title: [An integrated eutrophication assessment for lakes and reservoirs].
abstract: An integrated eutrophication assessment framework is developed for lakes and reservoirs based on an ecogeographical classification method and an artificial neural network model. Using the USEPA Nutrient Criteria Database as the basic reference and considering the ecogeographical characteristics of Chinese lakes and reservoirs, a simple eutrophication assessment criterion considering the ecogeographical characteristics is proposed for the first time. This criterion places the emphasis on the determination of critical values of key parameters for various regions. Moreover, an artificial neural network (ANN) assessment model is developed, considering the complexity and nonlinearity of eutrophication process. It is found that this ANN assessment model offers the advantage to assess with more accuracy the trophic status in nitrogen-limited water bodies. Integrating such two assessment methods can establish a simple but general eutrophication assessment framework; verification with 30 lakes and reservoirs shows that it can be served as a reliable and cost-effective tool for aquatic environmental management.
authors.affiliation: Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. wf@rcees.ac.cn
authors.forename: Wei-Feng
authors.initials: WF
authors.lastname: Li
authors.forename: Jing-Qiao
authors.initials: JQ
authors.lastname: Mao
mesh_terms: D004784:Environmental Monitoring / Q000379:methods*; D005068:Eutrophication; D005618:Fresh Water / Q000032:analysis; D060106:Lakes / Q000032:analysis*; D016571:Neural Networks, Computer; D014876:Water Pollution / Q000032:analysis* / Q000517:prevention & control; D014881:Water Supply / Q000032:analysis