Applied Chemistry for Engineering (공업화학)

The Korean Society of Industrial and Engineering Chemistry (한국공업화학회)
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Water Quality Assessment and Turbidity Prediction Using Multivariate Statistical Techniques: A Case Study of the Cheurfa Dam in Northwestern Algeria

  • ADDOUCHE, Amina (Laboratory of Advanced Materials and Physicochemistry for Environment and Health, Djillali Liabes University of Sidi Bel Abbes) ;
  • RIGHI, Ali (Laboratory of probability and statistics and stochastic processes, Djillali Liabes University of Sidi Bel Abbes) ;
  • HAMRI, Mehdi Mohamed (Computer Science Research Laboratory, Djillali Liabes University of Sidi Bel Abbes) ;
  • BENGHAREZ, Zohra (Laboratory of Advanced Materials and Physicochemistry for Environment and Health, Djillali Liabes University of Sidi Bel Abbes) ;
  • ZIZI, Zahia (Laboratory of Advanced Materials and Physicochemistry for Environment and Health, Djillali Liabes University of Sidi Bel Abbes)
  • Received : 2022.10.11
  • Accepted : 2022.11.24
  • Published : 2022.12.10
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Abstract

This work aimed to develop a new equation for turbidity (Turb) simulation and prediction using statistical methods based on principal component analysis (PCA) and multiple linear regression (MLR). For this purpose, water samples were collected monthly over a five year period from Cheurfa dam, an important reservoir in Northwestern Algeria, and analyzed for 12 parameters, including temperature (T°), pH, electrical conductivity (EC), turbidity (Turb), dissolved oxygen (DO), ammonium (NH4+), nitrate (NO3-), nitrite (NO2-), phosphate (PO43-), total suspended solids (TSS), biochemical oxygen demand (BOD5) and chemical oxygen demand (COD). The results revealed a strong mineralization of the water and low dissolved oxygen (DO) content during the summer period. High levels of TSS and Turb were recorded during rainy periods. In addition, water was charged with phosphate (PO43-) in the whole period of study. The PCA results revealed ten factors, three of which were significant (eigenvalues >1) and explained 75.5% of the total variance. The F1 and F2 factors explained 36.5% and 26.7% of the total variance, respectively and indicated anthropogenic pollution of domestic agricultural and industrial origin. The MLR turbidity simulation model exhibited a high coefficient of determination (R2 = 92.20%), indicating that 92.20% of the data variability can be explained by the model. TSS, DO, EC, NO3-, NO2-, and COD were the most significant contributing parameters (p values << 0.05) in turbidity prediction. The present study can help with decision-making on the management and monitoring of the water quality of the dam, which is the primary source of drinking water in this region.

Keywords

Acknowledgement

The authors would like to thank the Directorate General of Scientific Research and Technological Development (DGRSDT) and the Ministry of Higher Education and Scientific Research (MESRS), Algeria, for their support. Also, the authors are grateful to the staff of the National Agency for Water Resources (ANRH) and the National Agency for Dams and Transfers (ANBT) for providing some data used in this study.

References

  1. D. R. Kangabam, and M. Govindaraju, Anthropogenic activity-induced water quality degradation in the loktak lake, a ramsar site in the Indo-Burma biodiversity hotspot, Environ. Technol., 40, 1-10 (2017). https://doi.org/10.1080/09593330.2017.1375999
  2. H. Dalakoti, S. Mishra, M. Chaudhary, and S. K. Singal, Appraisal of water quality in the lakes of nainital district through numerical indices and multivariate statistics, India, Int. J. River Basin Manag., 16, 1-42 (2017). https://doi.org/10.1080/15715124.2017.1365721
  3. Y. Zhao, X. H. Xia, Z. F. Yang, and F. Wang, Assessment of water quality in baiyangdian lake using multivariate statistical techniques, Procedia Environ. Sci., 13, 1213-1226 (2012). https://doi.org/10.1016/j.proenv.2012.01.115
  4. Y. Wu and W. Yang, Indicators and implementing methods of wetland biodiversity monitoring: Taking Great Lakes Coastal Wetlands As An Example, Biodivers. Sci., 12, 527-535 (2015).
  5. D. Miljojkovic, I. Trepsic, and M. Milovancevic, Assessment of physical and chemical indicators on water Turbidity, Physica A, 527, 121-171 (2019).
  6. M. Stevenson, and C. Bravo, Advanced turbidity prediction for operational water supply planning, Decis. Support Syst., 119, 7284 (2019).
  7. A. C. Twort, D. D. Ratnayaka, and M. J. Brandt, Water Supply, 5th ed, 725, Edward Arnold Publishers and IWA Pulishing, London, UK (1994).
  8. S. M. Yidana, Groundwater classification using multivariate statistical methods: Southern Ghana, J. Afr. Earth Sci., 57, 455-469 (2010). https://doi.org/10.1016/j.jafrearsci.2009.12.002
  9. H. A. Isiyaka, A. Mustapha, H. Juahir, and P. O. Phil.Eze, Water quality modelling using artificial neural network and multivariate statistical techniques, Model. Earth Syst. Environ., 5, 583-593 (2019). https://doi.org/10.1007/s40808-018-0551-9
  10. A. K. Kadam, V. M. Wagh, A. A. Muley, and R. Sankhua, Prediction of water quality index using artificial neural network and multiple linear regression modelling approach in Shivganga river basin, India, Model. Earth Syst. Environ., 5, 951-962 (2019). https://doi.org/10.1007/s40808-019-00581-3
  11. S. Kukrer and E. Mutlu, Assessment of surface water quality using water quality index and multivariate statistical analyses in Sarayduzu dam lake, Turkey, Environ. Monit. Assess., 191, 71 (2019). https://doi.org/10.1007/s10661-019-7197-6
  12. F. Z. Merzougui, A. Makhloufi, and T. Merzougui, Hydro-chemical and microbiological characterization of lower cretaceous waters in a semi-arid zone Beni-Ounif Syncline, South-West of Algeria, J. Water Land Dev., 40, 67-80 (2019). https://doi.org/10.2478/jwld-2019-0007
  13. Z. Angello, J. Tranckner, and B. Behailu, Spatio-temporal evaluation and quantification of pollutant source contribution in little Akaki river, Ethiopia: Conjunctive application of factor analysis and multivariate receptor model, Pol. J. Environ. Stud., 30, 2334 (2020).
  14. M. Zeroual, A. Hani, and A. Boustila, Assessing domestic factors determining water consumption in a semi-arid area (Sedrata City) using artificial neural networks and principal component analysis, J. Water Land Dev., 49, 219-228 (2021).
  15. S. G. Schreiber, S. Schreiber, R. N. Tanna, D. R. Roberts, and T. J. Arciszewski, Statistical tools for water quality assessment and monitoring in river ecosystems - a scoping review and recommendations for data analysis, Water Qual. Res. J., 57, 40-57 (2022). https://doi.org/10.2166/wqrj.2022.028
  16. K. Zeinalzadeh and E. Rezaei, Determining spatial and temporal changes of surface water quality using principal component analysis, J. Hydrol. Reg. Stud., 13, 11-10 (2017). https://doi.org/10.1016/j.ejrh.2017.07.003
  17. A. Bouguerne, A. Boudoukha, A. Benkhaled and AH. Mebarkia, Assessment of surface water quality of Ain Zada dam (Algeria) using multivariate statistical techniques, Int. J. River Basin Manag., 15, 133-143 (2016).
  18. N. S. Rao, B. Sunitha, N. Adimalla, and M. Chaudhary, Quality criteria for groundwater use from a rural part of wanaparthy district, telangana state, India, through ionic spatial distribution (ISD), entropy water quality index (EWQI) and principal component analysis (PCA), Environ. Geochem. Health, 42, 579-599 (2022). https://doi.org/10.1007/s10653-019-00393-5
  19. W. Yang, Y. Zhao, D. Wang, H. Wu, A. Lin, and L. He, Using principal components analysis and IDW interpolation to determine spatial and temporal changes of surface water quality of xin'anjiang river in huangshan, china, Int. J. Environ. Res. Public Health, 17, 2942 (2020). https://doi.org/10.3390/ijerph17082942
  20. D. Beveridge, A. St-Hilaire, T. B. Ouarda, B. Khalil, F. M. Conly, L. I. Wassenaar, and E.A. Ritson-Bennett, Geostatistical approach to optimize water quality monitoring networks in large lakes: Application to lake winnipeg. J. Great Lakes Res., 38, 174-182 (2012). https://doi.org/10.1016/j.jglr.2012.01.004
  21. S. Xu, Y. Cui, C.Yang, S. Wei, W. Dong, L. Huang, C. Liu, Z. Ren, and W. Wang, The fuzzy comprehensive evaluation (FCE) and the principal component analysis (PCA) model simulation and its applications in water quality assessment of Nansi Lake Basin, China, Environ. Eng. Res., 26, 200022 (2021). https://doi.org/10.4491/eer.2020.022
  22. M. Zavareh, V. Maggioni, and V. Sokolov, Investigating water quality data using principal component analysis and granger causality, Water, 13, 343 (2021). https://doi.org/10.3390/w13030343
  23. M. Adamu and A. Ado, Application of principal component analysis & multiple regression models in surface water quality assessment, J. Environ. Earth Sci., 2, 16-23 (2012).
  24. R. Koklu, B. Sengorur, and B. Topal, Water quality assessment using multivariate statistical methods, a case study: Melen River system, Water Resour. Manag., 24, 959-978 (2012). https://doi.org/10.1007/s11269-009-9481-7
  25. B. Djelita, S. Bouzid-Lagha, and K. C. Nehar, Spatial and temporal patterns of the water quality in the Hammam Boughrara reservoir in Algeria. In P. Grammelis (ed.), Energy, Transportation and Global Warming, 635-653 Cham: Springer International Publishing., New York, USA (2016).
  26. A. A. Soltani, A. Bermad, H. Boutaghane, A. Oukil, O. Abdalla, M. Hasbaia, R. Oulebsir, S. Zeroual, and A. Lefkir, An integrated approach for assessing surface water quality: Case of Beni Haroun dam (Northeast Algeria), Environ. Monit. Assess., 192, 630 (2020). https://doi.org/10.1007/s10661-020-08572-z
  27. S. Rezak, F. Rahal, and A. Bahmani, Water quality trend analysis of Cheurfas II dam, Algeria, Revista Facultad d'Ingenieria Universidad d'Antioquia., 106, 9-24 (2021).
  28. ANBT, Detection des fuites d'eau dans les retenues des barrages. Rapport interne. Agence national des bassins et transferts, Mascara, Algerie. [Detection of water leaks in dam reservoirs. Report interne. National agency for basins and transfers, Mascara, Algeria] (2003).
  29. ABH, Cadastre hydraulique du bassin Macta, agence. Rapport technique. Agence de bassin hydrographique - Oranie - Chott Chergui, Oran, Algerie. [Hydraulic cadastre of the Macta basin, agency. Technical report. Hydrographic basin agency - Oranie - Chott Chergui, Oran, Algeria] (2010).
  30. N. Bentekhici, Y. Benkesmia, F. Berrichi, and S. A. Bellal, Evaluation des risques de la pollution des eaux et vulnerabilite de la nappe alluviale a l'aide des donnees spatiales. Cas de la plaine de Sidi Bel Abbes (Nord-Ouest Algerien). [Assessment of water pollution risks and vulnerability of the alluvial groundwater using spatial data. Case of the plain of Sidi Bel Abbes (North-West Algeria)], Revue des sciences de l'eau / J. Water Sci., 31, 43-59 (2018).
  31. J. Rodier, B. Legube and N. Merlet, L'analyse de l'eau: Controle et interpretation [Water analysis: Control and interpretation], 10th ed. Dunod, Paris (2016).
  32. G. Ioele, M. De Luca, F. Grande, G. Durante, R. Trozzo, C. Crupi, and G. Ragno, Assessment of surface water quality using multivariate analysis: Case study of the Crati river, Italy, Water, 12, 2214 (2020). https://doi.org/10.3390/w12082214
  33. X. Fan, B. Cui, H. Zhao, Z. Zhang and, H. Zhang, Assessment of river water quality in Pearl river delta using multivariate statistical techniques, Proc. Environ. Sci., 2, 1220-1234 (2010). https://doi.org/10.1016/j.proenv.2010.10.133
  34. K. E. Kouadio, N. Soro, and I. Savane, Strategie d'optimisation de la profondeur des forages en contexte de socle. Application a la region du denguele, Nord-Ouest de la Cote d'Ivoire. [Drilling depth optimization strategy in a basement context. Application to the Denguele region, North-West of Cote d'Ivoire]. Revue des Sciences de l'eau / J. Water Sci., 23, 1-15 (2010).
  35. JORA(Journal officiel de la republique Algerienne), decret executif No 11-219 Du 10 Rajab 1432 correspondant au 12 Juin 2011 fixant les objectifs de qualite des eaux superficielles et souterraines destinees a l'alimentation en eau des populations, JO No.34 (2011). [Executive decree No 11-219 of 10 Rajab 1432 corresponding to June 12, 2011 fixing the quality objectives of surface and underground waters intended for the water supply of the populations, JO No. 34 (2011)].
  36. F. Lakhili, M. Benabdelhadi, N. Bouderka, H. Lahrach, and A. Lahrach, Etude de La qualite physico-chimique et de la contamination metallique des eaux de surface du bassin versant de Beht (Maroc). [Study of the physico-chemical quality and metallic contamination of surface waters in the Beht watershed (Morocco)]. Eur. Sci. J., 11, 132-147 (2015).
  37. A. Jemali and A. Kefati, Reutilisation des eaux usees au Maroc. Forum sur la gestion de la demande en eau, direction du developpement et de la gestion d'irrigation / Madref/ Rabat. [Wastewater reuse in Morocco. Forum on water demand management, directorate of development and irrigation management / Madref/Rabat] (2002).
  38. JORA Journal officiel de la republique Algerienne, decret No.11-125 du 17 Rabie Ethani 1432 correspondant au 22 Mars 2011 relatif a la qualite de l'eau de consommation humaine, JO No. 18 (2011). [Decree No. 11-125 of 17 Rabie Ethani 1432 corresponding to March 22, 2011 on the quality of water for human consumption, JO No. 18 (2011)].
  39. S. K. Kalala, M. S. S. Christian, and M. K. Adelin, Implication des parametres Physico-chimiques sur la qualite des eaux de la riviere Lubumbashi (Pont Katuba jusqu'en aval de la riviere Kafubu) Lubumbashi, Haut- Katanga / RD Congo. [Implication of the physico-chemical parameters on the quality of the waters of the Lubumbashi River (Katuba Bridge to downstream of the Kafubu River) Lubumbashi, Upper Katanga / DR Congo], Int. J. Innovation Sci. Res., 25, 141-15 (2016).
  40. S. Hebert and S. Legare, Suivi de la qualite de l'eau des rivieres et petits cours d'eau, Direction du suivi de l'etat de l'environnement, ministere de l'environnement gouvernement du Quebec. [Monitoring the water quality of rivers and small streams, State of the environment monitoring branch, ministry of the environment government of Quebec], 5 (2020).
  41. ANRH, Etude de synthese sur les ressources en eaux de surface de l'Algerie du Nord, rapport d'etude (ANRH-GTZ), Agence Nationale des Ressources Hydrauliques. Oran, Algerie (2003). [Study of synthesis on the surface water resources of North Algeria, study report (ANRH-GTZ), National Water Resources Agency, Oran, Algeria].
  42. J. Papin, J. R. Gerard, P. Dossou-Yovo, S. F. Senou, and T. R. Moderan, Caracterisation physico-chimique et microbiologique des eaux souterraines et superficielles dans la zone de production cotonniere d'Aplahoue. [Physico-chemical and microbiological characterization of ground and surface water in the Aplahoue cotton production zone], J. Appl. Biosci., 103, 9841-9853 (2016).
  43. L. Akatumbila, M. Mabiala, A, Lubini, K. Pwema, and E. A. Musibono, Contribution a l'evaluation de la qualite physico-chimique de l'eau: Cas de la riviere urbaine Gombe de Kinshasa / republique democratique du Congo. [Contribution to the evaluation of the physical-chemical quality of water: Case of the urban river Gombe of Kinshasa / Democratic Republic of Congo], LARHYSS J., 26, 7-29 (2016).
  44. N. Allalgua, C. Kaouachi, C. Boualeg, A. Ayari, and A. Bensouileh, Caracterisation physico-chimique des eaux du barrage Foum el-Khanga (region de Souk-Ahras, Algerie). [Physico-chemical characterization of the waters of Foum El-Khanga dam (SoukAhras region, Algeria)], Eur. Sci. J. ES., 13, 258 (2017).
  45. S. Bouzid-Lagha, and B. Djelita, Etude du phenomene d'eutrophisation dans le barrage de Hammam Boughrara (Wilaya De Tlemcen, Algerie). [Study of the eutrophication phenomenon in the Hammam Boughrara dam (Wilaya De Tlemcen, Algeria)], Hydrol. Sci. J., 57, 186201 (2012).
  46. M. A. Jurado Zavaleta, M. R. Alcaraz, L. G. Penaloza, Boemo A, A. Cardozo, G. Tarcaya, S. M. Azcarate, and H. C. Goicoechea, Chemometric modeling for spatiotemporal characterization and self depuration monitoring of surface water assessing the pollution sources impact of northern Argentina rivers, Microchem. J., 162, 105-841 (2021).
  47. A. M. Ayanshola, A. A. Alao, A. W. Salami, S. O. Bilewu, A. A. Mohammed, O. O. Adeleke, and O. O. Olofintoye, Modelling of turbidity variation in a water treatment plant, Acta Technica Corviniensis - Bulletin of Engineering, 4 (2021).
  48. R. M. Amanda de Oliveira, A. C. Borges, A. T. Matos, and M. Nascimento, Estimation on the concentration of suspended solids from turbidity in the water of two sub-basins in the doce river basin, Engenharia Agricola, 38 (2018).
  49. P. J. Garcia Nieto, E. Garcia-Gonzalo, J. R. Alonso Fernandez, and C. Diaz Muniz, Hybrid PSO-SVM-based method for long-term forecasting of turbidity in the Nalon river basin: A case study in Northern Spain, Ecol. Eng., 73, 192-200 (2014). https://doi.org/10.1016/j.ecoleng.2014.09.042
  50. C. S. Lee, Y. C. Lee, and H. M. Chiang, Abrupt stSate change of river water quality (turbidity): Effect of extreme rainfalls and typhoons, Sci. Total Environ., 557, 91-101(2016). https://doi.org/10.1016/j.scitotenv.2016.02.213