Monika B. Kalinowska

Scenarios of the spread of a waste heat discharge in a river — Vistula River case study

The problem of two-dimensional mathematical modelling of heated cooling water discharges into running waters is considered in the paper. Two models — one for the evaluation of 2D turbulent velocity field and the other, developed by authors of the study, for 2D heat transport in open-channels — were used in the calculations. Relevant scenarios of the spread of heated water discharged from a designed gas-stem power plant to be constructed at the Vistula River were presented. Environmentally most friendly variant of the discharge of the thermal pollution was selected from among four various variants.

Evaluation of friction velocity in unsteady flow experiments

ABSTRACT The paper presents estimates of the friction velocity in unsteady flow using two formulas that have been derived from the two-dimensional Reynolds and one-dimensional Saint-Venant equations. Experiments on unsteady flow were performed to collect data on the spatio-temporal evolution of the water level and velocity necessary to apply the formulas. The key feature of these experiments is high temporal resolution of the data. The application of the formulas is presented with an in-depth analysis of the flow conditions, methods for estimating the input variables and an uncertainty analysis of the results. The evaluation of the input variables focuses on the spatial derivative of water depth, which is the most problematic variable in this study. A comparison of the formulas for the friction velocity shows that they are equivalent for the cases presented in this paper.

The Uncertainty of Measurements in River Hydraulics: Evaluation of Friction Velocity Based on an Unrepeatable Experiment

The chapter addresses the issue of evaluating uncertainty of measurements in river hydraulics. As replication of experiments in natural settings is not possible, the chapter highlights the case of unrepeatable experiments. Evaluation of friction velocity under flood conditions basing on the Saint-Venant set of equations serves as an example of indirect measurement of physical quantity.

Thermal Pollution in Rivers—Modelling of the Spread of Thermal Plumes

Modeling framework for stream temperature, especially after introducing substantial amount of heat pollution, is presented in this chapter. An overview of the mathematics and solution techniques suited for heat transfer quantification is given and the models presented range from 3D aimed at short distances towards 1D approach allowing for modeling of heat transfer over long distances. A special attention has been paid to the depth averaged two-dimensional models which are particularly useful when the fate of heat pollution such as the heat discharged from a steam power station is considered. The processes of exchange between the river water and river surrounding are also discussed. Examples of computational solutions are provided and discussed as well.

Are Evolutionary Algorithms Effective in Calibrating Different Artificial Neural Network Types for Streamwater Temperature Prediction

Streamwater temperature may be severely affected by the global warming. Different types of models could be used to evaluate the regime of water temperatures in future climatic conditions, including artificial neural networks. As neural networks have no physical background, they require calibration of large number of parameters. This is typically done by gradient-based algorithms, however there is an ongoing debate on usefulness of metaheuristics for this task. In this paper more than ten Swarm Intelligence and Evolutionary Algorithms, including one developed especially for this study, are tested to train four kinds of artificial neural networks (multi-layer perceptron, product-units, adaptive-network-based fuzzy inference systems and wavelet neural networks) for daily water temperature prediction in a natural river located in temperate climate zone. The results are compared with the ones obtained when the classical Levenberg-Marquardt algorithm is used. Finally, the ensemble aggregating approach is tested. Although the research confirms that most metaheuristics do not suite well for training any kind of neural networks, there are exceptions that include the newly proposed heuristic. However, the gain achieved when using even the best metaheuristics is low, comparing to the effort (computational time and complexity of such algorithms). Using ensemble aggregation approach seems to have higher impact on the model performance than seeking for new training methods.

Sensitivity Analysis for the Water-Air Heat Exchange Term

A term expressing heat exchange between water and air is often present in models of thermal pollution spreading in rivers. The importance of this term depends strongly on temporal and spatial scale of the process as well on meteorological and hydrological conditions. Although heat exchange between the water and atmosphere has been studied for many years, its determination is still difficult in practical cases, and different simplifications are considered in practice. The objective of this study was to verify which of the input data needed for the net heat flux calculations are of utmost importance and which of them influences its final value most significantly. The analyses have been performed for several data sets collected in natural conditions.

Pioneering Works in Polish Environmental Hydraulics: The Flavor of World-Class Science

Achievements of a noteworthy Polish scientist, Professor Wlodzimierz Czernuszenko, in the context of international cooperation are presented herein. He was one of the initiators of the in-depth research in the emerging field of environmental hydraulics. He is well-known for his studies on turbulence in open-channels, heat and mass transport in rivers and quite recently on solid particles’ transport in rivers from the perspective of two-phase flows. This chapter was prepared on the occasion of the 50th anniversary of his scientific work.