Abstract
Rivers are dynamic systems in complex interactions with their surrounding environments. Reliable and fast interpretation of water quality is therefore needed for sustainable river management. Unfortunately, water quality and environmental status interactions have not yet been documented sufficiently in West–Africa. This study explored the spatial–latitudinal and seasonal features of water quality along the Sô River Basin (SRB, West Africa) using self-organizing map (SOM) and principal component analysis. Twenty-two water quality variables were measured in the surface layer at 12 different sampling sites during a twenty-four-month period from July 2016 to June 2018. The results revealed three water quality groups, following an upstream-downstream pollution gradient: (1) upstream and middle reach sites with high dissolved oxygen and Secchi disk depth values, which are more suitable for the aquatic biota; (2) downstream sites with high concentrations of ammonium, biochemical oxygen demand, and heavy metals especially in flood period, reflecting both high organic and heavy metal pollution; and (3) brackish downstream sites characterized by less heavy metal and organic pollutions. No significant variation was observed between seasons. However, the SRB relatively suffered from higher risks of heavy metal contamination and organic pollution in wet seasons. Although hydroclimatic processes affect the water quality, anthropogenic inputs of point and non-point sources were identified and discussed as a more prominent factor contributing to variation in the water quality condition. These results offer insights into the water quality dynamics in river–estuary system as well as potential pollution sources, crucial for defining sanitation, and management measures.
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The datasets used and/or analysed in the current study are available on reasonable request from the corresponding author.
References
Aboelnour M, Gitau MW, Engel BA (2020) A comparison of streamflow and baseflow responses to land-use change and the variation in climate parameters using SWAT. Water (Basel) 12:191. https://doi.org/10.3390/w12010191
Aguirre BP, Masachessi G, Ferreyra LJ et al (2019) Searching variables to assess recreational water quality: the presence of infectious human enterovirus and its correlation with the main variables of water pollution by multivariate statistical approach in Córdoba, Argentina. Environ Sci Pollut Res 26:6586–6601. https://doi.org/10.1007/s11356-019-04124-2
Alvarez-Guerra M, González-Piñuela C, Andrés A et al (2008) Assessment of Self-Organizing Map artificial neural networks for the classification of sediment quality. Environ Int 34:782–790. https://doi.org/10.1016/j.envint.2008.01.006
Aniyikaiye TE, Oluseyi T, Odiyo JO, Edokpayi JN (2019) Physico-chemical analysis of wastewater discharge from selected paint industries in Lagos, Nigeria. Int J Environ Res Public Health 16:1235. https://doi.org/10.3390/ijerph16071235
Baudoin MA, Sanchez AC, Fandohan B (2014) Small scale farmers’ vulnerability to climatic changes in southern Benin: the importance of farmers’ perceptions of existing institutions. Mitig Adapt Strateg Glob Chang 19:1195–1207. https://doi.org/10.1007/s11027-013-9468-9
Berrada M, El Hmaidi A, Monyr N et al (2016) Self-organizing map for the detection of seasonal variations in Sidi Chahed Dam sediments (Northern Morocco). Hydrol Sci J 61:628–635. https://doi.org/10.1080/02626667.2014.964717
Calamari D, Naeve H (1994) Revue de la pollution dans l’environnement aquatique africain. FAO, Rome
Céréghino R, Park Y-S (2009) Review of the Self-Organizing Map (SOM) approach in water resources: commentary. Environ Model Softw 24:945–947. https://doi.org/10.1016/j.envsoft.2009.01.008
Chea R, Grenouillet G, Lek S (2016) Evidence of water quality degradation in lower Mekong basin revealed by Self-Organizing Map. PLoS One 11:e0145527. https://doi.org/10.1371/journal.pone.0145527
Cruz MAS, Gonçalves AD, de Aragão R, de Amorim JR et al (2019) Spatial and seasonal variability of the water quality characteristics of a river in Northeast Brazil. Environ Earth Sci 78:68. https://doi.org/10.1007/s12665-019-8087-5
Dai L, Wang L, Li L et al (2018) Multivariate geostatistical analysis and source identification of heavy metals in the sediment of Poyang Lake in China. Sci Total Environ 621:1433–1444. https://doi.org/10.1016/j.scitotenv.2017.10.085
Derek A, Wheeler P (2020) Package ‘FSA’: simple fisheries stock assessment methods. R package version 0.8.30. https://www.rdocumentation.org/packages/FSA/versions/0.8.30
Djihouessi MB, Aina MP (2018) A review of hydrodynamics and water quality of Lake Nokoué: current state of knowledge and prospects for further research. Reg Stud Mar Sci 18:57–67. https://doi.org/10.1016/j.rsma.2018.01.002
Dobson M, Frid C (2009) Ecology of Aquatic Systems, 2nd edn. Oxford University Press, Oxford
Dovonou F, Aina M, Boukari M, Alassane A (2011) Pollution physico-chimique et bactériologique d’un écosystème aquatique et ses risques écotoxicologiques: cas du lac Nokoue au Sud Benin. Int J Biol Chem Sci 5:1590–1602. https://doi.org/10.4314/ijbcs.v5i4.23
Fajemila OT, Sariaslan N, Langer MR (2020) Spatial distribution of benthic foraminifera in the Lagos Lagoon (Nigeria): tracing the impact of environmental perturbations. PLoS One 15:e0243481. https://doi.org/10.1371/journal.pone.0243481
Frid C, Dobson M (2013) Ecology of aquatic management, 2nd edn. Oxford University Press, Oxford
Gnohossou PM (2006) La faune benthique d’une lagune ouest africaine (le lac Nokoue au Benin), diversité, abondance, variations temporelles et spatiales, place dans la chaine trophique. PhD thesis. Institut National Polytechnique de Toulouse, France
Gu Q, Hu H, Ma L et al (2019) Characterizing the spatial variations of the relationship between land use and surface water quality using self-organizing map approach. Ecol Indic 102:633–643. https://doi.org/10.1016/j.ecolind.2019.03.017
Guo C, Chen Y, Xia W et al (2020) Eutrophication and heavy metal pollution patterns in the water suppling lakes of China’s south-to-north water diversion project. Sci Total Environ 711:134543. https://doi.org/10.1016/j.scitotenv.2019.134543
Haselbeck V, Kordilla J, Krause F, Sauter M (2019) Self-organizing maps for the identification of groundwater salinity sources based on hydrochemical data. J Hydrol 576:610–619. https://doi.org/10.1016/j.jhydrol.2019.06.053
Hazoume RUS (2018) Diversité, organisation trophique et exploitation des poissons de la rivière Sô au Benin (Afrique de l’Ouest). PhD Thesis. Université d’Abomey-Calavi, Bénin
Hong H, Zhang Z, Guo A et al (2020) Radial basis function artificial neural network (RBF ANN) as well as the hybrid method of RBF ANN and grey relational analysis able to well predict trihalomethanes levels in tap water. J Hydrol 591:125574. https://doi.org/10.1016/j.jhydrol.2020.125574
Hounsou MB, Ahamide B, Agbossou EK, Gaiser T (2011) Evaluation of water quality in the Ouémé River (Bénin). Environmentalist 31:407–415. https://doi.org/10.1007/s10669-011-9356-3
Husson F, Josse J, Le S, Mazet J (2020) Package “FactoMineR”: multivariate exploratory data analysis and data mining. R package version 2.3. https://cran.microsoft.com/snapshot/2020-04-13/web/packages/FactoMineR/index.html
Ibikounlé M, Gbédjissi LG, Ogouyèmi-Hounto A et al (2014) Schistosomose et géohelminthoses dans le nord-est du Bénin: cas des écoliers des communes de Nikki et de Pèrèrè. Bull de la Société de Pathologie Exotique 107:171–176. https://doi.org/10.1007/s13149-014-0344-y
ISO 5667-5 (2006) Water quality — Sampling — Part 5: Guidance on sampling of drinking water from treatment works and piped distribution systems. https://www.iso.org/standard/36694.html
ISO 5667-6 (2014) Water quality — Sampling — Part 6: Guidance on sampling of rivers and streams. https://www.iso.org/standard/55451.html
IUCN-PACO (2018) Partnership for Environmental Governance in West Africa. West Africa Water Resources Policy (WAWRP), Burkina Faso
Jaji MO, Bamgbose O, Odukoya OO (2007) Water quality assessment of Ogun river, South West Nigeria. Environ Monit Assess 133:473–482. https://doi.org/10.1007/s10661-006-9602-1
Joshi YK, Tortajada C, Biswas AK (2012) Cleaning of the Singapore River and Kallang Basin in Singapore: human and environmental dimensions. Ambio 41:777–781. https://doi.org/10.1007/s13280-012-0279-0
Kaki C, Guedenon P, Kelome N et al (2011) Evaluation of heavy metals pollution of Nokoue Lake. Afr J Environ Sci Technol 5:255–261
Kakpo SB, Aoudji AKN, Gnanguènon-Guéssè D et al (2019) Spatial distribution and impacts of climate change on Milicia excelsa in Benin, West Africa. J For Res. https://doi.org/10.1007/s11676-019-01069-7
Kassambara A, Mundt F (2019) Package “factoextra”: extract and visualize the Results of multivariate data analyses. R package version 1.0.6. https://cran.r-project.org/src/contrib/Archive/factoextra/factoextra_1.0.6.tar.gz
Kohonen T (1990) The Self-Organizing map. Proc IEEE 78:1464–1480. https://doi.org/10.1109/5.58325
Kohonen V (2001) Towards experiential foreign language education. In: Kohonen V, Jaatinen R, Kaikkonen P, Lehtovaara J (eds) Experiential learning in foreign language education. Routledge: Taylor and Francis Group, Milton Park, Oxfordshire, pp 8–60
Kohonen T (2013) Essentials of the self-organizing map. Neural Netw 37:52–65. https://doi.org/10.1016/j.neunet.2012.09.018
Koné T, Teugels GG, N’Douba V et al (2003) Fish assemblages in relation to environmental gradients along a small west African coastal basin, the San Pedro River, Ivory Coast. Afr J Aquat Sci 28:163–168. https://doi.org/10.2989/16085910309503780
Kouamélan EP, Teugels GG, N’Douba VN et al (2003) Fish diversity and its relationships with environmental variables in a West African basin. Hydrobiologia 505:139–146. https://doi.org/10.1023/b:hydr.0000007302.74296.84
Koudenoukpo C (2018) Evaluation de la qualité écologique de la rivière So au Sud Benin: diversité et distribution des assemblages de zooplancton et des macroinvertébrés aquatiques. PhD Thesis. Université d’Abomey-Calavi, Bénin
Koudenoukpo ZC, Odountan OH, Van Bocxlaer B et al (2020) Checklist of the fresh and brackish water snails (Mollusca, Gastropoda) of Bénin and adjacent West African ecoregions. Zookeys 942:21–64. https://doi.org/10.3897/zookeys.942.52722
Koudenoukpo ZC, Odountan OH, Agboho PA et al (2021) Using self–organizing maps and machine learning models to assess mollusc community structure in relation to physicochemical variables in a West Africa river–estuary system. Ecol Indic 126:107706. https://doi.org/10.1016/j.ecolind.2021.107706
Legendre P, Legendre L (2012) Numerical ecology, 3rd edn. Elsevier Science Publishers B.V, Amsterdam
Li T, Sun G, Yang C et al (2018) Using self-organizing map for coastal water quality classification: Towards a better understanding of patterns and processes. Sci Total Environ 628–629:1446–1459. https://doi.org/10.1016/j.scitotenv.2018.02.163
Liao X, Tao H, Gong X, Li Y (2019) Exploring the database of a soil environmental survey using a geo-self-organizing map: a pilot study. J Geogr Sci 29:1610–1624. https://doi.org/10.1007/s11442-019-1644-8
Mama D (2010) Méthodologie et résultats du diagnostic de l’eutrophisation du Lac Nokoue (Bénin). PhD Thesis. Université de Limoges, France
Mamun M, An K-G (2018) Ecological health assessments of 72 streams and rivers in relation to water chemistry and land-use patterns in South Korea. Turk J Fish Aquat Sci 18:871–880. https://doi.org/10.4194/1303-2712-v18_7_05
McClure M (2021) What are the causes and effects of water pollution in Africa?
Najar IA, Khan AB (2012) Assessment of water quality and identification of pollution sources of three lakes in Kashmir, India, using multivariate analysis. Environ Earth Sci 66:2367–2378. https://doi.org/10.1007/s12665-011-1458-1
Odountan OH, Janssens de Bisthoven L, Koudenoukpo CZ, Abou Y (2019) Spatio-temporal variation of environmental variables and aquatic macroinvertebrate assemblages in Lake Nokoué, a RAMSAR site of Benin. Afr J Aquat Sci 44:219–231. https://doi.org/10.2989/16085914.2019.1629272
Olawoyin R, Nieto A, Grayson RL et al (2013) Application of artificial neural network (ANN)–self-organizing map (SOM) for the categorization of water, soil and sediment quality in petrochemical regions. Expert Syst Appl 40:3634–3648. https://doi.org/10.1016/j.eswa.2012.12.069
Olkowska E, Kudłak B, Tsakovski S et al (2014) Assessment of the water quality of Kłodnica River catchment using self-organizing maps. Sci Total Environ 476–477:477–484. https://doi.org/10.1016/j.scitotenv.2014.01.044
OmiDelta–INE (2018) Planification Delta: Préparation et organisation. Abomey-Calavi, Benin
Pacheco FS, Miranda M, Pezzi LP et al (2017) Water quality longitudinal profile of the Paraíba do Sul River, Brazil during an extreme drought event. Limnol Oceanogr 62:S131–S146. https://doi.org/10.1002/lno.10586
Park Y-S, Kwon Y-S, Hwang S-J, Park S (2014) Characterizing effects of landscape and morphometric factors on water quality of reservoirs using a self-organizing map. Environ Model Softw 55:214–221. https://doi.org/10.1016/j.envsoft.2014.01.031
Park Y-S, Chon T-S, Bae M-J et al (2018) Multivariate data analysis by means of Self-Organizing Maps. In: Recknagel F, Michener WK (eds) Ecological Informatics. Springer International Publishing, Cham, pp 251–272
Peterson BG, Carl P, Boudt K et al (2020) Package “Performance Analytics”: econometric tools for performance and risk analysis. R package version 2.0.4. https://cran.r-project.org/web/packages/PerformanceAnalytics/index.html
R Core Team (2018) R: a language and environment for statistical computing. Version 3.5.2. https://cran.r-project.org/bin/windows/base/old/3.5.2/
Ren W, Zhong Y, Meligrana J et al (2003) Urbanization, land use, and water quality in Shanghai 1947–1996. Environ Int 29:649–659. https://doi.org/10.1016/S0160-4120(03)00051-5
Rice EW, Baird RB, Eaton AD, Clesceri LS (2012) Standard methods for the examination of water and wastewater. American Public Health Association, 22nd edn. American Water Works Association, Water Environment Federation, Washington
Rodier J, Legube B, Merlet N et al (2009) L’analyse de l’eau. 9ème edition entièrement mise à jour. Dunod, Paris
Rodrigues V, Estrany J, Ranzini M et al (2018) Effects of land use and seasonality on stream water quality in a small tropical catchment: the headwater of Córrego Água Limpa, São Paulo (Brazil). Sci Total Environ 622–623:1553–1561. https://doi.org/10.1016/j.scitotenv.2017.10.028
Subida MD, Berihuete A, Drake P, Blasco J (2013) Multivariate methods and artificial neural networks in the assessment of the response of infaunal assemblages to sediment metal contamination and organic enrichment. Sci Total Environ 450–451:289–300. https://doi.org/10.1016/j.scitotenv.2013.02.009
Totin VSH (2010) Sensibilité des eaux souterraines du bassin sédimentaire côtier du Bénin à l’évolution du climat et aux modes d’exploitation : stratégies de gestion durable. PhD Thesis. Université d’Abomey-Calavi, Bénin
Tsai W-P, Huang S-P, Cheng S-T et al (2017) A data-mining framework for exploring the multi-relation between fish species and water quality through self-organizing map. Sci Total Environ 579:474–483. https://doi.org/10.1016/j.scitotenv.2016.11.071
Tu J (2009) Combined impact of climate and land use changes on streamflow and water quality in eastern Massachusetts, USA. J Hydrol 379:268–283. https://doi.org/10.1016/j.jhydrol.2009.10.009
UNEP (2010) Africa Water Atlas. UNEP, Nairobi, Kenya
Ustaoğlu F, Tepe Y (2019) Water quality and sediment contamination assessment of Pazarsuyu Stream, Turkey using multivariate statistical methods and pollution indicators. Int Soil Water Conserv Res 7:47–56. https://doi.org/10.1016/j.iswcr.2018.09.001
Vadde K, Wang J, Cao L et al (2018) Assessment of water quality and identification of pollution risk locations in Tiaoxi River (Taihu Watershed), China. Water (Basel) 10:183. https://doi.org/10.3390/w10020183
Vesanto J, Himberg J, Alhoniemi E, Parhankangas J (2000) SOM Toolbox for Matlab 5. Technical Report A57, Helsinki
Wang X, Zhang F (2018) Effects of land use/cover on surface water pollution based on remote sensing and 3D-EEM fluorescence data in the Jinghe Oasis. Sci Rep 8:1–13. https://doi.org/10.1038/s41598-018-31265-0
Wang J, Liu G, Liu H, Lam PKS (2017) Multivariate statistical evaluation of dissolved trace elements and a water quality assessment in the middle reaches of Huaihe River, Anhui, China. Sci Total Environ 583:421–431. https://doi.org/10.1016/j.scitotenv.2017.01.088
Wehrens R, Kruisselbrink J (2018) Flexible Self-Organizing Maps in Kohonen 3.0. J Stat Softw 87:1–18. https://doi.org/10.18637/jss.v087.i07
Wendel J, Buttenfield BP (2010) Formalizing guidelines for building meaningful Self- Organizing Maps. In: Sixth International Conference on Geographic Information Science. Zurich, Swithzerland, p 6
WFD (2005) Overall approach to the classification of ecological status and ecological potential. Bruxelles, Belgique
WHO (2011) Guidelines for drinking-water quality, 4th edn. Geneva, Switzerland
Wickham H, François R, Henry L, Müller K (2020) Package ‘dplyr’: A Grammar of Data Manipulation. R package Version 0.8.5. https://cran.r-project.org/src/contrib/Archive/dplyr/dplyr_0.8.5.tar.gz
Xu Z, Shen J, Qu Y et al (2022) Using simple and easy water quality parameters to predict trihalomethane occurrence in tap water. Chemosphere 286:131586. https://doi.org/10.1016/j.chemosphere.2021.131586
Zhang Z, Juying L, Mamat Z, Qingfu Y (2016) Sources identification and pollution evaluation of heavy metals in the surface sediments of Bortala River, Northwest China. Ecotoxicol Environ Saf 126:94–101. https://doi.org/10.1016/j.ecoenv.2015.12.025
Zhao Y, Xia XH, Yang ZF, Wang F (2012) Assessment of water quality in Baiyangdian Lake using multivariate statistical techniques. Procedia Environ Sci 13:1213–1226. https://doi.org/10.1016/j.proenv.2012.01.115
Zhu G, Wu X, Ge J et al (2020) Influence of mining activities on groundwater hydrochemistry and heavy metal migration using a self-organizing map (SOM). J Clean Prod 257:120664. https://doi.org/10.1016/j.jclepro.2020.120664
Acknowledgements
ZCK and OHO acknowledge CAPE BIO NGO through the Biodiversity and Sustainable Productivity of Aquatic Ecosystem of Ouémé Delta project. Special thanks are due to Dèdéou Apocalypse Tchokponhoue for the valuable comments on the first draft of the manuscript.
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This study was supported by the grant provided by the Benin Higher Ministry of Education and Scientific Research to ZCK.
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ZCK: conceptualization, methodology, investigation, funding acquisition, resources, data curation, writing—review and editing; OHO: conceptualization, methodology, data curation, formal analysis, software, validation, visualization, writing—original draft, writing—review and editing; CG: methodology, validation, writing—review and editing; RC: methodology, data curation, validation, visualization, writing—review and editing; AC: conceptualization, methodology, funding acquisition, resources, writing—review and editing; Y-SP: conceptualization, methodology, writing—review and editing. All authors read and approved the manuscript.
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Koudenoukpo, Z.C., Odountan, O.H., Guo, C. et al. Understanding the patterns and processes underlying water quality and pollution risk in West–Africa River using self-organizing maps and multivariate analyses. Environ Sci Pollut Res 30, 11893–11912 (2023). https://doi.org/10.1007/s11356-022-22784-5
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DOI: https://doi.org/10.1007/s11356-022-22784-5