Feasibility Assessment of Data-Driven Models in Predicting Pollution Trends of Omerli Lake, Turkey

Water Resources Management

Volumn 24, Issue 13, 2010, Pages 3419-3436

  Akkoyunlu, Atilla ^a   Akiner, Muhammed Ernur ^a  

^a BOGAZICI UNIVERSITY   (Turkey)

Author keywords

Artificial neural network; Eutrophic status; Omerli Lake; Regression analysis; Water pollution

Indexed keywords

AMMONIUM NITROGEN; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; COMMONLY USED; DATA-DRIVEN MODEL; DISSOLVED OXYGEN LEVELS; EUTROPHIC STATUS; FEASIBILITY ASSESSMENT; LAKE WATERS; NITRATE NITROGEN; NITRITE NITROGEN; OMERLI LAKE; TOTAL PHOSPHORUS; VOLLENWEIDER DIAGRAMS;

AMMONIUM COMPOUNDS; BIOCHEMICAL OXYGEN DEMAND; DISSOLUTION; EUTROPHICATION; LAKE POLLUTION; LAKES; METAL ANALYSIS; MODELS; NEURAL NETWORKS; NITROGEN; OIL SPILLS; PHOSPHORUS; POLLUTION; REGRESSION ANALYSIS; STATISTICS;

DISSOLVED OXYGEN;

ARTIFICIAL NEURAL NETWORK; ASSESSMENT METHOD; DISSOLVED OXYGEN; EUTROPHICATION; LAKE POLLUTION; MODELING; PREDICTION; REGRESSION ANALYSIS; WATER QUALITY;

ISTANBUL [TURKEY]; OMERLI DAM; TURKEY;

EID: 84755161811     PISSN: 09204741     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11269-010-9613-0     Document Type: Article

References (38)

1. 2) concentration levels from the Mina Al-Fahal Refinery in Oman using artificial neural networks. Am J Environ Sci 4(5): 473-481.
2. Abo-Quadis S, Alhiary A (2007) Statistical models for traffic noise at signalized intersections. Build Environ 42(8): 2939-2948.
3. Akkoyunlu A (2003) Evaluation of eutrophication process in Lake Iznik. Fresenius Environ Bull 12(12): 801-807.
4. Almasri MN, Kaluarachchi JJ (2005) Modular neural networks to predict the nitrate distribution in ground water using the on-ground nitrogen loading and recharge data. Environ Model Softw 20(7): 851-871.
5. Baykal BB, Tanik A, Gonenc IE (2000) Water quality in drinking water reservoirs of a megacity, Istanbul. Environ Manag 26(6): 607-614.
6. Chang IC, Hsiao TY (2004) Short-term model of the production of construction aggregates in Taiwan based on artificial neural networks. Environ Sci Pollut Res Int 11(2): 84-90.
7. Coskun HG, Alparslan E (2008) Environmental modelling of Omerli catchment area in Istanbul, Turkey using remote sensing and GIS techniques. Environ Monit Assess 153: 323-332.
8. Coskun HG, Tanik A, Alganci U, Cigizoglu HK (2008) Determination of environmental quality of a drinking water reservoir by remote sensing, GIS and regression analysis. Water Air Soil Pollut 194: 275-285.
9. Demuth H, Beale M (1998) Neural network toolbox. The MathWorks, Inc, Natick.
10. Domagalski J, Lin C, Luo Y, Kang J, Wang S, Brown LR, Munnc MD (2007) Eutrophication study at the Panjiakou-Daheiting reservoir system, northern Hebei Province, People's Republic of China: Chlorophyll-a model and sources of phosphorus and nitrogen. Agric Water Manag 94(1-3): 43-53.
11. Elhatip H, Hinis MA, Gulbahar N (2008) Evaluation of the water quality at Tahtali dam watershed in Izmir-Turkey by means of statistical methodology. Stoch Environ Res Risk Assess 22(3): 391-400.
12. Gumrah F, Oz B, Guler B, Evin S (2000) The application of artificial neural networks for the prediction of water quality of polluted aquifer. Water Air Soil Pollut 119(1-4): 275-294.
13. Havens KE, Fukushima T, Xie P, Iwakuma T, James RT, Takamura N, Hanazato T, Yamamoto T (2001) Nutrient dynamics and the eutrophication of shallow lakes Kasumigaura (Japan), Donghu (PR China), and Okeechobee (USA). Environ Pollut 111(2): 263-272.
14. Hinck JE, Blazer VS, Denslow ND, Myers MS, Gross TS, Tillitt DE (2007) Biomarkers of contaminant exposure in Northern Pike (Esox lucius) from the Yukon Stream basin. Alaska Arch Environ Contam Toxicol 52(4): 549-562.
15. Hutchins MG, Dilks C, Davies HN, Deflandre A (2007) Issues of diffuse pollution model complexity arising from performance benchmarking. Hydrol Earth Syst Sci 11(1): 647-662.
16. ISKI (Istanbul Water and Sewerage Authority) (2008) Omerli drinking water treatment plants. Istanbul, Turkey. http://www. iski. gov. tr. Accessed Jan 2009.
17. Karakoc G, Erkoc FU, Katircioglu H (2003) Water quality and impacts of pollution sources for Eymir and Mogan Lakes (Turkey). Environ Int 29(1): 21-27.
18. Karul C, Soyupak S, Cilesiz AF, Akbay N, Germen E (2000) Case studies on the use of neural networks in eutrophication modeling. Ecol Model 134(2): 145-152.
19. Koklu R, Sengorur B, Topal B (2009) Water quality assessment using multivariate statistical methods-a case study: Melen River system (Turkey). Water Resour Manag. doi: 10. 1007/s11269-009-9481-7.
20. Kuo YM, Liu CW, Lin KH (2004) Evaluation of the ability of an artificial neural network model to assess the variation of groundwater quality in an area of blackfoot disease in Taiwan. Water Res 38(1): 148-158.
21. Li R, Dong M, Zhao Y, Zhang L, Cui Q, He W (2007) Assessment of water quality and identification of pollution sources of plateau lakes in Yunnan (China). J Environ Qual 36: 291-297.
22. Maier HR, Dandy GC (2000) Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications. Environ Modell Softw 15(1): 101-124.
23. Manache G, Meiching CS (2004) Sensitivity analysis of a water-quality model using Latin hypercube sampling. J Water Resour Plan Manage 130(3): 232-242.
24. Markfort CD, Hondzo M (2009) Dissolved oxygen measurements in aquatic environments: the effects of changing temperature and pressure on three sensor technologies. J Environ Qual 38: 1766-1774.
25. Mitra B, Scott HD, Dixon JC, McKimmey JM (1998) Applications of fuzzy logic to the prediction of soil erosion in a large watershed. Geoderma 86(3-4): 183-209.
26. Papanastasiou DK, Melas D, Kioutsioukis I (2007) Development and assessment of neural network and multiple regression models in order to predict PM10 levels in a medium-sized Mediterranean City. Water Air Soil Pollut 182(1-4): 325-334.
27. Serengil Y, Gokbulak F, Ozhan S, Hi{dotless}zal A, Sengonul K, Balci AN, Ozyuvaci N (2007) Hydrological impacts of a slight thinning treatment in a deciduous forest ecosystem in Turkey. J Hydrol 333(2-4): 569-577.
28. Shirsath PB, Singh AK (2009) A comparative study of daily pan evaporation estimation using ANN, Regression and climate based models. Water Resour Manag. doi: 10. 1007/s11269-009-9514-2.
29. SPSS (2007) Neural networks, user's guide, version 17. 0. SPSS Inc.
30. Suen JP, Eheart JW (2003) Evaluation of neural networks for modeling nitrate concentrations in streams. J Water Resour Plan Manage 129(6): 505-510.
31. Tayfur G, Singh VP (2006) ANN and fuzzy logic models for simulating event-based rainfall-runoff. J Hydraul Eng ASCE 132(12): 1321-1330.
32. Thomas S, Jacko RB (2007) Model for forecasting expressway fine particulate matter and carbon monoxide concentration: application of regression and neural network models. J Air Waste Manage Assoc 57: 480-488.
33. Tootle GA, Singh AK, Piechota TC, Farnham I (2007) Long lead-time forecasting of U. S. streamflow using partial least squares regression. Eur J Soil Sci 12(5): 442-451.
34. Uyak V, Ozdemir K, Toroz I (2007) Multiple linear regression modeling of disinfection by-products formation in Istanbul drinking water reservoirs. Sci Total Environ 378(3): 269-280.
35. Vollenweider RA (1975) Input-output models, with special reference to the phosphorus loading concept in limnology. Schweiz Hydrol 37: 53-84.
36. Vryzas Z, Mourkidou EP, Soulios G, Prodromou K (2007) Kinetics and adsorption of metolachlor and atrazine and the conversion products (deethylatrazine, deisopropylatrazine, hydroxyatrazine) in the soil profile of a stream basin. Eur J Soil Sci 58(5): 1186-1199.
37. Welter JR, Fisher SG, Grimm NB (2005) Nitrogen transport and retention in an arid land watershed: influence of storm characteristics on terrestrial-aquatic linkages. Biogeochemistry 76(3): 421-440.
38. Xiao Y, Ferreira JG, Bricker SB, Nunes JP, Zhu M, Zhang X (2007) Trophic assessment in Chinese coastal systems-review of methods and application to the Changjiang (Yangtze) Estuary and Jiaozhou Bay. Estuaries Coasts 30(6): 901-918.