Chlorophyll Emphasis Type="Italic"a/Emphasis S

Authors: Fei Wang Xuan Wang Bin Chen Ying Zhao Zhifeng Yang

Publish Date: 2013/03/21

Volume: 51, Issue: 5, Pages: 1044-1054

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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 WAANN 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 managementThis research was financially supported by the National Water Pollution Control Major Project of China No 2008ZX07209–009 The National Science Foundation for Innovative Research Group No 51121003 and the Program for Changjiang Scholars and Innovative Research Team in University No IRT0809

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