RESEARCH ON AQUATIC POLLUTION LEVEL OF MALEIA RIVER BY SIMULATION IN COMPUTATIONAL FLUID DYNAMICS
Watercourses that transit rural / urban areas are susceptible to the phenomenon of aquatic pollution due to various types of polluting
species. The important issues of river pollution and of polluting species dispersion, require an approach with predictive tools (models
for transport of polluting species) which can evaluate the performance of depollution measures/actions to reduce pollution and to
take optimal management decisions. Thus, from January 2017 to May 2017, a monitoring investigation was carried out on the
Maleia watercourse, polluting species concentrations measured by different physical-chemical methods being considered as input
data for the Surface Water Modelling Systems (SMS) software in order to establish the dispersion of pollutants in the aquatic
environment. The hydrodynamics of the river sector has been simulated through a module of the Surface Water Modelling Systems
using the Reynolds form of Navier-Stokes equation system, along with the continuity equation for incompressible fluids in turbulent
motion with free surface. The numerical simulation of advection-diffusion processes at an average depth of the studied river sector,
was used for analyzing the space-time evolution of aquatic pollutants.
The originality of this paper starts from the desideratum that rivers crossing inhabited areas are subjected to discharge of pollutants
which implies the analysis of the quality of the studied water course (Maleia), as well as the illustration of the dispersion of certain
pollutant species by estimating the dilution times as well as the determination of the iso-concentration field.
Numerical models have been obtained for a sector of the Maleia River, providing the possibility of simulating both common and
accidental pollution (related to space-time evolution of transport and dispersion of pollutants). The models obtained allowed the
estimation of water quality in each finite element of the studied sector, and not just in one sampling point, as it is usually measured.