title: Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China.
abstract: Identification and quantification of dissolved oxygen (DO) profiles of river is one of the primary concerns for water resources managers. In this research, an artificial neural network (ANN) was developed to simulate the DO concentrations in the Heihe River, Northwestern China. A three-layer back-propagation ANN was used with the Bayesian regularization training algorithm. The input variables of the neural network were pH, electrical conductivity, chloride (Cl(-)), calcium (Ca(2+)), total alkalinity, total hardness, nitrate nitrogen (NO3-N), and ammonical nitrogen (NH4-N). The ANN structure with 14 hidden neurons obtained the best selection. By making comparison between the results of the ANN model and the measured data on the basis of correlation coefficient (r) and root mean square error (RMSE), a good model-fitting DO values indicated the effectiveness of neural network model. It is found that the coefficient of correlation (r) values for the training, validation, and test sets were 0.9654, 0.9841, and 0.9680, respectively, and the respective values of RMSE for the training, validation, and test sets were 0.4272, 0.3667, and 0.4570, respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable. The most effective inputs were determined as pH, NO3-N, NH4-N, and Ca(2+). Cl(-) was found to be least effective variables on the proposed model. The identified ANN model can be used to simulate the water quality parameters.
authors.affiliation: Key Laboratory of Coastal Zone Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Chunhui Rd 17, Yantai, 264003 Shandong Province, China. xhwen@yic.ac.cn
authors.forename: Xiaohu
authors.initials: X
authors.lastname: Wen
authors.forename: Jing
authors.initials: J
authors.lastname: Fang
authors.forename: Meina
authors.initials: M
authors.lastname: Diao
authors.forename: Chuanqi
authors.initials: C
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002681:China; D004784:Environmental Monitoring / Q000379:methods*; D008956:Models, Chemical; D016571:Neural Networks, Computer; D009584:Nitrogen / Q000032:analysis; D010100:Oxygen / Q000032:analysis*; D045483:Rivers / Q000737:chemistry*; D014874:Water Pollutants, Chemical / Q000032:analysis*; D014877:Water Pollution, Chemical / Q000706:statistics & numerical data
chemical_list: D014874:Water Pollutants, Chemical; D009584:Nitrogen; D010100:Oxygen