean Square Error (RMSE) = 0.619 °C and Nash-Sutcliff coefficient (NS) = 0.992, while the AR(2) simple linear model with just two inputs was partially able to achieve better results (RMSE = 0.606 °C and NS = 0.994). Due to these promising outcomes, it is suggested that this work be extended to other catchment areas to extend and generalize the results.

Estimation of the Dependence of Ice Phenomena Trends on Air and Water Temperature in River

The identification of changes in the ice phenomena (IP) in rivers is a significant element of analyses of hydrological regime features, of the risk of occurrence of ice jam floods, and of the ecological effects of river icing (RI). The research here conducted aimed to estimate the temporal and spatial changes in the IP in a lowland river in the temperate climate (the Noteć River, Poland, Central Europe), depending on air temperature (TA) and water temperature (TW) during the multi-annual period of 1987–2013. Analyses were performed of IP change trends in three RI phases: freezing, when there appears stranded ice (SI), frazil ice (FI), or stranded ice with frazil ice (SI–FI); the phase of stable ice cover (IC) and floating ice (FoI); and the phase of stranded ice with floating ice (SI–FoI), frazil ice with floating ice (FI–FoI), and ice jams (IJs). Estimation of changes in IP in connection with TA and TW made use of the regression model for count data with a negative binomial distribution and of the zero-inflated negative binomial model. The analysis of the multi-annual change tendency of TA and TW utilized a non-parametric Mann–Kendall test for detecting monotonic trends with Yue–Pilon correction (MK–YP). Between two and seven types of IP were registered at individual water gauges, while differences were simultaneously demonstrated in their change trends over the researched period. The use of the Vuong test confirmed the greater effectiveness of estimates for the zero-inflated model than for the temporal trend model, thanks to which an increase in the probability of occurrence of the SI phenomenon in the immediate future was determined; this, together with FI, was found to be the most frequently occurring IP in rivers in the temperate climate. The models confirmed that TA is the best estimator for the evaluation of trends of the occurrence of IC. It was shown that the predictive strength of models increases when thermal conditions are taken into consideration, but it is not always statistically significant. In all probability, this points to the impact of local factors (changes in bed and valley morphology and anthropogenic pressure) that are active regardless of thermal conditions and modify the features of the thermal-ice regime of rivers at specific spatial locations. The results of research confirm the effectiveness of compilating a few models for the estimation of the dependence of IP trends on air and water temperature in a river.

Detecting Patterns of Changes in River Water Temperature in Poland

The study determined water temperature trends of rivers in Poland in the period 1971–2015, and also their spatial and temporal patterns. The analysis covered daily water temperature of 53 rivers recorded at 94 water gauge stations and air temperature at 43 meteorological stations. Average monthly, annual, seasonal and maximum annual tendencies of temperature change were calculated using the Mann–Kendall (M–K) test. Regional patterns of water temperature change were determined on the basis of Ward’s hierarchical grouping for 16 correlation coefficients of average annual water temperature in successive 30-year sub-periods of the multi-annual period of 1971–2015. Moreover, regularities in monthly temperature trends in the annual cycle were identified using 12 monthly values obtained from the M–K Z test. The majority of average annual air and water temperature series demonstrate statistically significant positive trends. In three seasons: spring, summer and autumn, upward tendencies of temperature were detected at 70%–90% of the investigated water gauges. In 82% of the analysed rivers, similarity to the tendencies of change of monthly air temperature was concluded, with the climatic factor being recognised as of decisive importance for the changes in water thermal characteristics of the majority of rivers in Poland. In the winter months, positive trends of temperature were considerably weaker and in general statistically insignificant. On a regional scale, rivers with a quasi-natural thermal regime experienced temperature increases from April to November. In the other cases, different directions of change in river water temperature (RWT) were attributed to various forms of human impact. It was also found that for the majority of rivers the average annual water temperature in the analysed 30-year sub-periods displayed upward trends, statistically significant or close to the significance threshold. Stronger trends were observed in the periods after 1980, while a different nature of water temperature change was detected only in a couple of mountainous rivers or rivers transformed by human impact. In the beginning of the analysed period (1971–2015), the average annual water temperature of these rivers displayed positive and statistically significant trends, while after 1980 the trends were negative. The detected regularities and spatial patterns of water temperature change in rivers with a quasi-natural regime revealed a strong influence of climate on the modification of their thermal regime features. Rivers characterised by a clearly different nature of temperature change, both in terms of the direction of the tendencies observed and their statistical significance, were distinguished by alterations of water thermal characteristics caused by human activity. The results obtained may be useful in optimising the management of aquatic ecosystems, for which water temperature is a significant indicator of the ongoing environmental changes.