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Prediction of Water Quality in Riva River Watershed Cover

Prediction of Water Quality in Riva River Watershed

Ecological Chemistry and Engineering S
Volume 26 (2019): Issue 4 (December 2019)
By: Nurtac Oz,  Bayram Topal and  Halil Ibrahim Uzun  
Open Access
|Jan 2020

References

  1. [1] Singh KP, Malik A, Sinha S. Water quality assessment and apportionment of pollution sources of Gomti river (India) using multivariate statistical techniques - a case study. Analytica Chim Acta. 2015;538(1-2):355-74. DOI: 10.1016/j.aca.2005.02.006.10.1016/j.aca.2005.02.006
    Open DOISearch in Google ScholarBack to article
  2. [2] Mishra BK, Regmi RK, Masago Y, Fukushi K, Kumar P, Saraswat C. Assessment of Bagmati river pollution in Kathmandu valley: Scenario-based modeling and analysis for sustainable urban development. Sustain Water Qual Ecol. 2017;9-10:67-77. DOI: 10.1016/j.swaqe.2017.06.001.10.1016/j.swaqe.2017.06.001
    Open DOISearch in Google ScholarBack to article
  3. [3] El-Tohamy WS, Abdel-Baki SN, Abdel-Aziz NE, Khidr AAA. Evaluation of spatial and temporal variations of surface water quality in the Nile River. Ecol Chem Eng S. 2018;25:569-80. DOI: 10.1515/eces-2018-0038.10.1515/eces-2018-0038
    Open DOISearch in Google ScholarBack to article
  4. [4] Taylor SD, He Y, Hiscock KM. Modelling the impacts of agricultural management practices on river water quality in Eastern England. J Environ Manage. 2016;180:147-63. DOI: 10.1016/j.jenvman.2016.05.002.10.1016/j.jenvman.2016.05.00227213867
    Open DOISearch in Google ScholarBack to article
  5. [5] Pirani M, Panton A, Purdie DA, Sahu SK. Modelling macronutrient dynamics in the Hampshire Avon River: A Bayasian approach to estimate seasonal variability and total flux. Sci Total Environ. 2016;572:1449-60. DOI: 10.1016/j.scitotenv.2016.04.129.10.1016/j.scitotenv.2016.04.12927179620
    Open DOISearch in Google ScholarBack to article
  6. [6] Melching CS, Liang J, Fleere L, Wethington D. Modeling the water quality impacts of the separation of the Great Lakes and Mississippi River basins for invasive species control. J Great Lakes Res. 2015;41:87-98. DOI: 10.1016/j.jglr.2014.11.009.10.1016/j.jglr.2014.11.009
    Open DOISearch in Google ScholarBack to article
  7. [7] Mainali J, Chang H. Landscape and anthropogenic factors affecting spatial patterns of water quality trends in a large river basin, South Korea. J Hydrol. 2018;564:26-40. DOI: 10.1016/j.jhydrol.2018.06.074.10.1016/j.jhydrol.2018.06.074
    Open DOISearch in Google ScholarBack to article
  8. [8] Swain R, Sahoo B. Improving river water quality monitoring using satellite data products and a genetic algorithm processing approach. Sustain Water Qual Ecol. 2017;9-10:88-114. DOI: 10.1016/j.swaqe.2017.09.001.10.1016/j.swaqe.2017.09.001
    Open DOISearch in Google ScholarBack to article
  9. [9] Shia Y, Xu G, Wang Y, Engel BA, Peng H, Zhang W, et al. Modelling hydrology and water quality processes in the Pengxi River basin of the Three Gorges Reservoir using the soil and water assessment tool. Agr Water Manage. 2017;82:24-38. DOI: 10.1016/j.agwat.2016.12.007.10.1016/j.agwat.2016.12.007
    Open DOISearch in Google ScholarBack to article
  10. [10] Decelis LDR, Igúzquiza EP, Andreo B. Spatial prediction of water quality variables along a main river channel, in presence of pollution hotspots. Sci Total Environ. 2017;605-606:276-90. DOI: 10.1016/j.scitotenv.2017.06.145.10.1016/j.scitotenv.2017.06.14528668739
    Search in Google ScholarBack to article
  11. [11] Vrebos D, Beauchard O, Meire P. The impact of land use and spatial mediated processes on the water quality in a river system. Sci Total Environ. 2017;601-602:365-73. DOI: 10.1016/j.scitotenv.2017.05.217.10.1016/j.scitotenv.2017.05.21728570971
    Open DOISearch in Google ScholarBack to article
  12. [12] Jannin LB, Brito D, Sun X, Jauch E, Neves R, Sauvage S, et al. Spatially distributed modelling of surface water - groundwater exchanges during overbank flood events - a case study at the Garonne River. Adv Water Resour. 2016;94:146-59. DOI: 10.1016/j.advwatres.2016.05.008.10.1016/j.advwatres.2016.05.008
    Open DOISearch in Google ScholarBack to article
  13. [13] Gorzel M, Kornijow R, Buczynska E. Quality of rivers: Comparison of hydro-morphological, physical-chemical and biological methods. Ecol Chem Eng S. 2018;25:101-22. DOI: 10.1515/eces-2018-0007.10.1515/eces-2018-0007
    Open DOISearch in Google ScholarBack to article
  14. [14] Wang Y, Zhang W, Zhao Y, Peng H, Shi Y. Modelling water quality and quantity with the influence of inter-basin water diversion projects and cascade reservoirs in the Middle-lower Hanjiang River. J Hydrol. 2016;541:1348-62. DOI:10.1016/j.jhydrol.2016.08.039.10.1016/j.jhydrol.2016.08.039
    Open DOISearch in Google ScholarBack to article
  15. [15] Whitehead PG, Bussi G, Bowes MJ, Read DS, Hutchins MG, Elliott JA, et al. Dynamic modelling of multiple phytoplankton groups in river with an application to the Thames river system in the UK. Environ Model Softw. 2015;74: 75-91. DOI: 10.1016/j.envsoft.2015.09.010.10.1016/j.envsoft.2015.09.010
    Open DOISearch in Google ScholarBack to article
  16. [16] Ogleni N, Topal B. Water quality assessment of the Mudurnu River, Turkey, using biotic indices. Water Resour Manage. 2011;25:2487-508. DOI: 10.1007/s11269-011-9822-1.10.1007/s11269-011-9822-1
    Open DOISearch in Google ScholarBack to article
  17. [17] Ustaoğlu F, Tepe Y. Water quality and sediment contamination assessment of Pazarsuyu Stream, Turkey using multivariate statistical methods and pollution indicators. J Soil Water Conserv. 2019;7:47-56. DOI: 10.1016/j.iswcr.2018.09.001.10.1016/j.iswcr.2018.09.001
    Open DOISearch in Google ScholarBack to article
  18. [18] Papazova P, Simeonova P. Long-term statistical assessment of the river quality of Tundja River. Ecol Chem Eng S. 2012;19:213-26. DOI: 10.2478/v10216-011-0016-9.10.2478/v10216-011-0016-9
    Open DOISearch in Google ScholarBack to article
  19. [19] Avila R, Horn B, Moriarty E, Hodson R, Moltchanova E. Evaluating statistical model performance in water quality prediction. J Environ Manage. 2018;206:910-9. DOI: 10.1016/j.jenvman.2017.11.049.10.1016/j.jenvman.2017.11.04929207304
    Open DOISearch in Google ScholarBack to article
  20. [20] Libera DA, Sankarasubramanian A. Multivariate bias corrections of mechanistic water quality model predictions. J Hydrol. 2018;564:529-41. DOI: 10.1016/j.jhydrol.2018.07.043.10.1016/j.jhydrol.2018.07.043
    Open DOISearch in Google ScholarBack to article
  21. [21] Tomas D, Čurlin M, Marić AS. Assessing the surface water status in Pannonian ecoregion by the water quality index model. Ecol Indic. 2017;79:182-90. DOI: 10.1016/j.ecolind.2017.04.033.10.1016/j.ecolind.2017.04.033
    Open DOISearch in Google ScholarBack to article
  22. [22] Mahmoodabadi M, Arshad RR. Long-term evaluation of water quality parameters of the Karoun River using a regression approach and the adaptive neuro-fuzzy inference system. Mar Pollut Bull. 2018;126:372-80. DOI: 10.1016/j.marpolbul.2017.11.051.10.1016/j.marpolbul.2017.11.05129421114
    Open DOISearch in Google ScholarBack to article
  23. [23] Kim SE, Seo IW. Artificial Neural Network ensemble modeling with conjunctive data clustering for water quality prediction in rivers. J Hydro-Environ Res. 2015;9:3325-39. DOI: 10.1016/j.jher.2014.09.006.10.1016/j.jher.2014.09.006
    Open DOISearch in Google ScholarBack to article
  24. [24] Turkish Standards Institution (TSE), (1989). Water Quality - Total Solids Determination. TS 7093, 4. Ankara. https://en.tse.org.tr.
    Search in Google ScholarBack to article
  25. [25] APWA, AWWA, WEF, Standard Methods for the Examination of Water and Wastewater. 21th Ed. Washington, DC: American Public Health Association; 2005. ISBN: 0875530478.
    Search in Google ScholarBack to article
  26. [26] Arora S, Keshari AK. Estimation of re-aeration coefficient using MLR for modelling water quality of rivers in urban environment. Groundwater Sustainable Dev. 2018;7:430-5. DOI: 10.1016/j.gsd.2017.11.006.10.1016/j.gsd.2017.11.006
    Open DOISearch in Google ScholarBack to article
  27. [27] Wu Z, Wang X, Chen Y, Cai Y, Deng J. Assessing river water quality using water quality index in Lake Taihu Basin, China. Sci Total Environ. 2018;612:914-22. DOI: 10.1016/j.scitotenv.2017.08.293.10.1016/j.scitotenv.2017.08.29328886543
    Open DOISearch in Google ScholarBack to article
  28. [28] Ewaid SH, Abed SA, Kadhum SA. Predicting the Tigris River water quality within Baghdad, Iraq by using water quality index and regression analysis. Environ Technol Innov. 2018;11:390-8. DOI: 10.1016/j.eti.2018.06.013.10.1016/j.eti.2018.06.013
    Search in Google ScholarBack to article
  29. [29] Cui F, Park C, Kim M. Application of curve-fitting techniques to develop numerical calibration procedures for a river water quality model. J Environ Manage. 2019;1:109375. DOI:10.1016/j.jenvman.2019.109375.10.1016/j.jenvman.2019.10937531408815
    Search in Google ScholarBack to article
  30. [30] Kim HG, Hong S, Jeong KS, Kim DK, Joo GJ. Determination of sensitive variable regardless of hydrological alteration in artificial neural network model of chlorophyll a: Case study of Nakdong River. Ecol Modell. 2019;398:67-76. DOI: 10.1016/j.ecolmodel.2019.02.003.10.1016/j.ecolmodel.2019.02.003
    Open DOISearch in Google ScholarBack to article
  31. [31] Singh KP, Basant A, Malik A, Jain G. Artificial neural network modeling of the river water quality - A case study. Ecol Modell. 2009;6:888-95. DOI:10.1016/j.ecolmodel.2009.01.004.10.1016/j.ecolmodel.2009.01.004
    Open DOISearch in Google ScholarBack to article
  32. [32] Rokach L, Maimon O. Data Mining With Decision Trees Theory and Applications. Danvers USA: World Scientific Publishing Co. Pte. Ltd; 2008. ISBN: 9789812771711.10.1142/6604
    Search in Google ScholarBack to article
  33. [33] Everaert G, Bennetsen E, Goethals PLM. An applicability index for reliable and applicable decision trees in water quality modelling. Ecol Inf. 2016;32:1-6. DOI: 10.1016/j.ecoinf.2015.12.004.10.1016/j.ecoinf.2015.12.004
    Open DOISearch in Google ScholarBack to article
  34. [34] Bostanmaneshrad F, Partani S, Noori R, Nachtnebel HP, Berndtsson R, Adamowski JF. Relationship between water quality and macro-scale parameters (landuse, erosion, geology, and population density) in the Siminehrood River Basin. Sci Total Environ. 2018;639:1588-600. DOI: 10.1016/j.scitotenv.2018.05.244.10.1016/j.scitotenv.2018.05.24429929321
    Open DOISearch in Google ScholarBack to article
DOI: https://doi.org/10.1515/eces-2019-0051 | Journal eISSN: 2084-4549 | Journal ISSN: 1898-6196
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Language: English
Page range: 727 - 742
Published on: Jan 21, 2020
Published by: Society of Ecological Chemistry and Engineering
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Riva river,
water quality,
artificial neural network (),
decision tree,
regression models
Related subjects:
Chemistry,
Sustainable and green chemistry,
Engineering,
Electrical engineering,
Energy engineering,
Life sciences,
Ecology

© 2020 Nurtac Oz, Bayram Topal, Halil Ibrahim Uzun, published by Society of Ecological Chemistry and Engineering
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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