Artificial neural network modeling of dissolved oxygen in reservoir

Environmental Monitoring and Assessment

Volumn 186, Issue 2, 2014, Pages 1203-1217

  Chen, Wei Bo ^a   Liu, Wen Cheng ^b,c  

^a NATIONAL SCIENCE AND TECHNOLOGY CENTER FOR DISASTER REDUCTION   (Taiwan)

^b NATIONAL UNITED UNIVERSITY   (Taiwan)

^c National Applied Research Institute   (Taiwan)

Author keywords

Artificial neural network; Dissolved oxygen; Multilinear regression; Reservoir; Water quality modeling

Indexed keywords

ENVIRONMENTAL MONITORING; EUTROPHICATION; FRESH WATER; MODELS, CHEMICAL; NEURAL NETWORKS (COMPUTER); OXYGEN; TAIWAN; WATER POLLUTANTS, CHEMICAL; WATER POLLUTION;

EID: 84893135042     PISSN: 01676369     EISSN: 15732959     Source Type: Journal    
DOI: 10.1007/s10661-013-3450-6     Document Type: Article

References (39)

1. Akkoyunlu, A.; Altun, H.; Cigizoglu, H. K. (2011). Depth-integrated estimation of dissolved oxygen in a lake. Journal of Environmental Engineering, 137(10), 961-967.
2. Boano, F.; Revelli, R.; Ridolfi, L. (2006). Stochastic modelling of DO and BOD components in a stream with random inputs. Advances in Water Resources, 29(9), 1341-1350.
3. Bonnet, M. P.; Poulin, M. (2004). DyLEM-1D: a 1D physical and biochemical for plankton succession, nutrients and dissolved oxygen cycling application to hyper-eutrophic reservoir. Ecological Modelling, 180(2-3), 317-344.
4. Chaves, P.; Kojiri, T. (2007). Conceptual fuzzy neural network model for water quality simulation. Hydrological Processes, 21(5), 634-646.
5. Chen, Y. J.; Wu, S. C. (2006). Behavior of storm-induced suspension interflow in subtropical Feitsui Reservoir, Taiwan. Limnology and Oceanography, 51(2), 1125-1133.
6. Cho, K. H.; Park, Y.; Kang, J. H.; Ki, S. J.; Cha, S.; Lee, S. W.; Kim, J. H. (2009). Interpretation of seasonal water quality variation in the Yeongsan Reservoir, Korea using multivariate statistical analysis. Water Science and Technology, 59(11), 2219-2226.
7. Chou, W. S.; Lee, T. C.; Lin, J. Y.; Yu, S. L. (2007). Phosphorus load reduction goals for Feitsui Reservoir watershed, Taiwan. Environmental Monitoring and Assessment, 131(1-3), 385-408.
8. Curi, W. F.; Unny, T. E.; Kay, J. J. (1995). A stochastic physical system approach to modeling river water quality. Stochastic Hydrology and Hydraulics, 9(2), 117-132.
9. Fletcher, R.; Powell, M. J. D. (1963). A rapid convergent descent method for minimization. The Computer Journal, 6(2), 163-168.
10. Gardner, M. W.; Dorling, S. R. (1998). Artificial neural network (the multilayer perceptron) - a review of application in atmospheric sciences. Atmospheric Environment, 32(14-15), 2626-2636.
11. Jang, J. S. R. (1992). Self-learning fuzzy controllers based on temporal back propagation. IEEE Transactions on Neural Networks, 3(5), 714-723.
12. Jang, J. S. R. (1993). ANFIS: adaptive-network-based fuzzy inference system. IEEE Transactions on Systems, Man, Cybernetics, 23(3), 665-685.
13. Karakaya, N.; Evrendilek, F.; Gungor, K. (2011). Modeling and validating long-term dynamics of diel dissolved oxygen with particular reference to pH in a temperate shallow lake (Turkey). Clean-Soil, Air, Water, 39(11), 966-971.
14. Keskin, M. E.; Taylan, D.; Terzi, O. (2006). Adaptive neural-based fuzzy inference system (ANFIS) approach for modelling hydrological time series. Hydrological Sciences Journal, 51(4), 588-598.
15. Kuo, J. T.; Liu, W. C.; Lin, R. T.; Lung, W. S.; Yang, M. D.; Yang, C. P.; Chu, S. C. (2003). Water quality modeling for the Feitsui Reservoir in northern Taiwan. Journal of the American Water Resources Association, 39(4), 671-687.
16. Kuo, J. T.; Hsieh, M. H.; Lung, W. S.; She, N. (2007). Using artificial network for reservoir eutrophication prediction. Ecological Modelling, 200(1-2), 171-177.
17. Lindim, C.; Pinho, J. L.; Vieira, J. M. P. (2011). Analysis of spatial and temporal patterns in a large reservoir using water quality and hydrodynamic modeling. Ecological Modelling, 222(14), 2485-2494.
18. Liu, W. C.; Chen, W. B.; Nobuaki, K. (2009). Impact of phosphorus load reduction on water quality in a stratified reservoir-eutrophication modeling study. Environmental Monitoring and Assessment, 159(1-4), 393-406.
19. Najah, A.; El-Shafie, A.; Karim, O. A.; Jaafar, O.; El-Shafie, A. H. (2011). An application of different artificial intelligences techniques for water quality prediction. International Journal of Physical Sciences, 6(22), 5298-5308.
20. Najah, A.; El-Shafie, A.; Karim, O. A.; Jaafar, O. (2012). Water quality prediction model utilizing integrated wavelet-ANFIS model with cross-validation. Neural Computing and Applications, 21(5), 833-841.
21. Nayak, P. C.; Sudheer, K. P.; Ragan, D. M.; Ramasastri, K. S. (2004). A neuro fuzzy computing technique for modeling hydrological time series. Journal of Hydrology, 291(1-20), 52-66.
22. Nourani, V.; Komasi, M. (2013). A geomorphology-based ANFIS model for multi-station modeling of rainfall-runoff process. Journal of Hydrology, 490, 41-55.
23. Palani, S.; Liong, S. Y.; Tkalich, P. (2008). An ANN application for water quality forecasting. Marine Pollution Bulletin, 56(9), 1586-1597.
24. Rankovic, V.; Radulovic, J.; Radojevic, I.; Ostojic, A.; Comic, L. (2012). Prediction of dissolved oxygen in reservoirs using adaptive network-based fuzzy inference system. Journal of Hydroinformatics, 14(1), 167-179.
25. Rezaeianzadeh, M.; Tabari, H.; Yazdi, A. A. (2013). Flood flow forecasting using ANN, ANFIS and regression models. Neural Computing and Applications. doi: 10.1007/s00521-013-1443-6.
26. Rucinski, D. K.; Beletsky, D.; DePinto, J. V.; Schwab, D. J.; Scavia, D. (2010). A simple 1-dimensional, climate based dissolved model to central basin of Lake Erie. Journal of Great Lakes Research, 36(3), 465-476.
27. Rumelhart, D. E.; Hinton, G. E.; Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323, 533-536.
28. Sengorur, B.; Dogan, E.; Koklu, R.; Samamdar, A. (2006). Dissolved oxygen estimation using artificial neural network for water quality control. Fresenius Environmental Bulletin, 15(9), 1064-1067.
29. Singh, K. P.; Basant, A.; Malik, A.; Jain, G. (2009). Artificial neural network modeling of the river water quality - a case study. Ecological Modelling, 220(6), 888-895.
30. Soltani, F.; Kerachian, R.; Shirangi, E. (2010). Developing operating rules for reservoirs considering the water quality issues: application of ANFIS-based surrogate models. Expert Systems with Applications, 37(9), 6639-6645.
31. Soyupak, S.; Karaer, F.; Gurbuz, H.; Kivrak, E.; Senturk, E.; Yazici, A. (2003). A neural network-based approach for calculating dissolved oxygen profiles in reservoirs. Neural Computing & Applications, 12(3-4), 166-172.
32. Stansbury, J.; Kozimor, L.; Admiraal, D.; Dove, E. (2008). Water quality modeling of the effects of macrophytes on dissolved oxygen in a shallow tailwater reservoir. Lake and Reservoir Management, 24(4), 339-348.
33. Takagi, T.; Sugeno, M. (1985). Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions on Systems, Man, Cybernetics, 15(1), 116-132.
34. Talei, A.; Chua, L. H. C.; Wong, T. S. W. (2010). Evaluation of rainfall and discharge inputs used by adaptive network-based fuzzy inference system (ANFIS) in rainfall-runoff modeling. Journal of Hydrology, 319(3-4), 248-262.
35. TWMC (Taipei Water Management Committee). (2003). A report of implementation efficiency on protecting water quality/quantity for Taipei Water Source Domain. Taipei: MOEA (in Chinese).
36. Wen, X.; Fang, J.; Diao, M.; Zhang, C. (2013). Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China. Environmental Monitoring and Assessment, 185(5), 4361-4371.
37. White, J. D.; Prochnow, S. J.; Filstrup, C. T.; Scott, J. T.; Byars, B. W.; Zygo-Flynn, L. (2010). A combined watershed-water quality modeling analysis of the Lake Waco reservoir: I. Calibration and confirmation of predicted water quality. Lake and Reservoir Management, 26(2), 147-158.
38. Yao, J. Y.; Xiao, P.; Zhang, Y. H.; Zhan, M.; Cheng, J. W. (2011). A mathematical model of algal blooms based on the characteristics of complex networks theory. Ecological Modelling, 222(20-22), 3727-3733.
39. Ying, Z.; Jun, N.; Fuvi, C.; Liang, G. (2007). Water quality forecast through application of BP neural network at Yuqiao reservoir. Journal Zhejiang University-Science A, 8(9), 1482-1487.