Application of Optimal Nonstationary Time Series Analysis to Water Quality Data and Pollutant Transport Modelling


Water quality and pollutant transport modelling play an important role in assessing the risk from pollution incidents. They are also important for the sustainable management of water resources. An ability to predict the concentrations of a pollutant travelling along the river is necessary in assessing the ecological impact of the pollutant and to plan a remedy against possible damage to humans and the environment. The risk from a pollutant at a given location along the river depends on the maximum concentration of any toxic component, the travel times of the pollutant from the release point and the duration over which its concentration exceeds feasible threshold levels. These tasks require modelling pollutant transport under varying flow conditions, i.e. unsteady flow. The aim is to outline on-going research on data-based models and to compare the results with physically-based approaches using worked case examples from pollutant transport modelling. In addition to steady-state examples, a Stochastic Transfer pollutant transport model in varying flow conditions is presented. A case study on water quality modelling has the form of a tutorial on the application of a multi-rate Stochastic Transfer Function to the identification of environmental processes.


Monte Carlo Water Quality Modelling Pollutant Transport Transfer Function Model Generalise Likelihood Uncertainty Estimation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



I would like to thank my colleagues from GKSS, Germany, for further use of the data from the River Elbe (among others, Ulrich Callies and Wilhelm Petersen). My collaborators Marzena Osuch, Jaroslaw Napiorkowski and Pawel Rowinski (Institute of Geophysics, PAS, Poland) and Steve Wallis (Heriot Watt University, Edinburgh, UK) are thanked for their help in the River Narew and Murray Burn case studies.


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© Springer-Verlag London Limited 2012

Authors and Affiliations

  1. 1.Institute of GeophysicsPolish Academy of SciencesWarsawPoland

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