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Development of a Groundwater Quality Prediction Model for the M'pody Village of Anyama

Received: 22 September 2022     Accepted: 7 November 2022     Published: 16 November 2022
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Abstract

Context: In the village of M'pody in the Anyama district, located about 60 kilometers from the town of Anyama, a diarrhea epidemic was detected in January 2020 and affected 69 people, mostly children aged 0 to 5 years. According to the affected population, these cases of diarrhea were related to the consumption of water from the improved village water system, which had not been maintained for nearly three years. The objective of this work was to develop a bacteriological characterization model of the water table in the village of M'pody (Ivory coast) based on physicochemical parameters and meteorology in order to estimate the concentration of indicator germs of fecal pollution (Escherichia coli) by well. Methods: The methodology consisted of four water sampling campaigns per well during the year's four seasons on all 72 wells in this region, for a total of 288 visits. Conventional physico-chemical parameters were determined using electrochemical and spectrophotometric methods. Bacteriological parameters were determined by the membrane filtration technique. A sanitary inspection was also carried out. The development of the prediction model for the Escherichia coli indicator was performed using a linear mixed model. The performance of our model was evaluated by bootstrap and k-fold cross-validation techniques. Results: The mixed linear model with random intercept (log transformation) chosen following the spaghetti plot and likelihood ratio test gave the following results: The predictive model explained 30,24% of the variance in Escherichia coli concentrations (log transformation). It is based on 9 variables. Validation of the model performance by bootstrap gave us a very low relative bias < 5%, average prediction errors (RMSE) and absolute prediction errors per K-fold lower than 2,5. Conclusion: The development of the statistical model for predicting concentrations of fecal pollution indicator bacteria in wells was made possible by the existence of reliable databases. These databases made it possible to use 9 explanatory variables in a scientific approach to explaining the variable explained Escherichia coli. The validation of the predictive performances by K-fold and bootstrap showed that the model predictions are accurate and the bootstrap estimates of the parameters are unbiased. This implemented model could be used in the event of a declaration of waterborne diseases in this locality before the results of the microbiological analysis are returned.

Published in American Journal of Biological and Environmental Statistics (Volume 8, Issue 4)
DOI 10.11648/j.ajbes.20220804.12
Page(s) 102-111
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Mixed Linear Model, Bootstrap, Principal Component Analysis

References
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Cite This Article
  • APA Style

    Meless Djedjro Franck-Renaud, Gbagbo Tchape Aubin, Kpaibe Sawa Andre Philippe, Yapo Toussaint Wolfgang, Kouassi-Agbessi Therese Brah, et al. (2022). Development of a Groundwater Quality Prediction Model for the M'pody Village of Anyama. American Journal of Biological and Environmental Statistics, 8(4), 102-111. https://doi.org/10.11648/j.ajbes.20220804.12

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    ACS Style

    Meless Djedjro Franck-Renaud; Gbagbo Tchape Aubin; Kpaibe Sawa Andre Philippe; Yapo Toussaint Wolfgang; Kouassi-Agbessi Therese Brah, et al. Development of a Groundwater Quality Prediction Model for the M'pody Village of Anyama. Am. J. Biol. Environ. Stat. 2022, 8(4), 102-111. doi: 10.11648/j.ajbes.20220804.12

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    AMA Style

    Meless Djedjro Franck-Renaud, Gbagbo Tchape Aubin, Kpaibe Sawa Andre Philippe, Yapo Toussaint Wolfgang, Kouassi-Agbessi Therese Brah, et al. Development of a Groundwater Quality Prediction Model for the M'pody Village of Anyama. Am J Biol Environ Stat. 2022;8(4):102-111. doi: 10.11648/j.ajbes.20220804.12

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  • @article{10.11648/j.ajbes.20220804.12,
      author = {Meless Djedjro Franck-Renaud and Gbagbo Tchape Aubin and Kpaibe Sawa Andre Philippe and Yapo Toussaint Wolfgang and Kouassi-Agbessi Therese Brah and Amin N’cho Christophe},
      title = {Development of a Groundwater Quality Prediction Model for the M'pody Village of Anyama},
      journal = {American Journal of Biological and Environmental Statistics},
      volume = {8},
      number = {4},
      pages = {102-111},
      doi = {10.11648/j.ajbes.20220804.12},
      url = {https://doi.org/10.11648/j.ajbes.20220804.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbes.20220804.12},
      abstract = {Context: In the village of M'pody in the Anyama district, located about 60 kilometers from the town of Anyama, a diarrhea epidemic was detected in January 2020 and affected 69 people, mostly children aged 0 to 5 years. According to the affected population, these cases of diarrhea were related to the consumption of water from the improved village water system, which had not been maintained for nearly three years. The objective of this work was to develop a bacteriological characterization model of the water table in the village of M'pody (Ivory coast) based on physicochemical parameters and meteorology in order to estimate the concentration of indicator germs of fecal pollution (Escherichia coli) by well. Methods: The methodology consisted of four water sampling campaigns per well during the year's four seasons on all 72 wells in this region, for a total of 288 visits. Conventional physico-chemical parameters were determined using electrochemical and spectrophotometric methods. Bacteriological parameters were determined by the membrane filtration technique. A sanitary inspection was also carried out. The development of the prediction model for the Escherichia coli indicator was performed using a linear mixed model. The performance of our model was evaluated by bootstrap and k-fold cross-validation techniques. Results: The mixed linear model with random intercept (log transformation) chosen following the spaghetti plot and likelihood ratio test gave the following results: The predictive model explained 30,24% of the variance in Escherichia coli concentrations (log transformation). It is based on 9 variables. Validation of the model performance by bootstrap gave us a very low relative bias Conclusion: The development of the statistical model for predicting concentrations of fecal pollution indicator bacteria in wells was made possible by the existence of reliable databases. These databases made it possible to use 9 explanatory variables in a scientific approach to explaining the variable explained Escherichia coli. The validation of the predictive performances by K-fold and bootstrap showed that the model predictions are accurate and the bootstrap estimates of the parameters are unbiased. This implemented model could be used in the event of a declaration of waterborne diseases in this locality before the results of the microbiological analysis are returned.},
     year = {2022}
    }
    

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  • TY  - JOUR
    T1  - Development of a Groundwater Quality Prediction Model for the M'pody Village of Anyama
    AU  - Meless Djedjro Franck-Renaud
    AU  - Gbagbo Tchape Aubin
    AU  - Kpaibe Sawa Andre Philippe
    AU  - Yapo Toussaint Wolfgang
    AU  - Kouassi-Agbessi Therese Brah
    AU  - Amin N’cho Christophe
    Y1  - 2022/11/16
    PY  - 2022
    N1  - https://doi.org/10.11648/j.ajbes.20220804.12
    DO  - 10.11648/j.ajbes.20220804.12
    T2  - American Journal of Biological and Environmental Statistics
    JF  - American Journal of Biological and Environmental Statistics
    JO  - American Journal of Biological and Environmental Statistics
    SP  - 102
    EP  - 111
    PB  - Science Publishing Group
    SN  - 2471-979X
    UR  - https://doi.org/10.11648/j.ajbes.20220804.12
    AB  - Context: In the village of M'pody in the Anyama district, located about 60 kilometers from the town of Anyama, a diarrhea epidemic was detected in January 2020 and affected 69 people, mostly children aged 0 to 5 years. According to the affected population, these cases of diarrhea were related to the consumption of water from the improved village water system, which had not been maintained for nearly three years. The objective of this work was to develop a bacteriological characterization model of the water table in the village of M'pody (Ivory coast) based on physicochemical parameters and meteorology in order to estimate the concentration of indicator germs of fecal pollution (Escherichia coli) by well. Methods: The methodology consisted of four water sampling campaigns per well during the year's four seasons on all 72 wells in this region, for a total of 288 visits. Conventional physico-chemical parameters were determined using electrochemical and spectrophotometric methods. Bacteriological parameters were determined by the membrane filtration technique. A sanitary inspection was also carried out. The development of the prediction model for the Escherichia coli indicator was performed using a linear mixed model. The performance of our model was evaluated by bootstrap and k-fold cross-validation techniques. Results: The mixed linear model with random intercept (log transformation) chosen following the spaghetti plot and likelihood ratio test gave the following results: The predictive model explained 30,24% of the variance in Escherichia coli concentrations (log transformation). It is based on 9 variables. Validation of the model performance by bootstrap gave us a very low relative bias Conclusion: The development of the statistical model for predicting concentrations of fecal pollution indicator bacteria in wells was made possible by the existence of reliable databases. These databases made it possible to use 9 explanatory variables in a scientific approach to explaining the variable explained Escherichia coli. The validation of the predictive performances by K-fold and bootstrap showed that the model predictions are accurate and the bootstrap estimates of the parameters are unbiased. This implemented model could be used in the event of a declaration of waterborne diseases in this locality before the results of the microbiological analysis are returned.
    VL  - 8
    IS  - 4
    ER  - 

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Author Information
  • National Institute of Public Hygiene, Abidjan, Ivory Coast

  • National Institute of Public Hygiene, Abidjan, Ivory Coast

  • National Institute of Public Hygiene, Abidjan, Ivory Coast

  • National Institute of Public Hygiene, Abidjan, Ivory Coast

  • National Institute of Public Hygiene, Abidjan, Ivory Coast

  • National Institute of Public Hygiene, Abidjan, Ivory Coast

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