DBPapers
DOI: 10.5593/SGEM2016/B31/S12.075

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

V. Nemtinov, Y.Nemtinova, A.Borisenko, S.Karpushkin, S. Egorov
Wednesday 7 September 2016 by Libadmin2016

References: 16th International Multidisciplinary Scientific GeoConference SGEM 2016, www.sgem.org, SGEM2016 Conference Proceedings, ISBN 978-619-7105-61-2 / ISSN 1314-2704, June 28 - July 6, 2016, Book3 Vol. 1, 577-584 pp

ABSTRACT
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 re-aeration 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.

Keywords: prediction of water quality, river with low discharge, mathematical modeling, information technologies.