PREDICTION OF WATER QUALITY IN RIVERS WITH LOW DISCHARGE USING INFORMATION TECHNOLOGIES

In most cases mathematical modeling of such objects as rivers is based on incomplete deterministic and probabilistic experimental information. In this context, we have developed a scheme of statistical testing, which allows creating an adequate model based on available experimental data. Acceptable...

Full description

Saved in:
Bibliographic Details
Published inInternational Multidisciplinary Scientific GeoConference : SGEM Vol. 1; pp. 577 - 584
Main Authors Nemtinov, Vladimir, Nemtinova, Yulia, Borisenko, Andrey, Karpushkin, Sergey, Egorov, Sergey
Format Conference Proceeding
LanguageEnglish
Published Sofia Surveying Geology & Mining Ecology Management (SGEM) 01.01.2016
Subjects
Accuracy
Ammonification
Aquaculture
Atmospheric models
Atmospheric oxygen
Back propagation
Computer simulation
Denitrification
Dissolved oxygen
Experimental data
Fuzzy logic
Fuzzy sets
Genetic algorithms
Illustrations
Initial conditions
Kalman filters
Markov analysis
Mathematical models
Methods
Modelling
Monte Carlo simulation
Neural networks
Nitrification
Norms
Organic matter
Oxidation
Oxygen
Parameters
Plankton
Principal components analysis
Probability theory
Proteins
Random numbers
Random variables
Rivers
Statistical analysis
Statistical methods
Urea
Wastewater
Wastewater treatment
Water quality
Wavelet transforms
China
Online AccessGet full text

Cover

More Information
Summary:In most cases mathematical modeling of such objects as rivers is based on incomplete deterministic and probabilistic experimental information. In this context, we have developed a scheme of statistical testing, which allows creating an adequate model based on available experimental data. Acceptable ranges of the model parameters are obtained as a result of simulation tests based on the Monte Carlo method. Based on either known or plausible ranges of changes in the initial conditions, parameters and input variables random number generator creates their combination. Solving the model with these values allows us to calculate the reaction of the model and to verify the restrictions, which are obtained from experimental data. Sufficient accuracy of the number of tests estimates is obtained using the Laplace integral theorem. Illustration of the proposed scheme is made on the example of Tsna River as receiver of treated wastewater from industrial enterprises of Tambov (Russia). As a result of studying the processes occurring in the river, we have defined the processes of aerobic oxidation of organic matter, nitrification, denitrification, plankton growth and dying off, water reaeration with atmospheric oxygen, protein and urea ammonification, ion exchange, and others. At the final stage of Tsna river study we have made forecasts about the content of water dissolved oxygen. Water quality at the control station of the river complies with the accepted norms with a probability of not less than 0.89.
ISSN:1314-2704