The Distributed Stochastic Monitoring and Modeling on Non-Point Source Pollution and Water Ecosystem Health Assessment

Pollutant factors of water quality for basin and their relationships are the key factors for basin water pollution control and environment management. However it is difficult to obtain sufficient ascertained influence factors information in agricultural non-point source pollution control and modeling aspect especially for the application of large scale models. So in this paper based on environmental factor variability, parameter extrapolation and model scale problems, the discussion on how to use stochastic theory, multi-variable statistics and co-systematic estimation theory then to set up a stochastic monitoring, modeling and parameter extropolation method in order to decrease time redundance and variable dimension and change the model application scale is explored. Besides according to the uncertainty of agricultural non-point source pollution producing ways, the relative basin water environment assessment and modeling scheme through adopting anti-figured river water quality modeling is preferred. The research provides references for regional agricultural nutrient exchange simulation and management, basin pollution prevention and water quality assessment and modeling. And it also contributes to the application of distributed model and reliability analysis in different scale.