Assessment of Nitrogen Loading in Miyun Reservoir Beijing Using Bayesian Decision Network

It has been found that non-point source pollution excessive nitrogen loading is one of the main reasons for the eutrophication of Miyun Reservoir, Beijing, China. At present, the research about eutrophication is still confined to a single level of analysis lacking a full perspective of monitoring, integrated simulation and evaluation. The model domain is the area of Miyun Reservoir, Beijing. This paper proposes an interdisciplinary approach in the future incorporating 3S (RS, GIS and GPS) high-tech to extract hydro-ecological environment information, coupled with surface water/groundwater hydrologic modeling and Bayesian Decision Networks (BDN) to preliminary estimate the sources and relative contributions of nitrogen deposited into Miyun Reservoir, Beijing. Remote sensing will be used to refine land use, soil moisture, and biomass information maps. Concentrations of nitrogen in precipitation, surface water, groundwater, and runoff will be sampled. Predictive analysis and scenario developments will be performed using a complete BDN to model decision impacts, performing sensitivity analysis, and gaining further understanding regarding the interaction of variables in the system. The expected increase in nitrogen loading as a result of population growth should be married with management of natural resources to best serve the environment as a whole.