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Environmental Science and Pollution Research

, Volume 26, Issue 1, pp 923–937 | Cite as

Determination of biochemical oxygen demand and dissolved oxygen for semi-arid river environment: application of soft computing models

  • Hai Tao
  • Aiman M. Bobaker
  • Majeed Mattar Ramal
  • Zaher Mundher YaseenEmail author
  • Md Shabbir Hossain
  • Shamsuddin Shahid
Research Article
  • 69 Downloads

Abstract

Surface and ground water resources are highly sensitive aquatic systems to contaminants due to their accessibility to multiple-point and non-point sources of pollutions. Determination of water quality variables using mathematical models instead of laboratory experiments can have venerable significance in term of the environmental prospective. In this research, application of a new developed hybrid response surface method (HRSM) which is a modified model of the existing response surface model (RSM) is proposed for the first time to predict biochemical oxygen demand (BOD) and dissolved oxygen (DO) in Euphrates River, Iraq. The model was constructed using various physical and chemical variables including water temperature (T), turbidity, power of hydrogen (pH), electrical conductivity (EC), alkalinity, calcium (Ca), chemical oxygen demand (COD), sulfate (SO4), total dissolved solids (TDS), and total suspended solids (TSS) as input attributes. The monthly water quality sampling data for the period 2004–2013 was considered for structuring the input-output pattern required for the development of the models. An advance analysis was conducted to comprehend the correlation between the predictors and predictand. The prediction performances of HRSM were compared with that of support vector regression (SVR) model which is one of the most predominate applied machine learning approaches of the state-of-the-art for water quality prediction. The results indicated a very optimistic modeling accuracy of the proposed HRSM model to predict BOD and DO. Furthermore, the results showed a robust alternative mathematical model for determining water quality particularly in a data scarce region like Iraq.

Keywords

Water quality variables Environmental prospects Soft computing models Euphrates River 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Computer Science DepartmentBaoji University of Arts and SciencesBaojiChina
  2. 2.Chemistry Department, Faculty of ScienceUniversity of BenghaziBenghaziLibya
  3. 3.Dams and Water Resources Department, College of EngineeringUniversity Of AnbarRamadiIraq
  4. 4.Sustainable Developments in Civil Engineering Research Group, Faculty of Civil EngineeringTon Duc Thang UniversityHo Chi Minh CityVietnam
  5. 5.Institute of Energy Infrastructure, Department of Civil EngineeringUniversiti Tenaga NasionalKajangMalaysia
  6. 6.Faculty of Civil EngineeringUniversiti Teknologi MalaysiaJohor BahruMalaysia

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