title: Chlorophyll a simulation in a lake ecosystem using a model with wavelet analysis and artificial neural network.
abstract: Accurate and reliable forecasting is important for the sustainable management of ecosystems. Chlorophyll a (Chl a) simulation and forecasting can provide early warning information and enable managers to make appropriate decisions for protecting lake ecosystems. In this study, we proposed a method for Chl a simulation in a lake that coupled the wavelet analysis and the artificial neural networks (WA-ANN). The proposed method had the advantage of data preprocessing, which reduced noise and managed nonstationary data. Fourteen variables were included in the developed and validated model, relating to hydrologic, ecological and meteorologic time series data from January 2000 to December 2009 at the Lake Baiyangdian study area, North China. The performance of the proposed WA-ANN model for monthly Chl a simulation in the lake ecosystem was compared with a multiple stepwise linear regression (MSLR) model, an autoregressive integrated moving average (ARIMA) model and a regular ANN model. The results showed that the WA-ANN model was suitable for Chl a simulation providing a more accurate performance than the MSLR, ARIMA, and ANN models. We recommend that the proposed method be widely applied to further facilitate the development and implementation of lake ecosystem management.
authors.affiliation: Key Laboratory for Water and Sediment Sciences of Ministry of Education, School of Environment, Beijing Normal University, Beijing, China.
authors.forename: Fei
authors.initials: F
authors.lastname: Wang
authors.forename: Xuan
authors.initials: X
authors.lastname: Wang
authors.forename: Bin
authors.initials: B
authors.lastname: Chen
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhao
authors.forename: Zhifeng
authors.initials: Z
authors.lastname: Yang
mesh_terms: D002681:China; D002734:Chlorophyll / Q000032:analysis*; D000077194:Chlorophyll A; D003198:Computer Simulation; D017753:Ecosystem; D004784:Environmental Monitoring; D005068:Eutrophication; D005544:Forecasting; D060106:Lakes / Q000737:chemistry; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D060753:Water Quality; D058067:Wavelet Analysis
chemical_list: D002734:Chlorophyll; D000077194:Chlorophyll A