Biogeochemical and isotopic study in groundwater near waste dumps in a fractured and urban environment : case of the municipality of Ouagadougou (Burkina Faso)

Les décharges d'ordures fonctionnent comme des bioréacteurs dont les processus fermentaires sont intenses et produisent des lixiviats riches en matière organique, azotée et métallique. Cette étude porte sur le développement d’un modèle conceptuel de la propagation latérale des polluants et leur biodégradation dans un aquifère cristallin fracturé, sous un climat tropical semi-aride, dans la ville de Ouagadougou, Burkina Faso. Une combinaison de techniques géophysiques (Potentiel Spontané), biogéochimique, thermodynamique, isotopiques et des traitements géostatistiques (ACP, AFD, CAH, EMMA et Monte-Carlo), ont permis : (1) de cartographier le panache de pollution, (2) de mettre en évidence une biodégradation importante du TOC issu des lixiviats grâce au couplage de plusieurs éléments chimiques, (3) de montrer un nombre élevé de contamination métallique et (4) de mettre en évidence les processus de mélange des eaux souterraines et les sources de pollution autres que les lixiviats. L’analyse de ces résultats démontre la grande complexité du modèle conceptuel de contamination de l'aquifère fracturé de Ouagadougou, en raison de plusieurs facteurs. Ces facteurs incluent (1) la grande diversité de situations et de compositions des décharges d'ordures, (2) l'hétérogénéité spatiale de la composition des lixiviats qui pénètrent dans la nappe phréatique, (3) l’hétérogénéité des lignes de flux de pollution suivant la structure fracturée de l’aquifère et provenant d'autres sources en amont de la décharge, notamment les fertilisations agricoles et la position des puits perdus, et (4) la biodégradation complexe et dynamique qui se produit dans le panache de polluant.Landfills function as bioreactors, generating intense fermentative processes that produce leachates rich in organic, nitrogenous, and metallic matter. This study focuses on the development of a conceptual model for the lateral propagation and biodegradation of pollutants in a fractured crystalline aquifer, under a semi-arid tropical climate in Ouagadougou, Burkina Faso. A combination of geophysical (Spontaneous Potential), biogeochemical, thermodynamic, isotopic techniques, together with geostatistical treatments (PCA, AFD, CAH, EMMA, and Monte-Carlo) allowed: (1) to delineate of the pollution plume, (2) to highlight significant biodegradation of TOC from leachates by coupling with various chemical elements, (3) to reveal high levels of metal contamination, and (4) to identify the groundwater mixing processes and sources of pollution other than leachates. The analysis of these results demonstrates the high complexity of the conceptual model of contamination of the fractured aquifer in Ouagadougou, due to several factors, namely, (1) a great diversity of situations and compositions of waste dumps, (2) a spatial heterogeneity of the composition of leachates that flow towards the groundwater table, (3) the heterogeneity of the pollution flow lines following the fractured structure of the aquifer and originating from other sources upstream of the dump, including agricultural fertilization and the position of sinkholes, and (4) the complex and dynamic biodegradation that occurs within the pollutant plume

Étude biogéochimique et isotopique dans les eaux souterraines au voisinage des décharges d’ordures en milieu fracturé et urbain : cas de la commune de Ouagadougou (Burkina Faso)

Landfills function as bioreactors, generating intense fermentative processes that produce leachates rich in organic, nitrogenous, and metallic matter. This study focuses on the development of a conceptual model for the lateral propagation and biodegradation of pollutants in a fractured crystalline aquifer, under a semi-arid tropical climate in Ouagadougou, Burkina Faso. A combination of geophysical (Spontaneous Potential), biogeochemical, thermodynamic, isotopic techniques, together with geostatistical treatments (PCA, AFD, CAH, EMMA, and Monte-Carlo) allowed: (1) to delineate of the pollution plume, (2) to highlight significant biodegradation of TOC from leachates by coupling with various chemical elements, (3) to reveal high levels of metal contamination, and (4) to identify the groundwater mixing processes and sources of pollution other than leachates. The analysis of these results demonstrates the high complexity of the conceptual model of contamination of the fractured aquifer in Ouagadougou, due to several factors, namely, (1) a great diversity of situations and compositions of waste dumps, (2) a spatial heterogeneity of the composition of leachates that flow towards the groundwater table, (3) the heterogeneity of the pollution flow lines following the fractured structure of the aquifer and originating from other sources upstream of the dump, including agricultural fertilization and the position of sinkholes, and (4) the complex and dynamic biodegradation that occurs within the pollutant plume.Les décharges d'ordures fonctionnent comme des bioréacteurs dont les processus fermentaires sont intenses et produisent des lixiviats riches en matière organique, azotée et métallique. Cette étude porte sur le développement d’un modèle conceptuel de la propagation latérale des polluants et leur biodégradation dans un aquifère cristallin fracturé, sous un climat tropical semi-aride, dans la ville de Ouagadougou, Burkina Faso. Une combinaison de techniques géophysiques (Potentiel Spontané), biogéochimique, thermodynamique, isotopiques et des traitements géostatistiques (ACP, AFD, CAH, EMMA et Monte-Carlo), ont permis : (1) de cartographier le panache de pollution, (2) de mettre en évidence une biodégradation importante du TOC issu des lixiviats grâce au couplage de plusieurs éléments chimiques, (3) de montrer un nombre élevé de contamination métallique et (4) de mettre en évidence les processus de mélange des eaux souterraines et les sources de pollution autres que les lixiviats. L’analyse de ces résultats démontre la grande complexité du modèle conceptuel de contamination de l'aquifère fracturé de Ouagadougou, en raison de plusieurs facteurs. Ces facteurs incluent (1) la grande diversité de situations et de compositions des décharges d'ordures, (2) l'hétérogénéité spatiale de la composition des lixiviats qui pénètrent dans la nappe phréatique, (3) l’hétérogénéité des lignes de flux de pollution suivant la structure fracturée de l’aquifère et provenant d'autres sources en amont de la décharge, notamment les fertilisations agricoles et la position des puits perdus, et (4) la biodégradation complexe et dynamique qui se produit dans le panache de polluant

Surface Formations Salinity Survey in an Estuarine Area of Northern Morocco, by Crossing Satellite Imagery, Discriminant Analysis, and Machine Learning

The salinity of estuarine areas in arid or semi-arid environments can reach high values, conditioning the distribution of vegetation and soil surface characteristics. While many studies focused on the prediction of soil salinity as a function of numerous parameters, few attempted to explain the role of salinity and its distribution within the soil profile in the pattern of landscape units. In a wadi estuary in northern Morocco, landscape units derived from satellite imagery and naturalistic environmental analysis are compared with a systematic survey of salinity by means of apparent electrical conductivity (Eca) measurements. The comparison is based on the allocation of measurement points to an area of the estuary from Eca measurements alone, using linear discriminant analysis and four machine learning methods. The results show that between 57 and 66% of the points are well-classified, highlighting that salinity is a major factor in the discrimination of estuary zones. The distribution of salinity is mainly the result of the interaction between capillary rise and flooding by the tides and the wadi. The location of the misclassified points is analysed and discussed, as well as the possible causes of the confusions

Groundwater Bodies Subdivision in Corsica: A Critical Approach Based on Multivariate Water Quality Criteria Using Large Database

International audienceThe cross-referencing of two databases, namely the compartmentalization into groundwater bodies (GWB) and the quality monitoring (2830 observations including 15 physico-chemical and bacteriological parameters, on 662 collection points and over a period of 27 years) is applied to better understand the diversity of the waters of the island of Corsica (France) and to facilitate the surveillance and quality monitoring of the groundwater resource. Data conditioning (log-transformation), dimensional reduction (PCA), classification (AHC) and then quantification of the information lost during grouping (ANOVA), highlight the need to subdivide the groundwater bodies in the crystalline part of the island in order to take better account of lithological diversity and other environmental factors (slope, altitude, soil thickness, etc.). The compartmentalization into 15 units, mainly based on structural geology, provides less information than the grouping into 12 units after subdivision of the crystalline region. The diversity of the waters in terms of chemical and bacteriological composition is discussed, and the results encourage a review of the compartmentalization of the island's GWBs, with a view to more targeted monitoring based on this diversity

Differentiation of Sahelian aquifers from chemical and isotopic composition using linear statistics and machine learning

In Sahelian Africa, the characteristics of boreholes are often lost and, when several aquifers are present on the same site, it is difficult to know which one is being tapped or is likely to be contaminated, which hinders good management of the resource. In this study conducted on 153 wells distributed in the 4 major aquifers of Burkina Faso, the variations in chemical composition within the aquifers is high compared to that between the aquifers. In spite of this, a treatment by linear statistical analysis and/or machine learning, allows to discriminate the aquifers with a success rate of about 80%. The introduction of water isotopes as an additional parameter and a dimensional reduction by principal component analysis allowed a discrimination rate of 87.6% to be achieved. The pathway of water from sedimentary to basement aquifers explains some of the confusions.</p

Differentiation of Multi-Parametric Groups of Groundwater Bodies through Discriminant Analysis and Machine Learning

International audienceIn order to facilitate the monitoring of groundwater quality in France, the groundwater bodies (GWB) in the Provence-Alpes-Côte d'Azur region have been grouped into 11 homogeneous clusters on the basis of their physico-chemical and bacteriological characteristics. This study aims to test the legitimacy of this grouping by predicting whether water samples belong to a given sampling point, GWB or group of GWBs. To this end, 8673 observations and 18 parameters were extracted from the Size-Eaux database, and this dataset was processed using discriminant analysis and various machine learning algorithms. The results indicate an accuracy of 67% using linear discriminant analysis and 69 to 83% using ML algorithms, while quadratic discriminant analysis underperforms in comparison, yielding a less accurate prediction of 59%. The importance of each parameter in the prediction was assessed using an approach combining recursive feature elimination (RFE) techniques and random forest feature importance (RFFI). Major ions show high spatial range and play the main role in discrimination, while trace elements and bacteriological parameters of high local and/or temporal variability only play a minor role. The disparity of the results according to the characteristics of the GWB groups (geography, altitude, lithology, etc.) is discussed. Validating the grouping of GWBs will enable monitoring and surveillance strategies to be redirected on the basis of fewer, homogeneous hydrogeological units, in order to optimize sustainable management of the resource by the health agencies