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.
Nitrogen loading Water quality Assessment Eutrophication Beijing 3S Bayesian Decision Network
Jing Zhang Huili Gong Xiaojuan Li Mark Ross
The Key Lab of Resource Environment & GIS of Beijing,College of Resource Environment and Tourism Cap Department of Civil and Environmental Engineering,University of South Florida Tampa,FL,U.S.A
国际会议
北京
英文
1-4
2009-06-11（万方平台首次上网日期，不代表论文的发表时间）