A new approach to spatiotemporal estimation of the river state

Gomółka, Zbigniew; Krutys, Paweł; Twaróg, Bogusław; Zeslawska, Ewa

doi:10.1016/j.jprocont.2020.08.008

Cited by 5 publications

(6 citation statements)

References 24 publications

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“…The results of simulation studies for models that do not take into account the diffusion phenomenon are described in [5][6][7]. The incentive for the experimental part of this paper is the attempt to test, in the form of simulation studies, the extended mathematical model which has been significantly extended in relation to the previously used simplified mathematical models of the river.…”

Section: Resultsmentioning

confidence: 99%

“…Otherwise, the river should be divided into sections corresponding to changes in flow or pollutant inflows. Each section should be treated as an individual case of the model considered [5][6][7]. Based on the Streeter-Phelps formulation, the process of BOD and DO changes can be modelled by differential equations:…”

Section: Streeter-phelps Mathematical River Modelmentioning

confidence: 99%

“…The result is a division of the river into many fragments interpreted individually. A detailed description of the considerations has been included in previous works [5][6][7].…”

Section: Streeter-phelps Mathematical River Modelmentioning

confidence: 99%

“…Its various components, consisting of different types of sensors that monitor the state of water quality and telemetry stations that send real-time data to the intelligent module, enable the monitoring and the prevention of the spread of emerging poor water conditions. A detailed description of the system and the results of research carried out to date, in connection with the intelligent monitoring and control system, are presented in [5][6][7]. The paper [6] presents an approach which employs ANN (Artificial Neural Networks) for the real-time monitoring and control of water quality status.…”

Section: Introductionmentioning

confidence: 99%

“…The paper [6] presents an approach which employs ANN (Artificial Neural Networks) for the real-time monitoring and control of water quality status. The paper [5] presents a spatio-temporal method for analysing the state of river pollution, in the context of application in modern control and measurement systems, for predicting changes. On the other hand, the paper [7] presents an adaptive algorithm to determine the value of the filter amplification factor, which allows for the avoidance of inconveniences, resulting from the need to estimate the characteristics of signals affecting the object under investigation.…”

Section: Introductionmentioning

confidence: 99%

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State Analysis of the Water Quality in Rivers in Consideration of Diffusion Phenomenon

2022

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The waters of rivers are not only used for consumption, industry and agriculture but have also found their way into the transport and energy generation sectors. Many disturbances introduced into the aquatic environment are of the natural variety, which are the result of “admixtures” contained in water, e.g., through contact with soil, and of man-made types, which are directly related to humanities destructive influences. In the presented examinations, the most important processes affecting the spread and transport of these pollutants are taken into account, i.e., advection and diffusion. The authors present observations on the influence of the diffusion phenomenon on river flow modelling processes. Such an approach allows for the separation of the dynamics of water flow and the dynamics of transport of the dissolved substance mass. Specifically, phenomena occurring in relation to spatial coordinates, time and variable parameter values in the proposed mathematical model were analysed. Ultimately, this research will contribute to the correct design and implementation of a complementary diffusion module as an extension to an intelligent water quality control and monitoring system. The Intelligent Analytical Computing Control System architecture under development already includes other modules such as the Intelligent Filtration and Prediction Module and, complemented by the Intelligent Diffusion Module, provides a complementary tool for monitoring river hydromorphology. Implementation of the above solution will help to improve water quality, thus preventing and eliminating the appearance of undesirable pollutants in rivers, and increase the standard of living in the current threatened environmental world.

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Section: Resultsmentioning

confidence: 99%

Section: Streeter-phelps Mathematical River Modelmentioning

confidence: 99%

“…The result is a division of the river into many fragments interpreted individually. A detailed description of the considerations has been included in previous works [5][6][7].…”

Section: Streeter-phelps Mathematical River Modelmentioning

confidence: 99%