American Journal of Environmental Protection
ISSN (Print): 2328-7241 ISSN (Online): 2328-7233 Website: Editor-in-chief: Mohsen Saeedi, Hyo Choi
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American Journal of Environmental Protection. 2018, 6(1), 1-9
DOI: 10.12691/env-6-1-1
Open AccessArticle

Monitoring and Modeling of Chlorophyll-a Dynamics in a Eutrophic Lake: M'koa Lake (Jacqueville, Ivory Coast)

Yapo Habib Kpidi1, Adele Salomão-Oliveira2, , Helyde Albuquerque Marinho3, Ossey Bernard Yapo1, 4, Mamadou Guy-Richard Koné5, , Gabaze André Gadji1, Agness Essoh Jean Eudes Yves Gnagne1, Jean Stéphane N’dri5 and Nahossé Ziao5

1Laboratoire des Sciences de l’Environnement (LSE), (UFR-SGE), Université Nangui Abrogoua, 02 BP 801 Abidjan 02 - Côte-d’Ivoire

2Department in Food Science, Universidade Federal do Amazonas (UFAM), Manaus-AM, Brazil

3Department of Research, Society and Health, Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus-AM, Brazil

4Laboratoire Central de l’Environnement du Centre Ivoirien Anti-pollution (LCE-CIAPOL)

5Laboratoire de Thermodynamique et Physico-chimie du Milieu (LTPCM), (UFR-SFA), Université Nangui Abrogoua, 02 BP 801 Abidjan 02 - Côte-d’Ivoire

Pub. Date: January 09, 2018

Cite this paper:
Yapo Habib Kpidi, Adele Salomão-Oliveira, Helyde Albuquerque Marinho, Ossey Bernard Yapo, Mamadou Guy-Richard Koné, Gabaze André Gadji, Agness Essoh Jean Eudes Yves Gnagne, Jean Stéphane N’dri and Nahossé Ziao. Monitoring and Modeling of Chlorophyll-a Dynamics in a Eutrophic Lake: M'koa Lake (Jacqueville, Ivory Coast). American Journal of Environmental Protection. 2018; 6(1):1-9. doi: 10.12691/env-6-1-1


In-situ measurements and physico-chemical analyzes of thirty (30) samples taken bimonthly from August 2015 to December 2016 on six (6) stations of Lake M'koa were carried out. A modeling study was made in order to determine a quantitative and qualitative relationship between chlorophyll-a and five physico-chemical descriptors (temperature, turbidity, oxidative power (RH), nitrate ions (NO3-) and nitrite (NO2-)). These descriptors constituted the explanatory and predictive parameters of chlorophyll-a of samples taken from Lake M'koa. This study was carried out by using Principal Component Analysis (PCA), Ascending Hierarchical Classification (AHC), Multiple Linear Regression (RML) and Nonlinear (RMNL) methods. Two quantitative and qualitative linear and nonlinear models (RML and RMNL) have been proposed. These accredited models as good statistical indicators have been validated according to the rules established by the Organization of Economic Cooperation and Development (OECD). Statistical indicators of RMNL reveal more efficient predictions with R2 = 0.942, RMSE = 0.049 and F = 291.986. The obtained results suggest that the combination of these five descriptors could be useful in predicting the property of chlorophyll-a. In addition, turbidity is the first most important descriptor for the prediction of chlorophyll-a at the M'koa Lake different stations.

Eutrophication chlorophyll-a Quantitative Structure-Property Relationship (QSPR) physico-chemical descriptors

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[1]  Zalewski M., Guidelines for the Integrated Management of the Watersheds. Phytotechnoloy and Ecohydrology, Newletter and Technical Publications. Freshwater Management Series, UNEP, (2002), 5, 237.
[2]  Fu F., Dionysiou D. D., Liu H.. The use of zero-valent iron for groundwater remediation and wastewater treatment: A review. J. Hazard. Mater, (2014), 267, 194-205.
[3]  Horn, A.L.; Rueda, F. J.; Hormann, G.; Fohrer, N., Implementing river water quality modelling issues in mesoscale watershed models for water policy demands-An overview on current concepts, deficits, and future tasks. Phys. Chem. Earth, (2004), 29, 725-737.
[4]  Montgomery M. A., Elimelech M., Water and sanitation in developing countries: Including health in the equation. Environmental Science & Technology, (2007), 41, 17-24.
[5]  Organization, W.H. Water, sanitation and hygiene links to health facts and figures-updated. November 2004, (2010), Geneva.
[6]  Sheela A. M., Letha J. & Sabu J. Environmental status of a tropical lake system. Environ Monit Assess, (2011), 180, 427-449.
[7]  Abell J. M., Ozkundakci D. & Hamilton D. P., Nitrogen and phosphorus limitation of phytoplankton growth in New Zealand Lakes: Implications for eutrophication control. Ecosystems, (2010), 13, 966-977.
[8]  Coulibaly-Kalpy, J., Soumahoro, M-K., Niamien-Ebrotié, J. E., Yéo, K., Amon, L., Djaman, A. J. & Dosso, M., Déterminisme de la prolifération de la prolifération des cyanobactéries toxiques en Côte-d’Ivoire. Int. J. Biol. Chem. Sci., (2017), 11, 266-274.
[9]  Hadj, A. R., Quaranta, G., Gueddari, F., Million, D. & Clauer, N., The life cycle impact assessment applied to a coastal lagoon: the case of the Slimane lagoon (Tunisia) by the study of seasonal variations of aquatic eutrophication potential. Environmental Geology, (2008), 54, 1103-1110.
[10]  Kpidi, Y. H., Yapo, O. B., Ohou-Yao, M.-J., Ballet, T. G., Variabilité journalière de la qualité physico-chimique du lac M’koa de Jacqueville (Côte d’Ivoire). Int. J. Biol. Chem. Sci., (2017), 11, 901-910.
[11]  N’Guessan, K. A., Konan, K. F., Kotchi, Y. B., Edia, O. E., Gnagne, T., Traoré, K. S. & Houenou, V. P., Prospects for rehabilitation of man-made lake system of Yamoussoukro (Ivory Coast). Procedia Environmental Sciences, (2011), 9, 140-147.
[12]  Grizzetti, B., Bouraoui, F., Billen G., van Grinsven H. J. M., Cardoso A. C., Thieu V., Garnier J., Curtis C., Howarth R. W. & Jones P., Nitrogen as a threat to European water quality. In: "European nitrogen assessment" (Sutton M. A., Howard C. M., Erisman J. W., Billen G., Bleeker A., Grennfelt P., Van Grinsven H. J. M., & Grizzetti B., eds.). Cambridge University Press, (2011), 379-404.
[13]  Neal, C., The potential for phosphorus pollution remediation by calcite precipitation in UK freshwaters. Hydrology and Earth System Sciences, (2001), 5, 119-131.
[14]  Villeneuve V., Légaré S., Painchaud J. & Warwick V., Dynamique et modélisation de l’oxygène dissous en rivière. Revue des Sciences de l’Eau, (2006), 19, 259-274.
[15]  Nechad B., Ruddick K. G. & Neukermans G., Calibration and Validation of a Generic Multisensor Algorithm for Mapping of Turbidity in Coastal Waters. SPIE European International Symposium on Remote Sensing, Berlin. (2009).
[16]  Raihan, A., Mehebub, S., Haroon, S., Preparing turbidity and aquatic vegetation inventory for waterlogged wetlands in Lower Barpani sub-watersheds (Assam), India using geospatial technology, The Egyptian Journal of Remote Sensing and Space Sciences, Egypt. J. Remote Sensing Space Sci. (2016), pp (1-7).
[17]  Wang, Q. H., Yu, L. J., Liu Y., Lin L., Lu R., Zhu J. p., He L. & Lu Z. L., Methods for the detection and determination of nitrite and nitrate: A review. Talanta, (2017), 165, 709-720.
[18]  Zhang J., Yang C., Wang X. & Yang X., Colorimetric recognition and sensing of nitrite with unmodified gold nanoparticles based on a specific diazo reaction with phenylenediamin. Analyst, (2012), 137, 3286-3292.
[19]  Rejset, F., Analyse des eaux: aspects réglementaires et techniques. Centre Régional de documentation pédagogique d’Aquitaine. (2002):
[20]  Microsoft ® Excel ® 2013 (15.0.4420.1017) MSO (15.0.4420.1017) 64 Bits Partie de Microsoft Office Professionnel Plus. (2013).
[21]  XLSTAT Version 2014.5.03 Copyright Addinsoft 1995-2014; XLSTAT and Addinsoft are Registered Trademarks of Addinsoft. (2014).
[22]  Chaltterjee, S., Hadi, A. and Price, B., Regression Analysis by Examples. Wiley VCH, New York. (2000)
[23]  Phuong, H.T.N., Synthèse et étude des relations structure/activité quantitatives (QSAR/2D) d’analogues Benzo [c] phénanthridiniques. Thèse de doctorat, Université d’Angers (2007).
[24]  Snedecor, G. W. & Cochran, W. G., Statistical Methods. Oxford and IBH, New Delhi, India, (1967). 381.
[25]  Diudea, M. V., QSPR/QSAR Studies for Molecular Descriptors. Nova Science: Huntingdon, New York, (2000).
[26]  Esposito, E.X., Hopfinger, A.J. and Madura, J. D., Methods for Applying the Quantitative Structure-Activity Relationship Paradigm. Methods in Molecular Biology, (2004), 275,131-213.
[27]  Clarke, K. R. & Ainsworth, M., A method of linking multivariate community structure to environmental variables. Marine Ecology, (1993), 92, 205-219.
[28]  Escofier, B. & Pagès, J., Analyses factorielles simples et multiples: Objectifs, méthodes et interprétation. Dunod, Paris, (2008), 318.
[29]  Rücker C. & Rücker G. J. (2007). Y-Randomization is a tool used in validation of QSPR/QSAR models. Chem. Inf. Model, 47, 2345-2357.
[30]  Eriksson, L., Jaworska J., Worth A., Cronin M.T. D., Dowell R. M. Mc & Gramatica P., Methods for Reliability and Uncertainty Assessment and for Applicability Evaluations of Classification and Regression-Based QSARs. Environmental Health Perspectives, (2003), 111, 1361-1375.
[31]  Golbraikh A., Tropsha A., Beware of qsar. J. Mol. Graph. Model, (2002), 20, 269-276.
[32]  Tropsha, A., Best practices for QSAR model development, validation, and exploitation. Molecular Informatics, (2010), 29, 476-488.
[33]  Tropsha, A. Gramatica, P. & Gombar V. K., The importance of being earnest, validation is the absolute essential for successful application and interpretation of QSPR models. QSAR Comb. Sci., (2003), 22, 69-77.
[34]  Roy, P. P. & Roy, K.. On some aspects of variable selection for partial least squares regression models. QSAR Comb Sci., (2008), 27, 302-313.