Simulation of diffuse source polluted water environment based on MIKE21: A case study of the urban section of the Bai river

Abstract

Affected by urban construction and industrial discharge, the diffuse source pollution of river water environment in urban sections is becoming more and more serious. The use of numerical models can accurately and efficiently simulate the process of diffuse source pollution and analyze its evolution. Based on MIKE21, the urban river water environment model of the Bai river is constructed. After parameter calibration, it is proved that the model has high accuracy. Based on the discharge of this river section in 2018, the river diffuse source pollution is simulated under three hydrological conditions, and the BP neural network is used to simulate the river diffuse source pollution. Network assessment of water quality in dry years. The results showed that the four water quality indicators showed the spatial distribution characteristics of upstream>urban section>downstream, and the river water quality in the year showed the temporal distribution characteristics of flood season better than a non-flood season. The mean value of the coefficient of certainty R2 reaches 0.94 when comparing the simulated and measured values, which indicates that the model has high applicability and satisfactory fit. If the water quality of the water year does not meet the standard, the diffuse source pollution discharge should be reduced from May to October. This study can provide reference and guidance for urban river diffuse source pollution control. HIGHLIGHT A two-dimensional hydrodynamic model was developed using MIKE software and validated by field test data to determine the two-dimensional model parameters, including flow rate, flow velocity, eddy viscosity coefficient, boundary conditions, roughness, etc.;

Keywords

• bp neural network
• diffuse source pollution
• numerical simulation
• water environment