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An Approach to Reaeration Coefficient Modeling in Local Surface Water Quality Monitoring

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Abstract

Reaeration coefficient (k 2) for River Atuwara, Ogun State, Nigeria was calculated from dissolved oxygen and biochemical oxygen demand data collected over period of 3 months covering the two prevailing climatic seasons in the country. Both the Akaike and Bayesian information criteria were used in the selection and analysis of ten models to identify the most suitable reaeration coefficient (k 2) model for Atuwara River. Models that passed the confidence limit were subjected to model evaluation using measures of agreement between observed and predicted data such as percent bias, Nash–Sutcliffe efficiency, and root mean square observation standard deviation ratio. The used approach yield better results than empirical models developed for local conditions while it is also useful in conserving scarce resources.

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Acknowledgments

This research was supported by the International Foundation for Science (IFS), Stockholm, Sweden, through a grant (IFS Ref: W/4852-1) to D.O. Omole. Our gratitude also goes to Covenant University, Ota and University of Lagos, for the use of their facilities during the course of the research.

Author information

Authors and Affiliations

  1. Department of Civil Engineering, College of Science and Technology, Covenant University, Canaanland, Ota, Nigeria

    D. O. Omole

  2. Department of Civil and Environmental Engineering, University of Lagos, Lagos, Nigeria

    E. O. Longe

  3. Department of Computer and Information Systems, College of Science and Technology, Covenant University, Canaanland, Ota, Nigeria

    A. G. Musa

Authors
  1. D. O. Omole
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  2. E. O. Longe
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  3. A. G. Musa
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Corresponding author

Correspondence to D. O. Omole.

Appendix: Data Structure and Algorithm

Appendix: Data Structure and Algorithm

Data structure:

  1. 1.

    Stat: array of records: Each record has 11 fields. Each field is a float

    Fields in a record: ICvalue, Relative_Likelihood, Relative_Likelihood_wi, Confidence, SigmaSquared, NSE, RMSE, PBIAS, RSR, PBIAS_Acceptable, NSE_Acceptable

  2. 2.

    Model_Type: array of strings. Model name is a string

  3. 3.

    Dataset_Results: array of records: Each record has four fields

    Fields in a record: Confidence_Value—array of integer, FinalModel—integer

    FinalModel_Freq—integer, CountFlag—boolean

Algorithm

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Omole, D.O., Longe, E.O. & Musa, A.G. An Approach to Reaeration Coefficient Modeling in Local Surface Water Quality Monitoring. Environ Model Assess 18, 85–94 (2013). https://doi.org/10.1007/s10666-012-9328-0

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  • DOI: https://doi.org/10.1007/s10666-012-9328-0

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